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| {{#Wiki_filter:VmGINIA ELECTRIC AND POWER COMPANY RICHMOND, VmGJNIA 23261 September 13, 2022 U.S. Nuclear Regulatory Commission Serial No.: 22-263 Attention: Document Control Desk NRA/ENC: RO Washington, DC 20555-0001 Docket Nos.: 50-338/339 License Nos.: NPF-4/7 VIRGINIA ELECTRIC AND POWER COMPANY {DOMINION ENERGY VIRGINIA) | | {{#Wiki_filter:}} |
| NORTH ANNA POWER STATION UNITS 1 AND 2 10 CFR 50, APPENDIX E1 EVACUATION TIME ESTIMATES Pursuant to 10 CFR 50, Appendix E, Section IV.41 Virginia Electric and Power Company
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| {Dominion Energy Virginia) submits the enclosed evacuation time estimates {ETE) study for North Anna Power Station (NAPS) Units 1 and 2.
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| The enclosed NAPS ETE study was developed using the 2020 decennial census data from the U. S. Census Bureau and provides the methods used to derive, for planning purposes, the time for public evacuation. The study provides an important part of the bases for development of protective action recommendations in coordination with the applicable offsite state/local emergency response agencies.
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| If you have any questions or require additional information, please contact Ms. Erica N.
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| Combs at {804) 273-3386.
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| Sincerely, Lisa A. Hilbert Site Vice President - North Anna Power Station Dominion Energy Virginia Commitments made inc this letter: None
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| ==Enclosure:==
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| North Anna Power Station Development of Evacuation Time Estimates
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| Serial No.: 22-263 Docket Nos.: 50-338/339 Page 2 of 2 cc: Regional Administrator, Region II U.S. Nuclear Regulatory Commission Marquis One Tower 245 Peachtree Center Avenue, NE Suite 1200 Atlanta, Georgia 30303-1257 Mr. G. E. Miller NRC Senior Project Manager U.S. Nuclear Regulatory Commission Mail Stop 09 E-3 One White Flint North 11555 Rockville Pike Rockville, Maryland 20852-2738 NRC Senior Resident Inspector North Anna Power Station Old Dominion Electric Cooperative R-North-Anna-Correspondence@odec.com
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| Serial No.: 22-263 Docket Nos.: 50-338/339 ENCLOSURE North Anna Power Station Development of Evacuation Time Estimates NORTH ANNA POWER STATION UNITS 1 AND 2 VIRGINIA ELECTRIC AND POWER COMPANY (DOMINION ENERGY VIRGINIA)
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| North Anna Power Station Development of Evacuation Time Estimates Work performed for Dominion Energy, by:
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| KLD Engineering, P.C.
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| 1601 Veterans Memorial Highway, Suite 340 Islandia, NY 11749 Email: kweinisch@kldcompanies.com August 22, 2022 Final Report, Rev. 0 KLD TR - 1258
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| Table of Contents EXECUTIVE
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| ==SUMMARY==
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| .................................................................................................................................. 1 1 INTRODUCTION .................................................................................................................................. 11 1.1 Overview of the ETE Process...................................................................................................... 11 1.2 The North Anna Power Station Location ................................................................................... 13 1.3 Preliminary Activities ................................................................................................................. 13 1.4 Comparison with Prior ETE Study .............................................................................................. 16 2 STUDY ESTIMATES AND ASSUMPTIONS ............................................................................................ 21 2.1 Data Estimates Assumptions...................................................................................................... 21 2.2 Methodological Assumptions .................................................................................................... 21 2.3 Study Assumptions on Mobilization Times ................................................................................ 23 2.4 Transit Dependent Assumptions ................................................................................................ 23 2.5 Traffic and Access Control Assumptions .................................................................................... 25 2.6 Scenarios and Regions ............................................................................................................... 25 3 DEMAND ESTIMATION ....................................................................................................................... 31 3.1 Permanent Residents ................................................................................................................. 32 3.2 Shadow Population .................................................................................................................... 32 3.3 Transient Population .................................................................................................................. 33 3.3.1 Seasonal Transient Population........................................................................................... 33 3.4 Employees .................................................................................................................................. 34 3.5 Medical Facilities ........................................................................................................................ 34 3.6 Transit Dependent Population ................................................................................................... 35 3.7 School Population Demand........................................................................................................ 37 3.8 Special Event .............................................................................................................................. 37 3.9 Access and/or Functional Needs Population ............................................................................. 38 3.10 External Traffic ........................................................................................................................... 38 3.11 Background Traffic ..................................................................................................................... 39 3.12 Summary of Demand ................................................................................................................. 39 4 ESTIMATION OF HIGHWAY CAPACITY ............................................................................................... 41 4.1 Capacity Estimations on Approaches to Intersections .............................................................. 42 4.2 Capacity Estimation along Sections of Highway ........................................................................ 44 4.3 Application to the NAPS Study Area .......................................................................................... 46 4.3.1 TwoLane Roads ................................................................................................................. 46 4.3.2 Multilane Highway ............................................................................................................. 46 4.3.3 Freeways ............................................................................................................................ 47 4.3.4 Intersections ...................................................................................................................... 48 4.4 Simulation and Capacity Estimation .......................................................................................... 48 4.5 Boundary Conditions .................................................................................................................. 49 5 ESTIMATION OF TRIP GENERATION TIME.......................................................................................... 51 5.1 Background ................................................................................................................................ 51 5.2 Fundamental Considerations ..................................................................................................... 53 5.3 Estimated Time Distributions of Activities Preceding Event 5 ................................................... 54 North Anna Power Station i KLD Engineering, P.C.
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| 5.4 Calculation of Trip Generation Time Distribution ...................................................................... 55 5.4.1 Statistical Outliers .............................................................................................................. 55 5.4.2 Staged Evacuation Trip Generation ................................................................................... 58 5.4.3 Trip Generation for Waterways and Recreational Areas ................................................... 59 6 EVACUATION CASES ........................................................................................................................... 61 7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE) .......................................................... 71 7.1 Voluntary Evacuation and Shadow Evacuation ......................................................................... 71 7.2 Staged Evacuation ...................................................................................................................... 72 7.3 Patterns of Traffic Congestion during Evacuation ..................................................................... 72 7.4 Evacuation Rates ........................................................................................................................ 74 7.5 Evacuation Time Estimate Results ............................................................................................. 74 7.6 Staged Evacuation Results ......................................................................................................... 76 7.7 Guidance on Using ETE Tables ................................................................................................... 77 8 TRANSITDEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES ................................. 81 8.1 ETE for Schools, PreSchools, Transit Dependent People, and Medical Facilities ..................... 82 8.2 ETE for Access and/or Functional Needs Population ................................................................. 87 9 TRAFFIC MANAGEMENT STRATEGY ................................................................................................... 91 9.1 Assumptions ............................................................................................................................... 92 9.2 Additional Considerations .......................................................................................................... 92 10 EVACUATION ROUTES AND EVACUATION ASSEMBLY CENTERS ..................................................... 101 10.1 Evacuation Routes.................................................................................................................... 101 10.2 Evacuation Assembly Centers .................................................................................................. 102 List of Appendices A. GLOSSARY OF TRAFFIC ENGINEERING TERMS .................................................................................. A1 B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL ......................................................... B1 B.1 Overview of Integrated Distribution and Assignment Model .................................................... B1 B.2 Interfacing the DYNEV Simulation Model with DTRAD .............................................................. B2 B.2.1 DTRAD Description ............................................................................................................. B2 B.2.2 Network Equilibrium .......................................................................................................... B4 C. DYNEV TRAFFIC SIMULATION MODEL ............................................................................................... C1 C.1 Methodology .............................................................................................................................. C2 C.1.1 The Fundamental Diagram ................................................................................................. C2 C.1.2 The Simulation Model ........................................................................................................ C2 C.1.3 Lane Assignment ................................................................................................................ C6 C.2 Implementation ......................................................................................................................... C6 C.2.1 Computational Procedure .................................................................................................. C6 C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD) ..................................................... C7 North Anna Power Station ii KLD Engineering, P.C.
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| D. DETAILED DESCRIPTION OF STUDY PROCEDURE .............................................................................. D1 E. SPECIAL FACILITY DATA ...................................................................................................................... E1 F. DEMOGRAPHIC SURVEY..................................................................................................................... F1 F.1 Introduction ............................................................................................................................... F1 F.2 Survey Instrument and Sampling Plan ....................................................................................... F1 F.3 Survey Results ............................................................................................................................ F2 F.3.1 Household Demographic Results ........................................................................................... F2 F.3.2 Evacuation Response ............................................................................................................. F3 F.3.3 Time Distribution Results ....................................................................................................... F4 F.3.4 Emergency Communications ................................................................................................. F5 G. TRAFFIC MANAGEMENT PLAN .......................................................................................................... G1 G.1 Manual Traffic Control .............................................................................................................. G1 G.2 Analysis of Key TCP/ACP Locations ........................................................................................... G1 H EVACUATION REGIONS ..................................................................................................................... H1 J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM ..................................... J1 K. EVACUATION ROADWAY NETWORK.................................................................................................. K1 L. PAZ BOUNDARIES............................................................................................................................... L1 M. EVACUATION SENSITIVITY STUDIES ................................................................................................. M1 M.1 Effect of Changes in Trip Generation Time .............................................................................. M1 M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate ................. M1 M.3 Effect of Changes in EPZ Resident Population ......................................................................... M2 M.4 Effect of Changes in Average Household Size .......................................................................... M3 M.5 Enhancements in Evacuation Time .......................................................................................... M3 N. ETE CRITERIA CHECKLIST ................................................................................................................... N1 Note: Appendix I intentionally skipped North Anna Power Station iii KLD Engineering, P.C.
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| List of Figures Figure 11. NAPS Location ....................................................................................................................... 113 Figure 12. NAPS LinkNode Analysis Network ........................................................................................ 114 Figure 21. Voluntary Evacuation Methodology ....................................................................................... 28 Figure 31. PAZs Comprising the NAPS EPZ.............................................................................................. 320 Figure 32. Permanent Resident Population by Sector ............................................................................ 321 Figure 33. Permanent Resident Vehicles by Sector ................................................................................ 322 Figure 34. Shadow Population by Sector ................................................................................................ 323 Figure 35. Shadow Vehicles by Sector .................................................................................................... 324 Figure 36. Transient Population by Sector.............................................................................................. 325 Figure 37. Transient Vehicles by Sector .................................................................................................. 326 Figure 38. Employee Population by Sector ............................................................................................. 327 Figure 39. Employee Vehicles by Sector ................................................................................................. 328 Figure 41. Fundamental Diagrams .......................................................................................................... 410 Figure 51. Events and Activities Preceding the Evacuation Trip ............................................................ 517 Figure 52. Time Distributions for Evacuation Mobilization Activities.................................................... 518 Figure 53. Comparison of Data Distribution and Normal Distribution....................................................... 519 Figure 54. Comparison of Trip Generation Distributions....................................................................... 520 Figure 55. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5Mile Region
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| ................................................................................................................................................................. 521 Figure 61. PAZs Comprising the NAPS EPZ ............................................................................................... 69 Figure 71. Voluntary Evacuation Methodology ..................................................................................... 722 Figure 72. NAPS Shadow Region ............................................................................................................. 723 Figure 73. Congestion Patterns at 30 Minutes after the Advisory to Evacuate ..................................... 724 Figure 74. Congestion Patterns at 1 Hour after the Advisory to Evacuate ............................................. 725 Figure 75. Congestion Patterns at 1 Hour and 30 Minutes after the Advisory to Evacuate .................. 726 Figure 76. Congestion Patterns at 2 Hours after the Advisory to Evacuate ........................................... 727 Figure 77. Congestion Patterns at 2 Hours and 30 Minutes after the Advisory to Evacuate ................. 728 Figure 78. Congestion Patterns at 3 Hours after the Advisory to Evacuate ........................................... 729 Figure 79. Evacuation Time Estimates Scenario 1 for Region R03 ...................................................... 730 Figure 710. Evacuation Time Estimates Scenario 2 for Region R03 .................................................... 730 Figure 711. Evacuation Time Estimates Scenario 3 for Region R03 .................................................... 731 Figure 712. Evacuation Time Estimates Scenario 4 for Region R03 .................................................... 731 Figure 713. Evacuation Time Estimates Scenario 5 for Region R03 .................................................... 732 Figure 714. Evacuation Time Estimates Scenario 6 for Region R03 .................................................... 732 Figure 715. Evacuation Time Estimates Scenario 7 for Region R03 .................................................... 733 Figure 716. Evacuation Time Estimates Scenario 8 for Region R03 .................................................... 733 Figure 717. Evacuation Time Estimates Scenario 9 for Region R03 .................................................... 734 Figure 718. Evacuation Time Estimates Scenario 10 for Region R03 .................................................. 734 Figure 719. Evacuation Time Estimates Scenario 11 for Region R03 .................................................. 735 Figure 720. Evacuation Time Estimates Scenario 12 for Region R03 .................................................. 735 Figure 721. Evacuation Time Estimates Scenario 13 for Region R03 .................................................. 736 Figure 722. Evacuation Time Estimates Scenario 14 for Region R03 .................................................. 736 Figure 81. Chronology of Transit Evacuation Operations ...................................................................... 817 Figure 101. Major Evacuation Routes within the NAPS EPZ .................................................................. 107 Figure 102. TransitDependent Bus Routes - Spotsylvania County....................................................... 108 North Anna Power Station iv KLD Engineering, P.C.
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| Figure 103. TransitDependent Bus Routes - Louisa County................................................................. 109 Figure 104. TransitDependent Bus Routes - Caroline, Hanover and Orange Counties .................... 1010 Figure 105. General Population Evacuation Assembly Centers ........................................................... 1011 Figure B1. Flow Diagram of SimulationDTRAD Interface........................................................................ B5 Figure C1. Representative Analysis Network ......................................................................................... C12 Figure C2. Fundamental Diagrams ......................................................................................................... C13 Figure C3. A UNIT Problem Configuration with t1 > 0 ........................................................................... C13 Figure C4. Flow of Simulation Processing (See Glossary: Table C3) .................................................... C14 Figure D1. Flow Diagram of Activities ..................................................................................................... D5 Figure E1. Schools and Preschools within the EPZ.................................................................................... E5 Figure E2. Medical Facilities within the EPZ ............................................................................................. E6 Figure E3. Major Employers within the EPZ.............................................................................................. E7 Figure E4. Recreational Areas within the EPZ ........................................................................................... E8 Figure E5. Lodging Facilities within the EPZ .............................................................................................. E9 Figure F1. Household Size in the EPZ ........................................................................................................ F8 Figure F2. Household Vehicle Availability ................................................................................................. F8 Figure F3. Vehicle Availability 1 to 6+ Person Households ..................................................................... F9 Figure F4. Household Ridesharing Preference ......................................................................................... F9 Figure F5. Commuters in Households in the EPZ .................................................................................... F10 Figure F6. Modes of Travel in the EPZ .................................................................................................... F10 Figure F7. Impact to Commuters due to COVID19 Pandemic ............................................................... F11 Figure F8. Households with Functional or Transportation Needs .......................................................... F11 Figure F9. Seasonal Residents in the EPZ................................................................................................ F12 Figure F10. Seasonal Residents Per Household ...................................................................................... F12 Figure F11. Number of Vehicles Used for Evacuation ............................................................................ F13 Figure F12. Percent of Households that Await Returning Commuter Before Leaving ........................... F13 Figure F13. Shelter in Place Characteristics ............................................................................................ F14 Figure F14. Shelter in Place Characteristics - Staged Evacuation .......................................................... F14 Figure F15. Study Area Evacuation Destinations .................................................................................... F15 Figure F16. Time Required to Prepare to Leave Work/College .............................................................. F15 Figure F17. Time to Commute Home from Work/College...................................................................... F16 Figure F18. Time to Prepare Home for Evacuation ................................................................................ F16 Figure F19. Time to Remove 68 of Snow from Driveway ................................................................... F17 Figure F20. Cell Phone Signal Reliability (for Phone Calls and/or Text Messages .................................. F17 Figure F21. Residents Compliance to Given Instruction (by Emergency Officials) ................................ F18 Figure F22. Perception of Public Alert Method ...................................................................................... F18 Figure G1. Access and Traffic Control Points for the North Anna Power Station ................................... G7 Figure H1. Region R01.............................................................................................................................. H4 Figure H2. Region R02.............................................................................................................................. H5 Figure H3. Region R03.............................................................................................................................. H6 Figure H4. Region R04.............................................................................................................................. H7 Figure H5. Region R05.............................................................................................................................. H8 Figure H6. Region R06.............................................................................................................................. H9 Figure H7. Region R07............................................................................................................................ H10 Figure H8. Region R08............................................................................................................................ H11 Figure H9. Region R09............................................................................................................................ H12 Figure H10. Region R10.......................................................................................................................... H13 North Anna Power Station v KLD Engineering, P.C.
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| Figure H11. Region R11.......................................................................................................................... H14 Figure H12. Region R12.......................................................................................................................... H15 Figure H13. Region R13.......................................................................................................................... H16 Figure H14. Region R14.......................................................................................................................... H17 Figure H15. Region R15.......................................................................................................................... H18 Figure H16. Region R16.......................................................................................................................... H19 Figure H17. Region R17.......................................................................................................................... H20 Figure H18. Region R18.......................................................................................................................... H21 Figure H19. Region R19.......................................................................................................................... H22 Figure H20. Region R20.......................................................................................................................... H23 Figure H21. Region R21.......................................................................................................................... H24 Figure H22. Region R22.......................................................................................................................... H25 Figure H23. Region R23.......................................................................................................................... H26 Figure H24. Region R24.......................................................................................................................... H27 Figure H25. Region R25.......................................................................................................................... H28 Figure H26. Region R26.......................................................................................................................... H29 Figure H27. Region R27.......................................................................................................................... H30 Figure H28. Region R28.......................................................................................................................... H31 Figure H29. Region R29.......................................................................................................................... H32 Figure H30. Region R30.......................................................................................................................... H33 Figure H31. Region R31.......................................................................................................................... H34 Figure H32. Region R32.......................................................................................................................... H35 Figure H33. Region R33.......................................................................................................................... H36 Figure H34. Region R34.......................................................................................................................... H37 Figure H35. Region R35.......................................................................................................................... H38 Figure H36. Region R36.......................................................................................................................... H39 Figure H37. Region R37.......................................................................................................................... H40 Figure H38. Region R38.......................................................................................................................... H41 Figure H39. Region R39.......................................................................................................................... H42 Figure H40. Region R40.......................................................................................................................... H43 Figure H41. Region R41.......................................................................................................................... H44 Figure H42. Region R42.......................................................................................................................... H45 Figure H43. Region R43.......................................................................................................................... H46 Figure H44. Region R44.......................................................................................................................... H47 Figure H45. Region R45.......................................................................................................................... H48 Figure H46. Region R46.......................................................................................................................... H49 Figure H47. Region R47.......................................................................................................................... H50 Figure H48. Region R48.......................................................................................................................... H51 Figure H49. Region R49.......................................................................................................................... H52 Figure H50. Region R50.......................................................................................................................... H53 Figure H51. Region R51.......................................................................................................................... H54 Figure H52. Region R52.......................................................................................................................... H55 Figure H53. Region R53.......................................................................................................................... H56 Figure H54. Region R54.......................................................................................................................... H57 Figure H55. Region R55.......................................................................................................................... H58 Figure J1. Network Sources/Origins.......................................................................................................... J7 Figure J2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1) .............. J8 North Anna Power Station vi KLD Engineering, P.C.
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| Figure J3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2) ............................... J8 Figure J4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3).............. J9 Figure J5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4) .............................. J9 Figure J6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)
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| ................................................................................................................................................................. J10 Figure J7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6) .............. J10 Figure J8. ETE and Trip Generation: Winter, Midweek, Midday, Rain/Light Snow (Scenario 7) ............ J11 Figure J9. ETE and Trip Generation: Winter, Midweek, Midday, Heavy Snow (Scenario 8) ................... J11 Figure J10. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 9) ............ J12 Figure J11. ETE and Trip Generation: Winter, Weekend, Midday, Rain/Light Snow (Scenario 10) ........ J12 Figure J12. ETE and Trip Generation: Winter, Weekend, Midday, Heavy Snow (Scenario 11) .............. J13 Figure J13. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 12)
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| ................................................................................................................................................................. J13 Figure J14. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather, Special Event (Scenario
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| : 13) ............................................................................................................................................................ J14 Figure J15. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 14) ............................................................................................................................................ J14 Figure K1. NAPS LinkNode Analysis Network .......................................................................................... K2 Figure K2. LinkNode Analysis Network - Grid 1 ..................................................................................... K3 Figure K3. LinkNode Analysis Network - Grid 2 ..................................................................................... K4 Figure K4. LinkNode Analysis Network - Grid 3 ..................................................................................... K5 Figure K5. LinkNode Analysis Network - Grid 4 ..................................................................................... K6 Figure K6. LinkNode Analysis Network - Grid 5 ..................................................................................... K7 Figure K7. LinkNode Analysis Network - Grid 6 ..................................................................................... K8 Figure K8. LinkNode Analysis Network - Grid 7 ..................................................................................... K9 Figure K9. LinkNode Analysis Network - Grid 8 ................................................................................... K10 Figure K10. LinkNode Analysis Network - Grid 9 ................................................................................. K11 Figure K11. LinkNode Analysis Network - Grid 10 ............................................................................... K12 Figure K12. LinkNode Analysis Network - Grid 11 ............................................................................... K13 Figure K13. LinkNode Analysis Network - Grid 12 ............................................................................... K14 Figure K14. LinkNode Analysis Network - Grid 13 ............................................................................... K15 Figure K15. LinkNode Analysis Network - Grid 14 ............................................................................... K16 Figure K16. LinkNode Analysis Network - Grid 15 ............................................................................... K17 Figure K17. LinkNode Analysis Network - Grid 16 ............................................................................... K18 Figure K18. LinkNode Analysis Network - Grid 17 ............................................................................... K19 Figure K19. LinkNode Analysis Network - Grid 18 ............................................................................... K20 Figure K20. LinkNode Analysis Network - Grid 19 ............................................................................... K21 Figure K21. LinkNode Analysis Network - Grid 20 ............................................................................... K22 Figure K22. LinkNode Analysis Network - Grid 21 ............................................................................... K23 Figure K23. LinkNode Analysis Network - Grid 22 ............................................................................... K24 Figure K24. LinkNode Analysis Network - Grid 23 ............................................................................... K25 Figure K25. LinkNode Analysis Network - Grid 24 ............................................................................... K26 Figure K26. LinkNode Analysis Network - Grid 25 ............................................................................... K27 Figure K27. LinkNode Analysis Network - Grid 26 ............................................................................... K28 Figure K28. LinkNode Analysis Network - Grid 27 ............................................................................... K29 Figure K29. LinkNode Analysis Network - Grid 28 ............................................................................... K30 Figure K30. LinkNode Analysis Network - Grid 29 ............................................................................... K31 North Anna Power Station vii KLD Engineering, P.C.
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| Figure K31. LinkNode Analysis Network - Grid 30 ............................................................................... K32 Figure K32. LinkNode Analysis Network - Grid 31 ............................................................................... K33 Figure K33. LinkNode Analysis Network - Grid 32 ............................................................................... K34 Figure K34. LinkNode Analysis Network - Grid 33 ............................................................................... K35 Figure K35. LinkNode Analysis Network - Grid 34 ............................................................................... K36 Figure K36. LinkNode Analysis Network - Grid 35 ............................................................................... K37 Figure K37. LinkNode Analysis Network - Grid 36 ............................................................................... K38 Figure K38. LinkNode Analysis Network - Grid 37 ............................................................................... K39 Figure K39. LinkNode Analysis Network - Grid 38 ............................................................................... K40 Figure K40. LinkNode Analysis Network - Grid 39 ............................................................................... K41 Figure K41. LinkNode Analysis Network - Grid 40 ............................................................................... K42 Figure K42. LinkNode Analysis Network - Grid 41 ............................................................................... K43 Figure K43. LinkNode Analysis Network - Grid 42 ............................................................................... K44 Figure K44. LinkNode Analysis Network - Grid 43 ............................................................................... K45 North Anna Power Station viii KLD Engineering, P.C.
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| List of Tables Table 11. Stakeholder Interaction ........................................................................................................... 18 Table 12. Highway Characteristics ........................................................................................................... 18 Table 13. ETE Study Comparisons ............................................................................................................ 19 Table 21. Evacuation Scenario Definitions............................................................................................... 27 Table 22. Model Adjustment for Adverse Weather................................................................................. 27 Table 31. EPZ Permanent Resident Population ...................................................................................... 310 Table 32. Permanent Resident Population and Vehicles by PAZ ............................................................ 311 Table 33. Shadow Population and Vehicles by Sector ............................................................................ 312 Table 34. Summary of Transients and Transient Vehicles ...................................................................... 313 Table 35. Summary of Employees and Employee Vehicles Commuting into the EPZ ............................ 314 Table 36. Medical Facility Transit Demand Estimates ............................................................................ 315 Table 37. TransitDependent Population Estimates ............................................................................... 315 Table 38. School and Preschool Population Demand Estimates ............................................................ 316 Table 39. Access and/or Functional Needs Demand Summary .............................................................. 316 Table 310. NAPS EPZ External Traffic...................................................................................................... 317 Table 311. Summary of Population Demand .......................................................................................... 318 Table 312. Summary of Vehicle Demand................................................................................................ 319 Table 51. Event Sequence for Evacuation Activities .............................................................................. 511 Table 52. Time Distribution for Notifying the Public ............................................................................. 511 Table 53. Time Distribution for Employees to Prepare to Leave Work and College ............................. 512 Table 54. Time Distribution for Commuters to Travel Home ................................................................ 512 Table 55. Time Distribution for Population to Prepare to Leave Home ................................................ 513 Table 56. Time Distribution for Population to Clear 6"8" of Snow from Driveway .............................. 513 Table 57. Mapping Distributions to Events ............................................................................................ 514 Table 58. Description of the Distributions ............................................................................................. 514 Table 59. Trip Generation Histograms for the EPZ Population for UnStaged Evacuation.................... 515 Table 510. Trip Generation Histograms for the EPZ Population for Staged Evacuation ....................... 516 Table 61. Description of Evacuation Regions........................................................................................... 64 Table 62. Evacuation Scenario Definitions............................................................................................... 66 Table 63. Percent of Population Groups Evacuating for Various Scenarios ............................................ 67 Table 64. Vehicle Estimates by Scenario.................................................................................................. 68 Table 71. Time to Clear the Indicated Area of 90 Percent of the Affected Population ......................... 710 Table 72. Time to Clear the Indicated Area of 100 Percent of the Affected Population ....................... 713 Table 73. Time to Clear 90 Percent of the 2Mile Region within the Indicated Region......................... 716 Table 74. Time to Clear 100 Percent of the 2Mile Region within the Indicated Region....................... 718 Table 75. Description of Evacuation Regions......................................................................................... 720 Table 81. Summary of Transportation Resources .................................................................................... 89 Table 82. School and PreSchool Evacuation Time Estimates - Good Weather .................................... 810 Table 83. School and PreSchool Evacuation Time Estimates - Rain/Light Snow ................................. 811 Table 84. School and PreSchool Evacuation Time Estimates - Heavy Snow ........................................ 812 Table 85. TransitDependent Evacuation Time Estimates Good Weather .......................................... 813 Table 86. TransitDependent Evacuation Time Estimates - Rain/Light Snow ....................................... 814 Table 87. Transit Dependent Evacuation Time Estimates - Heavy Snow .............................................. 815 Table 88. Medical Facilities Evacuation Time Estimates........................................................................ 816 Table 89. Access and/or Functional Needs Population Evacuation Time Estimates .............................. 816 North Anna Power Station ix KLD Engineering, P.C.
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| Table 101. Summary of TransitDependent Bus Routes ........................................................................ 103 Table 102. Bus Route Descriptions ........................................................................................................ 104 Table 103. School and Preschool Evacuation Assembly Centers ............................................................ 106 Table A1. Glossary of Traffic Engineering Terms .................................................................................... A1 Table C1. Selected Measures of Effectiveness Output by DYNEV II ........................................................ C8 Table C2. Input Requirements for the DYNEV II Model ........................................................................... C9 Table C3. Glossary ..................................................................................................................................C10 Table E1. Schools and Preschools within the EPZ ..................................................................................... E2 Table E2. Medical Facilities within the EPZ............................................................................................... E2 Table E3. Major Employers within the EPZ ............................................................................................... E3 Table E4. Recreational Areas within the EPZ ............................................................................................ E3 Table E5. Lodging Facilities within the EPZ ............................................................................................... E4 Table F1. North Anna Power Station Demographic Survey Sampling Plan and Results ........................... F7 Table G1. List of Key Manual Traffic Control Locations ........................................................................... G3 Table G2. ETE with No MTC .................................................................................................................... G6 Table H1. Percent of PAZ Population Evacuating for Each Region .......................................................... H2 Table J1. Sample Simulation Model Input ............................................................................................... J2 Table J2. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03) ........................... J3 Table J3. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Scenario 1) ................................................................................................................................................. J4 Table J4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 ......................... J5 Table K1. Summary of Nodes by the Type of Control ............................................................................... K1 Table M1. Evacuation Time Estimates for Trip Generation Sensitivity Study ....................................... M4 Table M2. Evacuation Time Estimates for Shadow Sensitivity Study .................................................... M4 Table M3. ETE Variation with Population Change ................................................................................. M5 Table M4. ETE Results for the Change in Average Household Size ........................................................ M5 Table N1. ETE Review Criteria Checklist .................................................................................................. N1 North Anna Power Station x KLD Engineering, P.C.
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| EXECUTIVE
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| ==SUMMARY==
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| This report describes the analyses undertaken and the results obtained by a study to develop Evacuation Time Estimates (ETE) for the North Anna Power Station (NAPS) located in Louisa County, Virginia. ETE are part of the required planning basis and provide Dominion Energy and state and local governments with sitespecific information needed for Protective Action decisionmaking.
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| In the performance of this effort, guidance is provided by documents published by Federal Governmental agencies. Most important of these are:
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| Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.
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| Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR7002, Rev. 1, February 2021.
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| Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG 0654/Radiological Emergency Preparedness Program Manual, FEMA P1028, December 2019.
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| Overview of Project Activities This project began in March 2021 and extended over a period of 17 months. The major activities performed are briefly described in chronological sequence:
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| Conducted a virtual kickoff meeting with Dominion Energy personnel and emergency management personnel representing state and county governments.
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| Accessed U.S. Census Bureau data files for the year 2020.
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| Studied Geographic Information Systems (GIS) maps of the area in the vicinity of the NAPS, then conducted a detailed field survey of the highway network to observe any roadway changes relative to the previous ETE study.
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| Updated the analysis network representing the highway system topology and capacities within the Emergency Planning Zone (EPZ), plus a Shadow Region covering the region between the EPZ boundary and approximately 15 miles radially from the plant.
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| Conducted a randomsample online demographic survey of residents within the EPZ, to gather focused data needed for this ETE study that were not contained within the census database. The survey instrument was reviewed and modified by the licensee and ORO personnel prior to the survey.
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| Data pertaining to employment, transients, and special facilities in each county were provided by Dominion Energy and by state and county offsite response organizations (OROs), supplemented with internet searches where data was missing.
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| The traffic demand and tripgeneration rates of evacuating vehicles were estimated from the gathered data. The trip generation rates reflected the estimated mobilization North Anna Power Station ES1 KLD Engineering, P.C.
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| time (i.e., the time required by evacuees to prepare for the evacuation trip) computed using the results of the demographic survey of EPZ residents.
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| The EPZ is subdivided into 25 PAZs. Following federal guidelines, these existing PAZs are grouped within circular areas or keyhole configurations (circles plus radial sectors) that define a total of 55 Evacuation Regions.
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| The timevarying external circumstances are represented as Evacuation Scenarios, each described in terms of the following factors: (1) Season (Summer, Winter); (2) Day of Week (Midweek, Weekend); (3) Time of Day (Midday, Evening); and (4) Weather (Good, Rain, Snow). One special event scenario - Kinetic Triathlon at Lake Anna State Park -
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| was considered. One roadway impact scenario was considered wherein a northbound segment of US522 NB at CR612 was closed for the duration of the evacuation.
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| Staged evacuation was considered for those regions wherein the 2Mile Region and sectors downwind to 5 miles were evacuated.
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| As per NUREG/CR7002, Rev. 1, the Planning Basis for the calculation of ETE is:
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| A rapidly escalating accident at the NAPS that quickly assumes the status of a general emergency wherein evacuation is ordered promptly, and no early protective action have been implemented such that the Advisory to Evacuate (ATE) is virtually coincident with the siren alert.
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| While an unlikely scenario, this planning basis will yield ETE, measured as the elapsed time from the ATE until the stated percentage of the population exits the impacted Region, that represent upper bound estimates. This conservative Planning Basis is applicable for all initiating events.
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| If the emergency occurs while schools and preschools are in session, the ETE study assumes that the children will be evacuated by bus directly to Evacuation Assembly Centers (EACs) located outside the EPZ. Parents, relatives, and neighbors are advised to not pick up their children at schools and preschools prior to the arrival of the buses dispatched for that purpose. The ETE for children at these facilities are calculated separately.
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| Evacuees who do not have access to a private vehicle will either rideshare with relatives, friends or neighbors, or be evacuated by buses provided as specified in the county and state Radiological Emergency Response Plans (RERP). Those in special facilities will likewise be evacuated with public transit, as needed: bus, wheelchair bus/van, or ambulance, as required. Separate ETE are calculated for the transit dependent evacuees, for access and/or functional needs population, and for those evacuated from special facilities.
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| Conducted a final meeting with Dominion Energy, emergency management personnel and the OROs to present final results of the study.
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| North Anna Power Station ES2 KLD Engineering, P.C.
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| Computation of ETE A total of 770 ETE were computed for the evacuation of the general public. Each ETE quantifies the aggregate evacuation time estimated for the population within one of the 55 Evacuation Regions to evacuate from that Region, under the circumstances defined for one of the 14 Evacuation Scenarios (55 x 14 = 770). Separate ETE are calculated for transitdependent evacuees, including children at schools and preschools for applicable scenarios.
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| Except for Region R03, which is the evacuation of the entire EPZ, only a portion of the people within the EPZ would be advised to evacuate. That is, the ATE applies only to those people occupying the specified impacted region. It is assumed that 100% of the people within the impacted region will evacuate in response to this ATE. The people occupying the remainder of the EPZ outside the impacted region may be advised to take shelter.
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| The computation of ETE assumes that 20% of the population within the EPZ but outside the impacted region, will elect to voluntarily evacuate. In addition, 20% of the population in the Shadow Region will also elect to evacuate. These voluntary evacuees could impede those who are evacuating from within the impacted region. The impedance that could be caused by voluntary evacuees is considered in the computation of ETE for the impacted region.
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| Staged evacuation is considered wherein those people within the 2Mile Region evacuate immediately, while those beyond 2 miles, but within the EPZ, shelterinplace. Once 90% of the 2Mile Region is evacuated, those people beyond 2 miles begin to evacuate. As per federal guidance, 20% of people beyond 2 miles will evacuate (noncompliance) even though they are advised to shelterinplace.
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| The computational procedure is outlined as follows:
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| A linknode representation of the highway network is coded. Each link represents a unidirectional length of highway; each node usually represents an intersection or merge point. The capacity of each link is estimated based on the field survey observations and on established traffic engineering procedures.
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| The evacuation trips are generated at locations called zonal centroids located within the EPZ and Shadow Region. The trip generation rates vary over time reflecting the mobilization process, and from one location (centroid) to another depending on population density and on whether a centroid is within, or outside, the impacted area.
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| The evacuation model computes the routing patterns for evacuating vehicles that are compliant with federal guidelines (outbound relative to the location of the plant), then simulate the traffic flow movements over space and time. This simulation process estimates the rate that traffic flow exits the impacted region.
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| The ETE statistics provide the elapsed times for 90% and 100%, respectively, of the population within the impacted region, to evacuate from within the impacted region. These statistics are presented in tabular and graphical formats. The 90th percentile ETE have been identified as the values that should be considered when making protective action decisions because the 100th percentile ETE are prolonged by those relatively few people who take longer to mobilize. This is referred to as the evacuation tail in Section 4.0 of NUREG/CR7002, Rev. 1.
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| North Anna Power Station ES3 KLD Engineering, P.C.
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| Traffic Management Plan This study references the comprehensive traffic management plan provided by Louisa, Spotsylvania, Orange, Caroline, and Hanover Counties, and identifies critical intersections.
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| Selected Results A compilation of selected information is presented on the following pages in the form of figures and tables extracted from the body of the report; these are described below.
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| Table 31 presents the estimates of permanent resident population in each PAZ based on the 2020 Census data.
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| Table 61 defines each of the 55 Evacuation Regions in terms of their respective groups of PAZs.
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| Table 62 lists the 14 Evacuation Scenarios.
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| Tables 71 and 72 are compilations of ETE for the general population. These data are the times needed to clear the indicated regions of 90% and 100% of the population occupying these regions, respectively. These computed ETE include consideration of mobilization time and of estimated voluntary evacuations from other regions within the EPZ and from the Shadow Region.
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| Tables 73 and 74 present ETE for the 2Mile Region for unstaged (concurrent) and staged evacuations for the 90th and 100th percentiles, respectively.
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| Table 82 presents ETE for the children at schools and preschools in good weather.
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| Table 85 presents ETE for the transitdependent population in good weather.
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| Table 88 presents ETE for the medical facilities.
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| Figure 61 presents displays a map of the NAPS EPZ showing the layout of the 25 PAZs that comprise, in aggregate, the EPZ.
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| Figure H11 presents an example of an Evacuation Region (Region R11) to be evacuated under the circumstances defined in Table 61. See Appendix H for maps of all regions.
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| Conclusions General population ETE were computed for 770 unique cases - a combination of 55 unique Evacuation Regions and 14 unique Evacuation Scenarios. Table 71 and Table 72 document these ETE for the 90th and 100th percentiles. These ETE range from 2:25 (hr:min) to 4:25 at the 90th percentile for all unstaged cases. The 100th percentile ETE range from 5:15 to 5:25 for good weather and rain/light snow cases, and from 7:00 to 7:10 for heavy snow cases.
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| The comparison of Table 71 and Table 72 indicates that the ETE for the 100th percentile are significantly longer than those for the 90th percentile. The 100th percentile ETE for all regions range from 5:15 to 5:25 for all nonheavy snow scenarios and between 7:00 and 7:10 for all heavy snow scenarios. This reflects the time needed to mobilize (5 hours and 15 minutes in good weather and rain/light snow, and 7 hours in heavy snow) plus 5 or 10 minutes travel time to the EPZ boundary - see Section 5.
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| North Anna Power Station ES4 KLD Engineering, P.C.
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| Inspection of Table 73 and Table 74 indicates that a staged evacuation provides no benefits to evacuees from within the 2Mile Region and unnecessarily delays the evacuation of those beyond 2 miles (compare Regions R02 and R04 through R14 with Regions R43 through R55, respectively, in Tables 71 and 72). See Section 7.6 for additional discussion. Staged evacuation is not recommended for the NAPS EPZ.
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| Comparison of Scenarios 9 and 13 in Table 71 and Table 72 indicates that the special event, the Kinetic Triathlon at Lake Anna State Park (see Section 3.8), has no impact on the ETE at the 90th or 100th percentile. The results indicate there is sufficient reserve roadway capacity to accommodate the additional special event vehicles.
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| Comparison of Scenarios 1 and 14 in Table 71 indicates that the roadway closure - one segment of US522 northbound from CR612 to CR719 - increases the 90th percentile by at most 5 minutes and has no effect on the 100th percentile ETE - not a significant impact. US522 experiences moderate traffic congestion, but there is sufficient reserve capacity on CR612 to service the additional evacuating traffic demand diverted from US522.
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| Separate ETE were computed for schools, preschools, medical facilities, transit dependent persons and access and/or functional needs persons. The average single wave ETE for all these facilities is comparable to or less than the general population ETE at the 90th percentile. See Section 8.
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| Table 81 indicates that there are sufficient bus resources available to evacuate the transit dependent population in a single wave (see Section 8.1).
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| A reduction in or expansion of base trip generation time by an hour impacts the 90th percentile ETE by 10 to 30 minutes (respectively) and the 100th percentile ETE by 1 hour for both (significant change). As discussed in Section 7.3, traffic congestion persists within the EPZ for about 2 hours and 50 minutes after the ATE. If the time to mobilize is longer than 2 hours and 50 minutes, the 100th percentile ETE is dictated by trip generation time. See Table M1 in Appendix M.
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| Shadow evacuation has a minimal impact on the general population ETE. Doubling (40%), tripling (60%), and quadrupling (80%) the shadow evacuation percentage increases the 90th percentile ETE by at most 5 minutes. A full evacuation (100%) of the Shadow Region increases the 90th percentile ETE by 10 minutes. See Table M2.
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| A population increase of 192% or more in the full EPZ results in ETE changes which meet the NRC criteria for updating ETE between decennial Censuses. See Section M.3.
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| Based on the demographic survey, the average household size of 2.90 people per household was used for this study. Decreasing the average household size (increasing the total number evacuating vehicles) to 2.67 people per household (as per 2020 Census data) has no impact on both the 90th and 100th percentile ETE. See Table M4.
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| North Anna Power Station ES5 KLD Engineering, P.C.
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| Table 31. EPZ Permanent Resident Population PAZ 2010 Population 2020 Population 2 466 463 3 1,490 1,524 4 1,107 1,322 5 1,472 1,476 6 484 575 7 484 668 8 409 464 9 203 238 10 429 487 11 981 1,017 12 1,561 1,681 13 1,364 1,412 14 803 867 15 697 843 16 1,601 1,860 17 144 214 18 2,416 2,592 19 383 456 20 1,026 1,113 21 2,232 2,386 22 1,538 1,718 23 260 264 24 946 925 25 464 573 26 2,242 2,351 EPZ TOTAL: 25,202 27,489 EPZ Population Growth (20102020): 9.07%
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| North Anna Power Station ES6 KLD Engineering, P.C.
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| Table 61. Description of Evacuation Regions Radial Regions Protection Action Zone (PAZ)
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| Region Description Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R01 2Mile Region N/A x x x x R02 5Mile Region N/A x x x x x x x x x x x x R03 Full EPZ N/A x x x x x x x x x x x x x x x x x x x x x x x x x Evacuate 2Mile Region and Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R04 NNW, N 327 11 x x x x x x R05 NNE 12 33 x x x x x R06 NE 34 56 x x x x x x R07 ENE 57 78 x x x x x R08 E 79 101 x x x x x x R09 ESE, SE 102 146 x x x x x x x R10 SSE 147 168 x x x x x x x R11 S, SSW 169 213 x x x x x x x R12 SW 214 236 x x x x x x x R13 WSW, W 237 281 x x x x x x R14 WNW 282 303 x x x x x x R15 NW 304 326 x x x x x x x Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R16 NNW, N 327 11 x x x x x x x x x R17 NNE 12 33 x x x x x x x x R18 NE 34 56 x x x x x x x x x x R19 ENE 57 78 x x x x x x x x x R20 E 79 101 x x x x x x x x x x x R21 ESE, SE 102 146 x x x x x x x x x x R22 SSE 147 168 x x x x x x x x x x R23 S 169 191 x x x x x x x x x x R24 SSW 192 213 x x x x x x x x x x x R25 SW 214 236 x x x x x x x x x x R26 WSW 237 258 x x x x x x x x x R27 W 259 281 x x x x x x x x x R28 WNW 282 303 x x x x x x x x x x x R29 NW 304 326 x x x x x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station ES7 KLD Engineering, P.C.
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| Evacuate 5Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R30 NNW, N 327 11 x x x x x x x x x x x x x x x R31 NNE 12 33 x x x x x x x x x x x x x x x x R32 NE, ENE 34 78 x x x x x x x x x x x x x x x x R33 E 79 101 x x x x x x x x x x x x x x x x x R34 ESE, SE 102 146 x x x x x x x x x x x x x x x R35 SSE 147 168 x x x x x x x x x x x x x x x R36 S 169 191 x x x x x x x x x x x x x x x R37 SSW 192 213 x x x x x x x x x x x x x x x x R38 SW 214 236 x x x x x x x x x x x x x x x R39 WSW 237 258 x x x x x x x x x x x x x x x R40 W 259 281 x x x x x x x x x x x x x x x R41 WNW 282 303 x x x x x x x x x x x x x x x x x R42 NW 304 326 x x x x x x x x x x x x x x x x Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region From: Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R43 5Mile Region N/A x x x x x x x x x x x x R44 NNW, N 327 11 x x x x x x R45 NNE 12 33 x x x x x R46 NE 34 56 x x x x x x R47 ENE 57 78 x x x x x R48 E 79 101 x x x x x x R49 ESE, SE 102 146 x x x x x x x R50 SSE 147 168 x x x x x x x R51 S, SSW 169 213 x x x x x x x R52 SW 214 236 x x x x x x x R53 WSW, W 237 281 x x x x x x R54 WNW 282 303 x x x x x x R55 NW 304 326 x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station ES8 KLD Engineering, P.C.
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| Table 62. Evacuation Scenario Definitions Time of 1
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| Scenarios Season Day of Week Day Weather Special 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None Midweek, 5 Summer Evening Good None Weekend 6 Winter Midweek Midday Good None Rain/Light 7 Winter Midweek Midday None Snow Heavy 8 Winter Midweek Midday None Snow 9 Winter Weekend Midday Good None Rain/Light 10 Winter Weekend Midday None Snow Heavy 11 Winter Weekend Midday None Snow Midweek, 12 Winter Evening Good None Weekend Special Event: Kinetic 13 Winter Weekend Midday Good Triathlon at Lake Anna State Park Roadway Impact: One 14 Summer Midweek Midday Good Segment Closure on US 522 Northbound 1
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| Winter means that school is in session at normal enrollment levels (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).
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| North Anna Power Station ES9 KLD Engineering, P.C.
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| Table 71. Time to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R02 2:55 2:55 2:30 2:30 2:30 3:10 3:10 4:15 2:40 2:40 3:50 2:40 2:40 2:55 R03 3:10 3:10 2:40 2:40 2:40 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:10 Evacuate 2Mile Region and Downwind to 5 Miles R04 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R05 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R06 2:55 2:55 2:35 2:35 2:35 3:05 3:05 4:10 2:40 2:40 3:55 2:40 2:40 2:55 R07 2:50 2:50 2:30 2:30 2:30 3:00 3:00 4:05 2:40 2:40 3:50 2:40 2:40 2:50 R08 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R09 2:45 2:45 2:25 2:25 2:30 3:00 3:05 4:05 2:35 2:35 3:50 2:40 2:35 2:45 R10 2:50 2:50 2:25 2:25 2:30 3:05 3:05 4:10 2:35 2:35 3:50 2:40 2:35 2:50 R11 2:50 2:55 2:25 2:25 2:30 3:05 3:05 4:10 2:35 2:35 3:50 2:40 2:35 2:55 R12 3:00 3:00 2:30 2:30 2:35 3:10 3:10 4:15 2:40 2:40 3:50 2:40 2:40 3:00 R13 3:00 3:00 2:30 2:35 2:35 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 3:00 R14 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R15 2:55 2:55 2:30 2:30 2:30 3:05 3:10 4:15 2:40 2:40 3:50 2:40 2:40 2:55 Evacuate 2Mile Region and Downwind to the EPZ Boundary R16 3:10 3:10 2:45 2:45 2:45 3:15 3:15 4:25 2:45 2:50 4:00 2:50 2:45 3:10 R17 3:10 3:10 2:40 2:45 2:45 3:15 3:15 4:20 2:45 2:45 4:00 2:45 2:45 3:10 R18 3:05 3:05 2:35 2:35 2:40 3:10 3:10 4:20 2:45 2:45 3:55 2:45 2:45 3:05 R19 3:05 3:05 2:35 2:35 2:40 3:10 3:10 4:15 2:40 2:45 3:55 2:45 2:40 3:05 R20 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R21 3:00 3:00 2:30 2:30 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R22 3:00 3:00 2:30 2:30 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R23 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:45 2:40 3:05 North Anna Power Station ES10 KLD Engineering, P.C.
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R24 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R25 3:05 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R26 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:10 R27 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:45 2:45 3:55 2:45 2:45 3:10 R28 3:15 3:15 2:40 2:45 2:45 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:15 R29 3:10 3:15 2:40 2:45 2:45 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:10 Evacuate 5Mile Region and Downwind to the EPZ Boundary R30 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:25 2:45 2:45 3:55 2:45 2:45 3:05 R31 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:45 2:45 3:55 2:45 2:45 3:05 R32 3:00 3:05 2:35 2:35 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R33 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R34 3:00 3:00 2:30 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R35 3:00 3:00 2:30 2:35 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R36 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R37 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R38 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R39 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R40 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R41 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:25 2:45 2:45 4:00 2:45 2:45 3:10 R42 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:25 2:40 2:45 3:55 2:45 2:40 3:05 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 3:40 3:40 3:35 3:35 3:40 3:40 3:45 5:00 3:40 3:40 4:55 3:40 3:40 3:40 R44 3:30 3:30 3:30 3:30 3:30 3:35 3:35 4:50 3:35 3:35 4:50 3:35 3:35 3:30 R45 3:25 3:30 3:25 3:25 3:25 3:35 3:35 4:45 3:30 3:30 4:45 3:30 3:30 3:30 R46 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R47 3:30 3:30 3:30 3:30 3:30 3:35 3:35 4:50 3:35 3:35 4:50 3:35 3:35 3:30 R48 3:35 3:35 3:30 3:30 3:30 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R49 3:35 3:35 3:30 3:30 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:40 3:35 3:35 R50 3:35 3:35 3:30 3:30 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 North Anna Power Station ES11 KLD Engineering, P.C.
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R51 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 R52 3:40 3:40 3:35 3:35 3:35 3:40 3:40 4:55 3:40 3:40 4:55 3:40 3:40 3:40 R53 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R54 3:35 3:35 3:30 3:30 3:30 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R55 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 North Anna Power Station ES12 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 72. Time to Clear the Indicated Area of 100 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R02 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R03 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Evacuate 2Mile Region and Downwind to 5 Miles R04 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R05 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R06 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R07 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R08 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R09 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R10 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R11 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R12 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R13 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R14 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R15 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 Evacuate 2Mile Region and Downwind to the EPZ Boundary R16 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R17 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R18 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R19 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R20 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R21 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R22 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R23 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R24 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 North Anna Power Station ES13 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R25 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R26 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R27 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R28 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R29 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Evacuate 5Mile Region and Downwind to the EPZ Boundary R30 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R31 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R32 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R33 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R34 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R35 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R36 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R37 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R38 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R39 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R40 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R41 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R42 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R44 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R45 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R46 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R47 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R48 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R49 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R50 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R51 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 North Anna Power Station ES14 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R52 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R53 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R54 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R55 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 North Anna Power Station ES15 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 73. Time to Clear 90 Percent of the 2Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2Mile Region and 5Mile Region R01 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R02 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R05 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R06 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R07 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R08 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R09 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R10 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R11 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R12 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R13 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R14 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R15 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R44 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R45 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R46 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R47 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R48 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R49 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R50 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R51 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R52 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 North Anna Power Station ES16 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R53 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R54 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R55 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 North Anna Power Station ES17 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 74. Time to Clear 100 Percent of the 2Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2Mile Region and 5Mile Region R01 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R02 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R05 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R06 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R07 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R08 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R09 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R10 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R11 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R12 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R13 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R14 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R15 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R44 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R45 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R46 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R47 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R48 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R49 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R50 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R51 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R52 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 North Anna Power Station ES18 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R53 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R54 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R55 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 North Anna Power Station ES19 KLD Engineering, P.C.
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| Table 82. School and Preschool Evacuation Time Estimates - Good Weather Travel Time Travel Dist. from Dist. To Time to EPZ EPZ Driver Loading EPZ Average EPZ Bdry to Bdry to ETA to Mobilization Time Bdry Speed Bdry ETE EAC EAC EAC School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)
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| LOUISA COUNTY SCHOOLS Mineral Christian Preschool 90 15 4.8 42.4 7 1:55 8.3 11 2:10 Louisa County High School 90 15 3.7 45.0 5 1:50 8.3 11 2:05 Louisa County Middle School 90 15 3.4 45.0 5 1:50 8.3 11 2:05 Thomas Jefferson Elementary School 90 15 1.5 45.0 2 1:50 8.6 11 2:05 Jouett Elementary School 90 15 0.3 39.9 0 1:45 21.0 28 2:15 SPOTSYLVANIA COUNTY SCHOOLS Livingston Elementary 90 15 9.1 45.0 12 2:00 9.1 12 2:15 Post Oak Middle School 90 15 3.4 45.0 5 1:50 9.1 12 2:05 Spotsylvania High School 90 15 3.2 44.9 4 1:50 8.0 11 2:05 Spotsylvania High School Governor's School 90 15 3.2 44.9 4 1:50 8.0 11 2:05 Berkeley Elementary 90 15 2.1 41.6 3 1:50 8.0 11 2:05 Maximum for EPZ: 2:00 Maximum: 2:15 Average for EPZ: 1:55 Average: 2:10 North Anna Power Station ES20 KLD Engineering, P.C.
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| Table 85. TransitDependent Evacuation Time Estimates - Good Weather OneWave TwoWave Route Route Pickup Distance Travel Driver Route Pickup Route Number Mobilization Length Speed Travel Time Time ETE to EAC Time to Unload Rest Travel Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) EAC (min) (min) (min) Time (min) (min) (hr:min) 1 1 150 12.6 45.0 17 30 3:20 12.9 17 5 10 51 30 5:15 2 1 150 17.3 43.5 24 30 3:25 12.9 17 5 10 63 30 5:30 3 1 150 20.2 45.0 27 30 3:30 8.0 11 5 10 65 30 5:35 4 1 150 15.3 45.0 20 30 3:20 12.9 17 5 10 58 30 5:20 5 1 150 15.9 45.0 21 30 3:25 8.0 11 5 10 54 30 5:15 6 1 150 21.9 45.0 29 30 3:30 12.9 17 5 10 75 30 5:50 7 1 150 19.8 45.0 26 30 3:30 8.0 11 5 10 64 30 5:30 8 1 150 32.2 45.0 43 30 3:45 13.6 18 5 10 104 30 6:35 9 1 150 22.8 45.0 30 30 3:30 8.0 11 5 10 72 30 5:40 10 1 150 26.3 41.0 38 30 3:40 13.6 18 5 10 90 30 6:15 11 1 150 17.3 45.0 23 30 3:25 13.7 18 5 10 64 30 5:35 12 1 150 27.6 42.6 39 30 3:40 12.9 17 5 10 92 30 6:15 13 1 150 17.0 41.7 24 30 3:25 8.0 11 5 10 57 30 5:20 14 1 150 36.6 45.0 49 30 3:50 12.9 17 5 10 115 30 6:50 15 1 150 17.5 45.0 23 30 3:25 8.0 11 5 10 58 30 5:20 16 1 150 23.2 44.4 31 30 3:35 12.9 17 5 10 79 30 6:00 17 1 150 19.1 43.3 26 30 3:30 8.0 11 5 10 63 30 5:30 18 1 150 26.3 45.0 35 30 3:35 9.5 13 5 10 83 30 6:00 19 1 150 18.5 45.0 25 30 3:25 8.3 11 5 10 60 30 5:25 20 1 150 29.2 45.0 39 30 3:40 8.3 11 5 10 89 30 6:05 21 1 150 10.7 45.0 14 30 3:15 13.5 18 5 10 47 30 5:05 22 1 150 5.1 45.0 7 30 3:10 8.3 11 5 10 25 30 4:35 23 1 150 8.8 45.0 12 30 3:15 7.8 10 5 10 34 30 4:45 24 1 150 8.0 33.5 14 30 3:15 7.8 10 5 10 35 30 4:45 25 1 150 17.0 43.1 24 30 3:25 21.8 29 5 10 75 30 5:55 Maximum ETE: 3:50 Maximum ETE: 6:50 Average ETE: 3:30 Average ETE: 5:40 North Anna Power Station ES21 KLD Engineering, P.C.
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| Table 88. Medical Facility Evacuation Time Estimates Travel Loading Time to Rate Total EPZ Mobilization (min per Loading Dist. To EPZ Boundary ETE Medical Facility Patient Weather Conditions (min) person) People Time (min) Bdry (mi) (min) (hr:min)
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| Good 90 15 8 30 12.1 16 2:20 Lake Anna Elder Care Bedridden Rain 100 15 8 30 12.1 18 2:30 Inc Snow 110 15 8 30 12.1 19 2:40 North Anna Power Station ES22 KLD Engineering, P.C.
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| Figure 61. PAZs Comprising the NAPS EPZ North Anna Power Station ES23 KLD Engineering, P.C.
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| Figure H11. Region R11 North Anna Power Station ES24 KLD Engineering, P.C.
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| 1 INTRODUCTION This report describes the analyses undertaken and the results obtained by a study to develop Evacuation Time Estimates (ETE) for the North Anna Power Station (NAPS), located in Louisa County, Virginia. This ETE study provides Dominion Energy, state and local governments with sitespecific information needed for Protective Action decisionmaking.
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| In the performance of this effort, guidance is provided by documents published by Federal governmental agencies. Most important of these are:
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| * Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.
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| * Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR7002, Rev. 1, February 2021.
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| * Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG 0654/Radiological Emergency Preparedness Program Manual, FEMA P1028, December 2019.
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| The work effort reported herein was supported and guided by Dominion Energy and local stakeholders who contributed suggestions, critiques, and the local knowledge base required.
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| Table 11 presents a summary of stakeholders and interactions.
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| 1.1 Overview of the ETE Process The following outline presents a brief description of the work effort in chronological sequence:
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| : 1. Information Gathering:
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| : a. Defined the scope of work in discussions with representatives from Dominion Energy.
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| : b. Attended a project kickoff meeting with personnel from Dominion Energy, Virginia Department of Emergency Management (VDEM), Federal Emergency Management Agency (FEMA), Louisa, Spotsylvania, Hanover, Orange, and Caroline Counties to discuss methodology, project assumptions and to identify issues to be addressed and resources available.
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| : c. Conducted a detailed field survey of the highway system and of area traffic conditions within the Emergency Planning Zone (EPZ) and Shadow Region.
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| : d. Reviewed existing state and county emergency plans.
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| : e. Conducted an online demographic survey of EPZ residents (see Appendix F).
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| : f. Obtained demographic data from the 2020 Census (see Section 3.1).
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| : g. Conducted a data collection effort to identify and describe special facilities (i.e.,
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| schools, preschools, medical facilities), major employers, access and/or North Anna Power Station 11 KLD Engineering, P.C.
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| functional needs population, transportation resources available, the special event, and other important information.
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| : 2. Estimated distributions of Trip Generation times representing the time required by various population groups (permanent residents, employees, and transients) to prepare (mobilize) for the evacuation trip. These estimates are primarily based upon the random sample online demographic survey.
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| : 3. Defined Evacuation Scenarios. These scenarios reflect the variation in demand, in trip generation distribution and in highway capacities, associated with different seasons, day of week, time of day and weather conditions.
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| : 4. Reviewed the existing traffic management plan to be implemented by local and state police in the event of an incident at the plant. Traffic and access control are applied at specified Traffic and Access Control Points (TCP/ACP) located within the study area. See Section 9 and Appendix G.
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| : 5. Used existing Protective Action Zones (PAZs) to define Evacuation Regions. The EPZ is partitioned into 25 PAZs along jurisdictional and geographic boundaries. Regions are groups of contiguous PAZs for which ETE are calculated. The configurations of these Regions reflect wind direction and the radial extent of the impacted area. Each Region, other than those that approximate circular areas, approximates a keyhole section within the EPZ as recommended by NUREG/CR7002, Rev. 1.
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| : 6. Estimated demand for transit services for persons at schools, preschools, medical facilities, transitdependent persons at home, and those with access and/or functional needs.
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| : 7. Prepared the input streams for the DYNEV II System which computes ETE (see Appendices B and C).
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| : a. Estimated the evacuation traffic demand, based on the available information derived from Census data, and from data provided by county and state agencies, Dominion Energy and from the demographic survey.
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| : b. Applied the procedures specified in the 2016 Highway Capacity Manual (HCM 20161) to the data acquired during the field survey, to estimate the capacity of all highway segments comprising the evacuation routes.
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| : c. Updated the linknode representation of the evacuation network, which is used as the basis for the computer analysis that calculates the ETE.
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| : d. Calculated the evacuating traffic demand for each Region and for each Scenario.
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| : e. Specified selected candidate destinations for each origin (location of each source where evacuation trips are generated over the mobilization time) to support evacuation travel consistent with outbound movement relative to the 1
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| Highway Capacity Manual (HCM 2016), Transportation Research Board, National Research Council, 2010.
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| location of the plant.
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| : 8. Executed the DYNEV II model to determine optimal evacuation routing and compute ETE for all residents, transients and employees (general population) with access to private vehicles. Generated a complete set of ETE for all specified Regions and Scenarios.
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| : 9. Documented ETE in formats in accordance with NUREG/CR7002, Rev. 1.
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| : 10. Calculated the ETE for all transit activities including those for special facilities (schools, preschools, and medical facilities), for the transitdependent population and for the access and/or functional needs population.
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| 1.2 The North Anna Power Station Location The North Anna Power Station is located approximately 40 miles northwest of Richmond, Virginia. The EPZ consists of parts of Caroline, Hanover, Louisa, Orange, and Spotsylvania Counties in Virginia. Figure 11 displays the area surrounding the NAPS. This map identifies the communities in the area and the major roads.
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| 1.3 Preliminary Activities These activities are described below.
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| Field Surveys of the Highway Network In February 2021, KLD personnel drove the entire highway system within the EPZ and the Shadow Region which consists of the area between the EPZ boundary and approximately 15 miles radially from the plant. The characteristics of each section of highway were recorded.
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| These characteristics are shown in Table 12.
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| Video and audio recording equipment were used to capture a permanent record of the highway infrastructure. No attempt was made to meticulously measure such attributes as lane width and shoulder width; estimates of these measures based on visual observation and recorded images were considered appropriate for the purpose of estimating the capacity of highway sections. For example, Exhibit 157 in the HCM 2016 indicates that a reduction in lane width from 12 feet (the base value) to 10 feet can reduce free flow speed (FFS) by 1.1 mph - not a material difference - for twolane highways. Exhibit 1546 in the HCM 2016 shows little sensitivity for the estimates of Service Volumes at Level of Service (LOS) E (near capacity), with respect to FFS, for twolane highways.
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| The data from the audio and video recordings were used to create detailed geographic information systems (GIS) shapefiles and databases of the roadway characteristics and of the traffic control devices observed during the road survey; this information was referenced while preparing the input stream for the DYNEV II System. Roadway types were assigned based on the following criteria:
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| Freeway: limited access highway, 2 or more lanes in each direction, high free flow speeds North Anna Power Station 13 KLD Engineering, P.C.
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| Freeway Ramp: ramp on to or off of a limited access highway Major Arterial: 3 or more lanes in each direction Minor Arterial: 2 lanes in each direction Collector: single lane in each direction Local Roadway: single lane in each direction, local road with low free flow speeds As documented on page 156 of the HCM 2016, the capacity of a twolane highway is 1,700 passenger cars per hour in one direction. For freeway sections, a value of 2,250 vehicles per hour per lane is assigned, as per Exhibit 1237 of the HCM 2016. The road survey has identified several segments which are characterized by adverse geometrics on twolane highways which are reflected in reduced values for both capacity and speed. These estimates are consistent with the service volumes for LOS E presented in HCM 2016 Exhibit 1546. Link capacity is an input to DYNEV II which computes the ETE. Further discussion of roadway capacity is provided in Section 4 of this report.
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| Traffic signals are either pretimed (signal timings are fixed over time and do not change with the traffic volume on competing approaches) or are actuated (signal timings vary over time based on the changing traffic volumes on competing approaches). Actuated signals require detectors to provide the traffic data used by the signal controller to adjust the signal timings.
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| These detectors are typically magnetic loops in the roadway, or video cameras mounted on the signal masts and pointed toward the intersection approaches. If detectors were observed on the approaches to a signalized intersection during the road survey, detailed signal timings were not collected as the timings vary with traffic volume. TCPs at locations which have control devices are represented as actuated signals in the DYNEV II system.
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| If no detectors were observed, the signal control at the intersection was considered pretimed, and detailed signal timings were gathered for several signal cycles. These signal timings were input to the DYNEV II system used to compute ETE, as per NUREG/CR7002, Rev. 1 guidance.
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| Figure 12 presents the linknode analysis network that was constructed to model the evacuation roadway network in the EPZ and Shadow Region. The directional arrows on the links and the node numbers have been removed from Figure 12 to clarify the figure. The detailed figures provided in Appendix K depict the analysis network with directional arrows shown and node numbers provided. The observations made during the field survey and aerial imagery were used to calibrate the analysis network.
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| Demographic Survey An online demographic survey was performed in April 2021 to gather information needed for the evacuation study. Appendix F presents the survey instrument, the procedures used and tabulations of data compiled from the survey returns.
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| These data were utilized to develop estimates of vehicle occupancy, to estimate the number of evacuating vehicles during an evacuation, and to estimate elements of the mobilization process. This database was also referenced to estimate the number of transitdependent residents.
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| Computing the Evacuation Time Estimates The overall study procedure is outlined in Appendix D. Demographic data were obtained from several sources, as detailed later in this report. These data were analyzed and converted into vehicle demand data. The vehicle demand was loaded onto appropriate source links of the analysis network using GIS mapping software. The DYNEV II model was then used to compute ETE for all Regions and Scenarios.
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| Analytical Tools The DYNEV II System that was employed for this study is comprised of several integrated computer models. One of these is the DYNEV (DYnamic Network EVacuation) macroscopic simulation model, a new version of the IDYNEV model that was developed by KLD under contract with the Federal Emergency Management Agency (FEMA).
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| DYNEV II consists of four submodels:
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| A macroscopic traffic simulation model (for details, see Appendix C).
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| A Trip Distribution (TD), model that assigns a set of candidate destination (D) nodes for each origin (O) located within the analysis network, where evacuation trips are generated over time. This establishes a set of OD tables.
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| A Dynamic Traffic Assignment (DTA), model which assigns trips to paths of travel (routes) which satisfy the OD tables, over time. The TD and DTA models are integrated to form the DTRAD (Dynamic Traffic Assignment and Distribution) model, as described in Appendix B.
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| A Myopic Traffic Diversion model which diverts traffic to avoid intense, local congestion, if possible.
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| Another software product developed by KLD, named UNITES (UNIfied Transportation Engineering System) was used to expedite data entry and to automate the production of output tables.
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| The dynamics of traffic flow over the network are graphically animated using the software product, EVAN (EVacuation ANimator), developed by KLD. EVAN is GIS based, and displays statistics output by the DYNEV II System, such as LOS, vehicles discharged, average speed, and percent of vehicles evacuated. The use of a GIS framework enables the user to zoom in on areas of congestion and query road name, town name and other geographical information.
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| The procedure for applying the DYNEV II System within the framework of developing ETE is outlined in Appendix D. Appendix A is a glossary of terms.
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| For the reader interested in an evaluation of the original model, IDYNEV, the following references are suggested:
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| NUREG/CR4873 Benchmark Study of the IDYNEV Evacuation Time Estimate Computer Code NUREG/CR4874 The Sensitivity of Evacuation Time Estimates to Changes in Input Parameters for the IDYNEV Computer Code North Anna Power Station 15 KLD Engineering, P.C.
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| The evacuation analysis procedures are based upon the need to:
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| Route traffic along paths of travel that will expedite their travel from their respective points of origin to points outside the EPZ.
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| Restrict movement toward the plant to the extent practicable and disperse traffic demand so as to avoid focusing demand on a limited number of highways.
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| Move traffic in directions that are generally outbound, relative to the location of the plant.
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| DYNEV II provides a detailed description of traffic operations on the evacuation network. This description enables the analyst to identify bottlenecks and to develop countermeasures that are designed to represent the behavioral responses of evacuees. The effects of these countermeasures may then be tested with the model.
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| 1.4 Comparison with Prior ETE Study Table 13 presents a comparison of this ETE study with the 2012 study (KLD TR - 503, dated November 2012). The 90th percentile ETE for the full EPZ for Scenario 6 (winter, midweek, midday with good weather), Scenario 7 (winter, midweek, midday with rain/light snow), and Scenario 8 (winter, midweek, midday with heavy snow) increased by 40 minutes for good weather and rain, and increased by 55 minutes for heavy snow, when compared with the previous ETE study. For Scenario 3 (summer, weekend, midday with good weather), Scenario 4 (summer, weekend, midday with rain), the 90th percentile ETE increased by 40 minutes when compared with the previous ETE study.
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| The 100th percentile ETE for the full EPZ for Scenario 6 (winter, midweek, midday with good weather), Scenario 7 (winter, midweek, midday with rain/light snow), and Scenario 8 (winter, midweek, midday with heavy snow) decreased by 15 minutes for good weather and rain, and increased by 30 minutes for heavy snow, when compared with the previous ETE study. For Scenario 3 (summer, weekend, midday with good weather), Scenario 4 (summer, weekend, midday with rain weather), the 100th percentile ETE decreased by 15 minutes when compared with the previous ETE study.
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| The major factors contributing to the differences between the ETE values obtained in this study and those of the previous study can be summarized as follows:
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| The permanent resident population within the EPZ has increased by 9.1%. This population increase results in additional permanent resident evacuating vehicles, which can increase the ETE.
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| The permanent resident population in the Shadow Region increased by 13.8%. This population increase results in significantly more vehicles evacuating within the Shadow Region, which reduces the available roadway capacity for EPZ evacuees, which can increase the ETE.
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| The number of employees commuting into the EPZ decreased significantly (by 25%), due to the updated federal guidance for major employers from 50 or more employees per shift to 200 or more employees per shift. This decrease in quickly mobilizing vehicles can North Anna Power Station 16 KLD Engineering, P.C.
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| increase the 90th percentile ETE as it will take longer to reach 90% of the evacuating traffic.
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| Roadway capacity reductions for heavy snow cases have increased from 20% to 25%
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| based on the new NRC guidance. As a result, roadways process less vehicles than previously assumed during heavy snow cases and could result in longer ETE.
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| The time to mobilize 90% of residents with commuters in the 2012 study was 190 minutes versus 225 minutes in this study. The time to mobilize 90% of residents with no commuters in the 2012 study was 105 minutes versus 155 minutes in this study. Given the limited traffic congestion in this EPZ (see Section 7.3), the 90th percentile ETE are dictated by mobilization time. The longer time to mobilize 90% of residents in this study will increase ETE.
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| The time to mobilize 100% of the EPZ population in good weather and rain in the 2012 study was 330 minutes versus 315 minutes in this study. The time to mobilize 100% of the EPZ population in heavy snow in the 2012 study was 390 minutes versus 420 minutes in this study. Given the limited traffic congestion in this EPZ (see Section 7.3),
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| the 100th percentile ETE are dictated by mobilization time. The 15minute decrease in mobilization time for good weather and rain in this study is directly responsible for the 15minute decrease in 100th percentile ETE for good weather and rain. The 30minute increase in mobilization time for heavy snow is directly responsible for the 30minute increase in 100th percentile ETE for heavy snow.
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| The differences in ETE in this study versus the 2012 ETE study are ultimately explained by the changes in mobilization time based on the responses to the demographic survey.
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| Table 11. Stakeholder Interaction Stakeholder Nature of Stakeholder Interaction Attended kickoff meeting to define project methodology and data requirements. Provided recent NAPS employee data. Coordinated information exchange with offsite response organizations. Reviewed and approved all project Dominion Energy assumptions and draft report. Engaged in the ETE development and was informed of the study results.
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| Attended final meeting with Dominion Energy personnel where the ETE study results were presented.
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| Federal Emergency Management Agency Attended kickoff meeting to discuss the project (FEMA) methodology, key project assumptions and to define Virginia Department of Emergency data needs. Provided existing emergency plans, Management (VDEM) including traffic and access control points and other Louisa County information critical to the ETE study. Reviewed and approved project assumptions. Engaged in the ETE Spotsylvania County development and informed of the study results.
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| Caroline County Provided data for special facilities in the EPZ.
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| Orange County Attended final meeting with ORO personnel where the ETE study results were presented.
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| Hanover County Table 12. Highway Characteristics Number of lanes Posted speed Lane width Actual free speed Shoulder type & width Abutting land use Interchange geometries Control devices Lane channelization & queuing Intersection configuration (including capacity (including turn bays/lanes) roundabouts where applicable)
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| Geometrics: curves, grades (>4%) Traffic signal type Unusual characteristics: Narrow bridges, sharp curves, poor pavement, flood warning signs, inadequate delineations, toll booths, etc.
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| Table 13. ETE Study Comparisons Topic 2012 ETE Study Current ETE Study ArcGIS Software using 2010 US Census ArcGIS Software using 2020 US Census blocks; area ratio method used. blocks; area ratio method used.
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| Resident Population Population = 25,202 Population = 27,489 Basis Vehicles = 13,915 Vehicles = 15,550 2.57 persons/household, 1.42 evacuating 2.90 persons/household, 1.64 evacuating Resident Population vehicles/household yielding: 1.81 vehicles/household yielding: 1.77 Vehicle Occupancy persons/vehicle. persons/vehicle Employee estimates based on information provided by the counties and Employee estimates based on information Dominion Energy, and phone calls made provided by Dominion Energy. 1.10 to major employers in the EPZ. 1.04 employees per vehicle based on Employees employees per vehicle based on demographic survey results.
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| telephone survey results.
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| Employees = 591 Employees = 788 Vehicles = 537 Vehicles = 757 Estimates based upon U.S. Census data and Estimates based upon U.S. Census data the results of the demographic survey.
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| and the results of the telephone survey.
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| TransitDependent A total of 193 people who do not have A total of 360 people who do not have Population access to a vehicle, requiring 25 buses to access to a vehicle, requiring 25 buses to evacuate.
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| evacuate.
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| 191 homebound special needs persons 310 access and/or functional needs persons Access and/or needed special transportation to require special transportation to evacuate.
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| Functional Needs evacuate. 25 buses and 8 wheelchair 46 buses, 1 wheelchair van, and 16 Population vans are required to evacuate this ambulances are required to evacuate this population. population.
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| Topic 2012 ETE Study Current ETE Study Transient estimates based upon data provided by Louisa County and by Transient estimates based upon phone Spotsylvania County. When updated data calls made to facilities, supplemented by was not provided, the number of transient observations of the facilities during the vehicles was estimated based on the parking road survey and from aerial lot capacity or accommodation capacity Transient Population photography. Seasonal population obtained from aerial imagery and facility estimated using Census data on vacant websites. Seasonal population estimated households. using Census data on vacant households.
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| Transients = 6,997 (including 1,879 seasonal residents) Transients = 6,148 (including 1,956 seasonal Vehicles = 2,801 residents)
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| Vehicles = 3,512 Population based upon phone call made Population based on data provided by to the one facility. Spotsylvania County.
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| Medical Facility Population Current Census = 8 Current census = 23 Ambulances Required = 4 Buses Required = 1 Wheelchair Vans Required = 1 School population based on data provided by the counties within the EPZ, Student enrollment data was provided by supplemented with 20112012 county emergency management agencies School Population enrollment data from a Virginia State website. School enrollment = 6,645 School enrollment = 6,427 Buses required: 126 Buses required = 113 Voluntary evacuation 20% of the population within the EPZ, 20% of the population within the EPZ, but from within EPZ in but not within the Evacuation Region not within the Evacuation Region (see Figure areas outside region to (see Figure 21) 21) be evacuated 20% of people outside of the EPZ within 20% of people outside of the EPZ within the the Shadow Region (See Figure 72). Shadow Region (see Figure 72)
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| Shadow Evacuation/Population 20% Population = 6,389 20% Population = 7,273 20% Vehicles = 3,533 20% Vehicles = 4,098 External (Through) Average Annual Daily Traffic (AADT) data Average Annual Daily Traffic (AADT) data Traffic Vehicles = 13,550 Vehicles = 16,708 Network Size 856 links; 665 nodes. 1,526 links; 1,252 nodes Field surveys conducted in February Field surveys conducted in February 2021.
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| Roadway Geometric 2012. Roads and intersections were Roads and intersections were video Data video archived. archived. Road capacities based on HCM Road capacities based on 2010 HCM. 2016.
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| Direct evacuation to designated Direct evacuation to designated Evacuation School Evacuation Evacuation Assembly Center. Assembly Center.
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| Topic 2012 ETE Study Current ETE Study Assumed 50% of transit dependent 77% of transitdependent persons will Ridesharing persons will evacuate with a neighbor or evacuate with a neighbor or friend based on friend. the results of the demographic survey.
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| Based on residential telephone survey of Based on residential demographic survey of specific pretrip mobilization activities: specific pretrip mobilization activities:
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| Residents with commuters returning Residents with commuters returning leave leave between 15 and 330 minutes.
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| between 30 and 315 minutes.
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| Trip Generation for Residents without commuters returning Residents without commuters returning Evacuation leave between 0 and 270 minutes. leave between 15 and 225 minutes.
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| Employees and transients leave between Employees and transients leave between 0 0 and 150 minutes. and 120 minutes.
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| All times measured from the Advisory to All times measured from the Advisory to Evacuate. Evacuate.
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| Good, Rain/Light Snow, or Heavy Snow. The Normal, Rain, or Snow. The capacity and capacity and free flow speed of all links in free flow speed of all links in the network the network are reduced by 10% in the event Weather are reduced by 10% in the event of rain of rain and light snow. During heavy snow, and 20% for snow. speed and capacity are reduced by 15% and 25%, respectively.
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| Modeling DYNEV II System - Version 4.0.8.0 DYNEV II System - Version 4.0.21.0 The Kinetic Triathlon The Kinetic Triathlon Special Events Special Event Population = 1,100 Special Event Population = 1,100 additional additional transients, 249 vehicles. transients, 249 vehicles.
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| 41 Regions (central sector wind direction 55 Regions (central sector wind direction and each adjacent sector technique and each adjacent sector technique used)
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| Evacuation Cases used) and 14 Scenarios producing 574 and 14 Scenarios producing 770 unique unique cases. cases.
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| ETE reported for 90th and 100th percentile ETE reported for 90th and 100th percentile Evacuation Time population. Results presented by Region population. Results presented by Region and Estimates Reporting and Scenario. Scenario.
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| Winter Weekday Midday, Winter Weekday Midday, Good Weather = 2:40 Good Weather = 3:20 Evacuation Time Rain/Light Snow: 2:40 Rain/Light Snow: 3:20 Estimates for the Heavy Snow: 3:30 Heavy Snow: 4:25 Entire EPZ (Region R03), 90th Percentile Summer Weekend, Midday, Summer Weekend, Midday, Good Weather = 2:00 Good Weather = 2:40 Rain: 2:00 Rain: 2:40 North Anna Power Station 111 KLD Engineering, P.C.
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| Topic 2012 ETE Study Current ETE Study Winter Weekday Midday, Winter Weekday Midday, Good Weather = 5:40 Good Weather = 5:25 Evacuation Time Rain/Light Snow: 5:40 Rain/Light Snow: 5:25 Estimates for the Heavy Snow: 6:40 Heavy Snow: 7:10 Entire EPZ (Region R03), 100th Percentile Summer Weekend, Midday, Summer Weekend, Midday, Good Weather = 5:40 Good Weather = 5:25 Rain: 5:40 Rain: 5:25 North Anna Power Station 112 KLD Engineering, P.C.
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| Figure 11. NAPS Location North Anna Power Station 113 KLD Engineering, P.C.
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| Figure 12. NAPS LinkNode Analysis Network North Anna Power Station 114 KLD Engineering, P.C.
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| 2 STUDY ESTIMATES AND ASSUMPTIONS This section presents the estimates and assumptions utilized in the development of the Evacuation Time Estimates (ETE).
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| 2.1 Data Estimates Assumptions
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| : 1. Permanent resident population estimates are based upon 2020 U.S. Census population from the Census Bureau website1. A methodology, referred to as the area ratio method, is employed to estimate the population within portions of census blocks that are divided by Protection Action Zone (PAZ) boundaries. It is assumed that the population is evenly distributed across a census block in order to employ the area ratio method (See Section 3.1).
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| : 2. Federal guidance (NUREG/CR7002, Rev. 1) defines a major employer as an employer with 200 or more employees working a single shift. The only major employer in the Emergency Planning Zone (EPZ) is NAPS. Estimates of total plant and employees and employees who reside outside the EPZ and commute to work at the plant are based upon data provided by Dominion Energy (see Section 3.4).
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| : 3. Population estimates at transient and special facilities are based upon data received from the county emergency management agencies and the previous ETE study, supplemented by internet searches where data is missing.
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| : 4. The relationship between the permanent resident population and evacuating vehicles is developed from the demographic survey. Average values of 2.90 persons per household and 1.64 evacuating vehicles per household are used. See Appendix F.
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| : 5. Employee vehicle occupancies for major employers are based on the results of the demographic survey. 1.10 employees per vehicle are used in the study. In addition, it is assumed there are two people per carpool, on average.
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| : 6. The maximum bus speed assumed within the EPZ is 45 mph based on Virginia state laws for buses and average posted speed limits on major roadways within the EPZ.
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| : 7. Roadway capacity estimates are based on field surveys performed in 2021 (verified by aerial imagery), and the application of the Highway Capacity Manual 2016.
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| 2.2 Methodological Assumptions
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| : 1. The Planning Basis Assumption for the calculation of ETE is a rapidly escalating accident that requires evacuation, and includes the following2 (as per NRC guidance):
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| : a. The Advisory to Evacuate (ATE) is announced coincident with the siren notification.
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| 1 www.census.gov 2
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| We emphasize that the adoption of this planning basis is not a representation that these events will occur within the indicated time frame. Rather, these assumptions are necessary in order to:
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| : 1. Establish a temporal framework for estimating the Trip Generation distribution in the format recommended in Section 2.13 of NUREG/CR-6863.
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| : 2. Identify temporal points of reference that uniquely define "Clear Time" and ETE.
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| It is likely that a longer time will elapse between the various stages of an emergency. See Section 5.1 for more detail.
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| : b. Mobilization of the general population will commence within 15 minutes after siren notification.
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| : c. ETE are measured relative to the ATE.
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| : 2. The centerpoint of the plant will be located at the geometric center of the containment building for the two reactors at 38° 3' 38.16" N, 77° 47' 21.48" W.
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| : 3. The DYNEV II3 system is used to compute ETE in this study.
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| : 4. Evacuees will drive safely, travel radially away from the plant to the extent practicable given the highway network, and obey all traffic control devices and traffic guides. All major evacuation routes are used in the analysis.
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| : 5. The existing EPZ and PAZ boundaries will be used. See Figure 31.
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| : 6. The Shadow Region extends to 15 miles radially from the plant, or approximately 5 miles radially beyond the EPZ boundary, as per NRC guidance. See Figure 72.
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| : 7. One hundred (100%) of people within the impacted keyhole will evacuate. Twenty percent (20%) of the population within the Shadow Region and within PAZs in the EPZ that are not advised to evacuate will voluntarily evacuate, as shown in Figure 21, as per NRC guidance. Sensitivity studies explore the effect on ETE of increasing the percentage of voluntary evacuees in the Shadow Region (see Appendix M).
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| : 8. Shadow population characteristics (household size, evacuating vehicles per household, and mobilization time) are assumed to be the same as that of the permanent resident population within the EPZ.
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| : 9. The ETE are presented at the 90th and 100th percentiles in graphical and tabular format, as per NRC guidance. The percentile ETE is defined as the elapsed time from the ATE issued to a specific Region of the EPZ, to the time that Region is clear of the indicated percentile of evacuees.
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| : 10. The ETE also includes consideration of through (ExternalExternal traffic that originates its trip outside of the study area and has its destination outside of the study area) trips during the time that such traffic is permitted to enter the evacuated Region.
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| See Section 3.10.
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| : 11. This study does not assume that roadways are empty at the start of the evacuation.
| |
| Rather, there is an initialization period (often referred to as fill time in traffic simulation) wherein the anticipated traffic volumes from the beginning of evacuation are loaded onto roadways in the study area. The amount of initialization/fill traffic that is on the roadways in the study area at the start of the evacuation depends on the scenario and the region being evacuated. See Section 3.11.
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| : 12. To account for boundary conditions (roadway conditions outside the study area that are not specifically modeled due to the limited radius of the study area) beyond the study area, this study assumed a 25% reduction in capacity on twolane roads and multilane highways for roadways that have traffic signals downstream. The 25% reduction in capacity is based on the prevalence of actuated traffic signals in the study area and the 3
| |
| The models of the I-DYNEV System were recognized as state of the art by the Atomic Safety & Licensing Board (ASLB) in past hearings. (Sources: Atomic Safety & Licensing Board Hearings on Seabrook and Shoreham; Urbanik). The models have continuously been refined and extended since those hearings and were independently validated by a consultant retained by the NRC. The DYNEV II model incorporates the latest technology in traffic simulation and in dynamic traffic assignment.
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| North Anna Power Station 22 KLD Engineering, P.C.
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| fact that the evacuating (main street) traffic volume is more significant than the competing (side street) traffic volume at any downstream signalized intersections, thereby warranting a more significant percentage (75% in this case) of the signal green time. There is no reduction in capacity for freeways due to boundary conditions.
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| 2.3 Study Assumptions on Mobilization Times
| |
| : 1. Trip generation time (also known as mobilization time, or the time required by evacuees to prepare for the evacuation) are based upon the results of the recent, online demographic survey. It is assumed that stated events take place in sequence such that all preceding events must be completed before the current event can occur.
| |
| : 2. One hundred percent (100%) of the EPZ population can be notified within 45 minutes, in accordance with the 2019 Federal Emergency Management Agency (FEMA) Radiological Emergency Preparedness Program Manual.
| |
| : 3. Commuter percentages (and percentage of residents awaiting the return of a commuter) are based on the results of the demographic survey. According to the survey results, 73% of the households in the EPZ have at least 1 commuter; 46% of those households with commuters will await the return of a commuter before beginning their evacuation trip (see Appendix F). Therefore, 34% (73% x 46% = 34%) of EPZ households will await the return of a commuter, prior to beginning their evacuation trip.
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| 2.4 Transit Dependent Assumptions
| |
| : 1. The percentage of transitdependent people who will rideshare with a neighbor or friend are based on the results of the demographic survey. According to the survey results, approximately 77% of the transitdependent population will rideshare (see Appendix F).
| |
| : 2. Buses are used to transport those without access to private vehicles:
| |
| : a. Schools/preschools
| |
| : i. If schools/preschools are in session, transport (buses) will evacuate students directly to the designated Evacuation Assembly Centers (EACs).
| |
| ii. For the schools that are evacuated via buses, it is assumed no school children will be picked up by their parents prior to the arrival of the buses.
| |
| iii. Schoolchildren, if school is in session, are given priority in assigning transit vehicles.
| |
| : b. Medical/Senior Living Facilities
| |
| : i. Buses, vans, wheelchair buses, wheelchair vans, and ambulances will evacuate patients at medical/senior living facilities within the EPZ, as needed.
| |
| ii. The percent breakdown of ambulatory, wheelchair bound and bedridden patients was obtained through phone calls to individual facilities.
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| North Anna Power Station 23 KLD Engineering, P.C.
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| : c. Transitdependent permanent residents:
| |
| : i. Transitdependent (do not own or have access to a private vehicle) general population will be evacuated to EACs.
| |
| ii. Access and/or functional needs population may require county assistance (ambulance, bus or wheelchair transport) to evacuate. This is considered separately from the general population ETE, as per NRC guidance.
| |
| iii. Households with 3 or more vehicles were assumed to have no need for transit vehicles.
| |
| : d. Analysis of the number of required roundtrips (waves) of evacuating transit vehicles are presented.
| |
| : e. Transport of transitdependent evacuees from EACs to congregate care centers is not considered in this study.
| |
| : 3. Transit vehicle capacities:
| |
| : a. School buses = 70 students (65 in Hanover County only) per bus for elementary schools/preschools and 50 students per bus for middle/high schools
| |
| : b. Ambulatory transitdependent persons, medical facility patients = 30 persons per bus
| |
| : c. Vans = 5 persons
| |
| : d. Ambulances = 2 bedridden persons (includes advanced and basic life support)
| |
| : e. Wheelchair buses = 15 wheelchair bound persons
| |
| : f. Wheelchair vans = 4 wheelchair bound persons
| |
| : 4. Transit vehicles mobilization times, which are considered in ETE calculations:
| |
| : a. School and transit buses will arrive at schools and facilities to be evacuated within 90 minutes of the ATE.
| |
| : b. Transit dependent buses are mobilized when approximately 90% of residents with no commuters have completed their mobilization at about 2 hours and 30 minutes after the ATE. The residents taking longer to mobilize are assumed to rideshare with a friend or neighbor.
| |
| : c. Vehicles will arrive at medical/senior living facilities to be evacuated within 90 minutes of the ATE.
| |
| : 5. Transit Vehicle loading times:
| |
| : a. Concurrent loading on multiple buses/transit vehicles is assumed
| |
| : b. School buses will be loaded in 15 minutes.
| |
| : c. Transit Dependent buses will require 1 minute of loading time per passenger.
| |
| : d. Buses for medical/senior living facilities will require 1 minute of loading time per ambulatory passenger.
| |
| : e. Wheelchair transport vehicles will require 5 minutes of loading time per passenger.
| |
| : f. Ambulances will be loaded in 15 minutes per bedridden passenger.
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| North Anna Power Station 24 KLD Engineering, P.C.
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| : 6. Drivers for all transit vehicles are available.
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| 2.5 Traffic and Access Control Assumptions
| |
| : 1. Traffic Control Points (TCP) and Access Control Points (ACP) as defined in the approved county and state emergency plans are considered in the ETE analysis, as per NRC guidance.
| |
| : 2. TCP and ACP are assumed to staffed approximately 120 minutes after the ATE, as per NRC guidance. It is assumed that no through traffic will enter the EPZ after this 120 minute time period.
| |
| : 3. All transit vehicles and other responders entering the EPZ to support the evacuation are unhindered by personnel manning TCPs and ACPs.
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| 2.6 Scenarios and Regions
| |
| : 1. A total of 14 Scenarios representing different temporal variations (season, time of day, day of week) and weather conditions are considered. Scenarios to be considered are defined in Table 21:
| |
| : a. The Kinetic Triathlon at Lake Anna State Park is considered as the special event (single or multiday event that attracts a significant population into the EPZ; recommended by NRC guidance) for Scenario 13.
| |
| : b. As per NRC guidance, one segment of one of the highest volume roadways will be out of service or one lane outbound on a freeway must be closed for a roadway impact scenario. This study considers the closure of US522 northbound from Route 612 (Monrovia Rd) to Route 719 (Belmont Rd) for the roadway impact scenario - Scenario 14.
| |
| : 2. Two types of adverse weather scenarios are considered. Rain may occur for either winter or summer scenarios; snow occurs in winter scenarios only. It is assumed that the rain or snow begins at about the same time the evacuation advisory is issued. Thus, no weatherrelated reduction in the number of transients who may be present in the EPZ is assumed. It is further assumed that snow removal equipment is available, the appropriate agencies are clearing/treating the roads as they would normally during snow, and the roads are passable albeit at lower speeds and capacities.
| |
| : 3. Adverse weather affects roadway capacity and free flow speeds. Transportation research indicates capacity and speed reductions of about 10% for rain and a range of 10% to 25% for snow. In accordance with Table 31 of Revision 1 to NUREG/CR7002, this study assumes a 10% reduction in speed and capacity for rain and light snow. The heavy snow scenarios considered assume that there was a significant snowfall such that minor roadways and driveways have snow on them. Major roadways have been plowed but still have a coating of snow on them that will slow traffic down and reduce roadway capacity. During heavy snow scenarios, a speed and capacity reduction of North Anna Power Station 25 KLD Engineering, P.C.
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| 15% and 25% was used, respectively. The adverse weather speed and capacity factors are shown in Table 22.
| |
| : 4. Some evacuees will need additional time to clear their driveways and access the public roadway system for heavy snow scenarios. The distribution of time for this activity was gathered through a demographic survey of the public and takes up to 180 minutes (see Appendix F, Figure F19). the time needed by evacuees to remove snow from their driveways is sufficient time for snow removal crews to mobilize and clear/treat major roadways. There are additional activities that a person will have to do before they actually begin their evacuation trip, which will delay their departure time. This allows additional time to plow the minor roads, as needed.
| |
| : 5. Employment is reduced slightly in the summer for vacations.
| |
| : 6. Mobilization and loading times for transit vehicles evacuating schools and the transit dependent population are slightly longer in adverse weather. Table 22 summarizes the impact of adverse weather on mobilization and loading times for transit vehicles.
| |
| : 7. Regions are defined by the underlying keyhole or circular configurations as specified in Section 1.4 of NUREG/CR7002, Rev. 1. These Regions, as defined, display irregular boundaries reflecting the geography of the PAZs included within these underlying configurations. All 16 cardinal and intercardinal wind direction keyhole configurations are considered. Regions to be considered are defined in Table 61. It is assumed that everyone within the group of PAZs forming a Region that is issued an ATE will, in fact, respond and evacuate in general accord with the planned routes.
| |
| : 8. Due to irregular shapes of the PAZs, there are instances wherein a small portion of a PAZ (a sliver) is within the keyhole and the population within that small portion is low (less than 500 people or 10% of the PAZ population, whichever is less). Under those circumstances, the PAZ would not be included in the Region so as to not evacuate large numbers of people outside of the keyhole for a small number of people that are actually in the keyhole, unless otherwise stated in the PAR document.
| |
| : 9. Staged evacuation is considered as defined in NUREG/CR7002, Rev. 1 - those people between 2 and 5 miles will shelterinplace until 90% of the 2Mile Region has evacuated, then they will evacuate. See Regions R43 through R55 in Table 61.
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| North Anna Power Station 26 KLD Engineering, P.C.
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| Table 21. Evacuation Scenario Definitions Scenario Season4 Day of Week Time of Day Weather Special 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None Midweek, 5 Summer Evening Good None Weekend 6 Winter Midweek Midday Good None 7 Winter Midweek Midday Rain/Light Snow None 8 Winter Midweek Midday Heavy Snow None 9 Winter Weekend Midday Good None 10 Winter Weekend Midday Rain/Light Snow None 11 Winter Weekend Midday Heavy Snow None Midweek, 12 Winter Evening Good None Weekend Special Event: Kinetic 13 Winter Weekend Midday Good Triathlon at Lake Anna State Park Roadway Impact: One 14 Summer Midweek Midday Good Segment Closure on US522 Northbound Table 22. Model Adjustment for Adverse Weather Mobilization Time Mobilization Loading Time Highway Free Flow for General Time for Transit for School Loading Time for Scenario Capacity* Speed* Population Vehicles Buses Transit Buses5 Rain 90% 90% 10minute 5minute 10minute No Effect increase increase increase Clear driveway before leaving 20minute 10minute 20minute Snow 75% 85%
| |
| home increase increase increase (See Figure F19)
| |
| *Adverse weather capacity and speed values are given as a percentage of good weather conditions.
| |
| Roads are assumed to be passable.
| |
| 4 Winter means that school is in session at normal enrollment levels, (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).
| |
| 5 Does not apply to medical/senior living facilities and those with access and/or functional needs as loading times for these people are already conservative.
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| North Anna Power Station 27 KLD Engineering, P.C.
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| Figure 21. Voluntary Evacuation Methodology North Anna Power Station 28 KLD Engineering, P.C.
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| 3 DEMAND ESTIMATION The estimates of demand, expressed in terms of people and vehicles, constitute a critical element in developing an evacuation plan. These estimates consist of three components:
| |
| : 1. An estimate of population within the EPZ, stratified into groups (resident, employee, transient).
| |
| : 2. An estimate, for each population group, of mean occupancy per evacuating vehicle. This estimate is used to determine the number of evacuating vehicles.
| |
| : 3. An estimate of potential doublecounting of vehicles.
| |
| Appendix E presents much of the source material for the population estimates. Our primary source of population data, the 2020 Census, is not adequate for directly estimating some transient groups.
| |
| Throughout the year, vacationers and tourists enter the EPZ. These nonresidents may dwell within the EPZ for a short period (e.g., a few days or one or two weeks), or may enter and leave within one day. Estimates of the size of these population components must be obtained, so that the associated number of evacuating vehicles can be ascertained.
| |
| The potential for doublecounting people and vehicles must be addressed. For example:
| |
| A resident who works and camps within the EPZ could be counted as a resident, again as an employee and once again as a transient.
| |
| A visitor who stays at a hotel and spends time at a park, then goes to a marina could be counted three times.
| |
| Furthermore, the number of vehicles at a location depends on time of day. For example, motel parking lots may be full at dawn and empty at noon. Similarly, parking lots at area parks, which are full at noon, may be almost empty at dawn. Estimating counts of vehicles by simply adding up the capacities of different types of parking facilities could overestimate the number of transients and can lead to ETE that are too conservative.
| |
| Analysis of the population characteristics of the NAPS EPZ indicates the need to identify three distinct groups:
| |
| Permanent residents - people who are yearround residents of the EPZ.
| |
| Transients - people who reside outside of the EPZ who enter the area for a specific purpose (shopping, recreation) and then leave the area. Transients also include seasonal residents who may spend several weeks or months in the EPZ.
| |
| Employees - people who reside outside of the EPZ and commute to work within the EPZ on a daily basis.
| |
| Estimates of the population and number of evacuating vehicles for each of the population groups are presented for each PAZ and by polar coordinate representation (population rose).
| |
| The NAPS EPZ is subdivided into 25 PAZs. The PAZs comprising the EPZ are shown in Figure 31.
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| North Anna Power Station 31 KLD Engineering, P.C.
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| 3.1 Permanent Residents The primary source for estimating permanent population is the latest U.S. Census data with an availability date of September 16, 2021. The average household size (2.90 persons/household -
| |
| See Appendix F, Subsection F.3.1) and the number of evacuating vehicles per household (1.64 vehicles/household - See Appendix F, Subsection F.3.2) were adapted from the demographic survey.
| |
| The permanent resident population is estimated by cutting the census block polygons by PAZ and EPZ boundaries using GIS software. A ratio of the original area of each census block and the updated area (after cutting) is multiplied by the total block population to estimate the population within the EPZ. The methodology (referred to as the area ratio method) assumes that the population is evenly distributed across a census block. Table 31 provides the permanent resident population within the EPZ, by PAZ, for 2010 and 2020 (based on the methodology above). As indicated, the permanent resident population within the EPZ has increased by 9.07% since the 2010 Census.
| |
| To estimate the number of vehicles, the year 2020 permanent resident population is divided by the average household size and then multiplied by the average number of evacuating vehicles per household. Permanent resident population and vehicle estimates are presented in Table
| |
| : 32. Figure 32 and Figure 33 present the permanent resident population and permanent resident vehicle estimates by sector and distance from NAPS. This rose was constructed using GIS software.
| |
| 3.2 Shadow Population A portion of the population living outside the evacuation area extending to 15 miles radially from the NAPS may elect to evacuate without having been instructed to do so. This area is called the Shadow Region. Based upon NUREG/CR7002, Rev. 1 guidance, it is assumed that 20% of the permanent resident population, based on U.S. Census Bureau data, in the Shadow Region will elect to evacuate.
| |
| Shadow population characteristics (household size, evacuating vehicles per household, mobilization time) are assumed to be the same as that for the EPZ permanent resident population. Table 33, Figure 34, and Figure 35 present estimates of the shadow population and vehicles, by sector. Note, the 2020 Census includes residents living in group quarters, such as skilled nursing facilities, group homes, prisons, college/university student housing, etc.
| |
| These people are transit dependent (will not evacuate in personal vehicles). To avoid double counting vehicles, the vehicle estimates for these people have been removed from the shadow population vehicle demand in Table 33 and Figure 35.
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| North Anna Power Station 32 KLD Engineering, P.C.
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| 3.3 Transient Population Transient population groups are defined as those people (who are not permanent residents, nor commuting employees) who enter the EPZ for a specific purpose (camping, recreation).
| |
| Transients may spend less than one day or stay overnight at camping facilities, hotels and motels. Data for these facilities were provided by Louisa County and by Spotsylvania County.
| |
| When data was not provided, the number of transient vehicles was estimated based on the parking lot capacity or accommodation capacity obtained from aerial imagery and facility websites. It is assumed that transients would travel to the recreational areas as a family/household. As such, the average household size (2.90 - See Section 3.1) was used to estimate the transient population. The transient attractions within the NAPS are summarized as follows:
| |
| Campgrounds - 2,368 transients and 930 vehicles; 2.55 transients per vehicle Marinas - 1,708 transients and 856 vehicles; 2.00 transients per vehicle (NOTE: vehicles with boat trailers are treated as 2 vehicles.)
| |
| Parks - 2,000 transients and 580 vehicles; 3.45 transients per vehicle Lodging Facilities - 72 transients and 46 vehicles; 1.57 transients per vehicle Appendix E summarizes the transient data that was estimated for the EPZ. Table E4 presents the number of transients visiting recreational areas within the EPZ and Table E5 presents the number of transients visiting lodging facilities within the EPZ.
| |
| 3.3.1 Seasonal Transient Population The NAPS EPZ has a secondary category of transient population which is seasonal residents.
| |
| These people will enter the area during the summer months and may stay considerably longer (several weeks or the entire season) than the average transient using a hotel or motel. The seasonal population use other lodging facilities such as condos, beach houses and summer rentals that otherwise would not be captured in a typical lodging population.
| |
| 2020 Census block data was used to estimate the seasonal resident population. Each census block includes information regarding the number of vacant and occupied households. An average vacant household percentage was calculated for the entire NAPS EPZ (20.1%) using this data.
| |
| It is assumed that seasonal residents will be renting homes near the Lake Anna shoreline. Using only those census blocks that are within 1.5 miles of the shoreline, the number of seasonal homes was calculated. It is further assumed that 20.1% (EPZ average) of the vacant homes within these census blocks are not rental homes and are in fact vacant homes. The remaining households (668 total) were considered to be seasonal households. An average household size of 2.90 persons per household is used to determine the seasonal transient population from the number of vacant homes, and 1.64 evacuating vehicles per seasonal household is used to determine the number of seasonal transient vehicles from the number of vacant homes.
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| North Anna Power Station 33 KLD Engineering, P.C.
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| | |
| It is estimated that there is an additional seasonal population of 1,956 transients traveling in 1,100 vehicles within the NAPS EPZ.
| |
| In total, there are 8,104 transients in the EPZ at peak times, evacuating in 3,512 vehicles (an average vehicle occupancy of 2.31 transients per vehicle). Table 34 presents transient population and transient vehicle estimates by PAZ. Figure 36 and Figure 37 present these data by sector and distance from the plant.
| |
| 3.4 Employees As per the NUREG/CR7002, Rev.1 guidance, employers with 200 or more employees working in a single shift are considered to be major employers. As such, employers not meeting this criterion are not considered in this study. Based on the employment data provided by the counties within the EPZ and by Dominion, North Anna Power Station is the only major employer within the EPZ, as shown in Appendix E, Table E3.
| |
| Employees who work within the EPZ fall into two categories:
| |
| Those who live and work in the EPZ Those who live outside of the EPZ and commute to jobs within the EPZ.
| |
| Those of the first category are already counted as part of the permanent resident population. To avoid double counting, we focus only on those employees commuting from outside the EPZ who will evacuate along with the permanent resident population. Data provided by Dominion was used to estimate the percentage of employees who live outside of the EPZ and commute to the power plant.
| |
| To estimate the evacuating employee vehicles, a vehicle occupancy of 1.10 employees per vehicle obtained from the demographic survey (see Appendix F, Subsection F.3.1) was used for NAPS. Table 35 presents the estimates of employees and vehicles commuting into the EPZ by PAZ. Figure 38 and Figure 39 present these data by sector.
| |
| 3.5 Medical Facilities Data for medical facilities were provided by Spotsylvania County. The number and type of evacuating vehicles that need to be provided depends on the patients' state of health. It is estimated that ambulances can transport up to 2 people. Table 36 summarizes the medical facility population and vehicles needed for evacuation. Section 8 details the evacuation of medical facilities and their patients.
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| North Anna Power Station 34 KLD Engineering, P.C.
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| | |
| 3.6 Transit Dependent Population The demographic survey (see Appendix F) results were used to estimate the portion of the population requiring transit service:
| |
| * Those persons in households that do not have a vehicle available.
| |
| * Those persons in households that do have vehicle(s) that would not be available at the time the evacuation is advised.
| |
| In the latter group, the vehicle(s) may be used by a commuter(s) who does not return (or is not expected to return) home to evacuate the household.
| |
| Table 37 presents estimates of transitdependent people. Note:
| |
| * Estimates of persons requiring transit vehicles include schoolchildren. For those evacuation scenarios where children are at school when an evacuation is ordered, separate transportation is provided for the schoolchildren. The actual need for transit vehicles by residents is thereby less than the given estimates. However, estimates of transit vehicles are not reduced when schools are in session.
| |
| * It is reasonable and appropriate to consider that many transitdependent persons will evacuate by ridesharing with neighbors, friends or family. For example, nearly 80% of those who evacuated from Mississauga, Ontario1 who did not use their own cars, shared a ride with neighbors or friends. Other documents report that approximately 70% of transit dependent persons were evacuated via ride sharing.
| |
| This study assumes 77% of transit dependent persons will ride share based on the results of the online demographic survey (see Appendix F, subsection F.3.1).
| |
| The estimated number of bus trips needed to service transitdependent persons is based on an estimate of average bus occupancy of 30 persons at the conclusion of the bus run. Transit vehicle seating capacities typically equal or exceed 60 children on average (roughly equivalent to 40 adults). If transit vehicle evacuees are two thirds adults and one third children, then the number of adult seats taken by 30 persons is 20 + (2/3 x10) = 27. On this basis, the average load factor anticipated is (27/40) x 100 = 68%. Thus, if the actual demand for service exceeds the estimates of Table 37 by 50%, the demand for service can still be accommodated by the available bus seating capacity.
| |
| 2 20 10 40 1.5 1.00 3
| |
| Table 37 indicates that transportation must be provided for 193 people. Therefore, a total of 7 bus runs are required from a capacity standpoint. In order to service all of the transit dependent population and have at least one bus drive through each of the PAZs picking up 1
| |
| Institute for Environmental Studies, University of Toronto, THE MISSISSAUGA EVACUATION FINAL REPORT, June 1981. The report indicates that 6,600 people of a transitdependent population of 8,600 people shared rides with other residents; a ride share rate of 77% (Page 510).
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| North Anna Power Station 35 KLD Engineering, P.C.
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| | |
| transit dependent people, 25 buses are used in the ETE calculations, (even though only 7 buses are needed from a capacity standpoint). These buses are represented as two vehicles in the ETE simulations due to their larger size and more sluggish operating characteristics.
| |
| To illustrate this estimation procedure, we calculate the number of persons, P, requiring public transit or rideshare, and the number of buses, B, required for the NAPS EPZ:
| |
| Where:
| |
| A = Percent of households with commuters C = Percent of households who will not await the return of a commuter 9,479 0.1 1.88 1 0.73 0.54 0.419 2.83 2 0.73 0.54 841 1 0.77 30 7 These calculations based on the demographic survey results are explained as follows:
| |
| * The number of households (HH) is computed by dividing the EPZ population by the average household size (27,489 ÷ 2.90) and is 9,479.
| |
| * Zero households indicated that they did not have access to a vehicle.
| |
| * The members of HH with 1 vehicle away (10.0%), who are at home, equal (1.881).
| |
| The number of HH where the commuter will not return home is equal to (9,479 x 0.10 x 0.88 x 0.73 x 0.54), as 73% of EPZ households have a commuter, 54% of which would not return home in the event of an emergency. The number of persons who will evacuate by public transit or rideshare is equal to the product of these two terms.
| |
| * The members of HH with 2 vehicles that are away (41.9%), who are at home, equal (2.83 - 2). The number of HH where neither commuter will return home is equal to 9,479 x 0.419 x 0.83 x (0.73 x 0.54)2. The number of persons who will evacuate by public transit or rideshare is equal to the product of these two terms (the last term is squared to represent the probability that neither commuter will return).
| |
| * Households with 3 or more vehicles are assumed to have no need for transit vehicles.
| |
| * The total number of persons requiring public transit is the sum of such people in HH with no vehicles, or with 1 or 2 vehicles that are away from home.
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| North Anna Power Station 36 KLD Engineering, P.C.
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| | |
| 3.7 School Population Demand Table 38 presents the school population and transportation requirements for the direct evacuation of all schools and preschools within the EPZ for the 20202021 school year. All schools and preschools in the NAPS EPZ are located in either Spotsylvania or Louisa County.
| |
| Student enrollment data was provided by emergency management agencies. The column in Table 38 entitled Buses Required specifies the number of buses required for each school under the following set of assumptions and estimates:
| |
| * No students will be picked up by their parents prior to the arrival of the buses.
| |
| * While many high school students commute to school using private automobiles (as discussed in Section 2.4 of NUREG/CR7002, Rev. 1), the estimate of buses required for school evacuation does not consider the use of these private vehicles.
| |
| * Bus capacity, expressed in students per bus, is set to 70 for elementary schools/preschools and 50 for middle/high schools.
| |
| * Those staff members who do not accompany the students will evacuate in their private vehicles.
| |
| * No allowance is made for student absenteeism, typically 3% daily.
| |
| The counties in the EPZ could introduce procedures whereby the schools are contacted prior to the dispatch of buses from the depot, to ascertain the current estimate of students to be evacuated. In this way, the number of buses dispatched to the schools will reflect the actual number needed. The need for buses would be reduced by any high school students who have evacuated using private automobiles (if permitted by school authorities). Those buses originally allocated to evacuate schoolchildren that are not needed due to children being picked up by their parents (although they are not advised to do so) can be gainfully assigned to service other facilities or those persons who do not have access to private vehicles or to ridesharing.
| |
| School buses are represented as two vehicles in the ETE simulation due to their larger size and more sluggish operating characteristics.
| |
| 3.8 Special Event One special event (Scenario 13) is considered for the ETE study - the Kinetic Triathlon at Lake Anna State Park, which occurs annually on the second weekend in May. Data was gathered by calling the facility for the previous study. This event attracts an additional 1,100 transients to the park, traveling in approximately 249 vehicles. Spotsylvania County confirmed the data for this event. Spotsylvania County also mentioned another potential special event - Live and Outside at the Lake Anna Winery - which attracts 300 transients in 100 vehicles. However, this was not chosen as the special event as it had less transients and evacuating vehicles than the Kinetic Triathlon.
| |
| These vehicles are all loaded at the park and are included in Table 64 under Special Event. The special event vehicle trips were generated utilizing the same mobilization distributions as North Anna Power Station 37 KLD Engineering, P.C.
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| | |
| transients. Public transportation is not provided for this event and was not considered in the special event analysis.
| |
| 3.9 Access and/or Functional Needs Population The county emergency management agencies provided the following data regarding registered population with access and/or functional needs:
| |
| Caroline County - 12 people total, 11 ambulatory and 1 wheelchair bound Hanover County - 22 people, 19 ambulatory and 3 bedridden Louisa County - 200 people, 178 ambulatory, 20 bedridden, and 2 wheelchair bound (detailed breakdown of population was not provided - assumed 89% ambulatory, 10%
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| bedridden and 1% wheelchair bound based on the data provided from the other counties)
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| Orange County - 0 people Spotsylvania County - 76 people, 68 ambulatory, and 8 bedridden EPZ Total: 310 people, 276 ambulatory, 31 bedridden, and 3 wheelchair bound Table 39 shows the total number of people registered for access and/or functional needs by type of need. The table also estimates the transportation resources needed to evacuate these people in a timely manner using the transit vehicle capacity assumptions from item 3 of Section 2.4. Buses needed to evacuate the access and/or functional needs population are represented as two vehicles in the ETE simulations due to their larger size and more sluggish operating characteristics.
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| 3.10 External Traffic Vehicles will be traveling through the EPZ (externalexternal trips) at the time of an accident.
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| After the Advisory to Evacuate (ATE) is announced, these throughtravelers will also evacuate.
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| These through vehicles are assumed to travel on major routes traversing the study area - US1, Interstate95 (I95) and I64. It is assumed that this traffic will continue to enter the study area during the first 120 minutes following the ATE. Note, I95 and I64 do not actually enter the study area and US1 only has a small section in the study area. Nonetheless, many evacuees from the study area will ultimately use these routes to evacuate the area and their egress may be slowed by traffic flowing on these major through routes.
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| Average Annual Daily Traffic (AADT) data was obtained from the Virginia Department of Transportation (VDOT2) to estimate the number of vehicles per hour on the aforementioned routes. The AADT was multiplied by the KFactor, which is the proportion of the AADT on a roadway segment or link during the design hour, resulting in the design hour volume (DHV).
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| The design hour is usually the 30th highest hourly traffic volume of the year, measured in vehicles per hour (vph). The DHV is then multiplied by the DFactor, which is the proportion of the DHV occurring in the peak direction of travel (also known as the directional split). The 2
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| resulting values are the directional design hourly volumes (DDHV), and are presented in Table 310, for each of the routes considered. The DDHV is then multiplied by 2 hours (access control points - ACP - are assumed to be activated at 120 minutes after the ATE as per item 2 in Section 2.5) to estimate the total number of external vehicles loaded on the analysis network.
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| As indicated, there are 16,708 vehicles entering the study area as externalexternal trips prior to the activation of ACP and the diversion of this traffic. This number is reduced to 40% for evening scenarios (Scenarios 5 and 12) as discussed in Section 6.
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| 3.11 Background Traffic Section 5 discusses the time needed for the people in the EPZ to mobilize and begin their evacuation trips. As shown in Table 59, there are 15 time periods during which traffic is loaded on to roadways in the study area to model the mobilization time of people in the EPZ. Note, there is no traffic generated during the 15th time period, as this time period is intended to allow traffic that has already begun evacuating to clear the study area boundaries.
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| This study does not assume that roadways are empty at the start of the evacuation (Time Period 1). Rather, there is an initialization time period (often referred to as fill time in traffic simulation) wherein the anticipated traffic volumes from the start of the evacuation are loaded onto roadways in the study area. The amount of initialization/fill traffic that is on the roadways in the study area at the start of evacuation depends on the scenario and the region being evacuated (see Section 6). There are approximately 2,500 vehicles on the roadways in the study area at the end of fill time for an evacuation of the entire EPZ (Region R03) under Scenario 1 (summer, midweek, midday, good weather) conditions.
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| 3.12 Summary of Demand A summary of the population and vehicle demand is provided in Table 311 and Table 312, respectively. This summary includes all population groups described in this section. A total of 51,399 people and 40,960 vehicles are considered in this study.
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| Table 31. EPZ Permanent Resident Population PAZ 2010 Population 2020 Population 2 466 463 3 1,490 1,524 4 1,107 1,322 5 1,472 1,476 6 484 575 7 484 668 8 409 464 9 203 238 10 429 487 11 981 1,017 12 1,561 1,681 13 1,364 1,412 14 803 867 15 697 843 16 1,601 1,860 17 144 214 18 2,416 2,592 19 383 456 20 1,026 1,113 21 2,232 2,386 22 1,538 1,718 23 260 264 24 946 925 25 464 573 26 2,242 2,351 EPZ TOTAL: 25,202 27,489 EPZ Population Growth (20102020): 9.07%
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| Table 32. Permanent Resident Population and Vehicles by PAZ 2020 PAZ 2020 Population Resident Vehicles 2 463 264 3 1,524 862 4 1,322 746 5 1,476 831 6 575 325 7 668 380 8 464 263 9 238 134 10 487 276 11 1,017 576 12 1,681 951 13 1,412 799 14 867 491 15 843 478 16 1,860 1,050 17 214 121 18 2,592 1,467 19 456 258 20 1,113 630 21 2,386 1,348 22 1,718 973 23 264 149 24 925 524 25 573 323 26 2,351 1,331 EPZ TOTAL: 27,489 15,550 North Anna Power Station 311 KLD Engineering, P.C.
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| Table 33. Shadow Population and Vehicles by Sector Evacuating Sector 2020 Population Vehicles N 1,380 783 NNE 2,376 1,344 NE 5,632 3,174 ENE 2,623 1,483 E 5,173 2,920 ESE 5,214 2,943 SE 996 565 SSE 1,139 643 S 1,445 814 SSW 1,093 620 SW 932 525 WSW 2,770 1,519 W 1,596 902 WNW 1,463 825 NW 723 408 NNW 1,809 1,024 TOTAL: 36,364 20,492 North Anna Power Station 312 KLD Engineering, P.C.
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| Table 34. Summary of Transients and Transient Vehicles Seasonal Total Transient Seasonal Resident Total Transient PAZ Transients Vehicles Residents Vehicles Transients Vehicles 2 9 5 0 0 9 5 3 0 0 0 0 0 0 4 0 0 134 75 134 75 5 0 0 6 3 6 3 6 0 0 109 61 109 61 7 0 0 65 36 65 36 8 0 0 161 90 161 90 9 175 120 44 25 219 145 10 0 0 264 150 264 150 11 125 45 193 109 318 154 12 275 110 27 15 302 125 13 35 27 26 15 61 42 14 2,961 979 128 72 3,089 1,051 15 255 141 183 102 438 243 16 2,000 800 85 48 2,085 848 17 0 0 36 20 36 20 18 110 45 263 148 373 193 19 0 0 0 0 0 0 20 0 0 0 0 0 0 21 0 0 0 0 0 0 22 0 0 9 5 9 5 23 0 0 0 0 0 0 24 0 0 0 0 0 0 25 203 140 190 107 393 247 26 0 0 33 19 33 19 EPZ TOTAL: 6,148 2,412 1,956 1,100 8,104 3,512 North Anna Power Station 313 KLD Engineering, P.C.
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| Table 35. Summary of Employees and Employee Vehicles Commuting into the EPZ PAZ Employees Employee Vehicles 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 591 537 9 0 0 10 0 0 11 0 0 12 0 0 13 0 0 14 0 0 15 0 0 16 0 0 17 0 0 18 0 0 19 0 0 20 0 0 21 0 0 22 0 0 23 0 0 24 0 0 25 0 0 26 0 0 EPZ TOTAL: 591 537 North Anna Power Station 314 KLD Engineering, P.C.
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| Table 36. Medical Facility Transit Demand Estimates Current Wheelchair Bed Bus Wheelchair Ambulance PAZ Facility Name Capacity Census Ambulatory Bound ridden Runs Van Runs Runs Spotsylvania County 12 Lake Anna Elder Care Inc 8 8 0 0 8 0 0 4 Spotsylvania County Subtotal: 8 8 0 0 8 0 0 4 EPZ TOTAL: 8 8 0 0 8 0 0 4 Table 37. TransitDependent Population Estimates Survey Average Survey Percent HH Size Survey Percent HH Survey Percent HH Total People Population with Indicated Estimated with Indicated No. of Percent HH with Non People Estimated Requiring Requiring 2020 EPZ No. of Vehicles No. of Vehicles with Returning Requiring Ridesharing Public Public Population 0 1 2 Households 0 1 2 Commuters Commuters Transport Percentage Transit Transit 27,489 0 1.88 2.83 9,479 0.0% 10.0% 41.9% 73% 54% 841 77% 193 0.7%
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| Table 38. School and Preschool Population Demand Estimates Buses PAZ School Name Enrollment Required Louisa County 2 Mineral Christian Preschool 60 1 3 Louisa County High School 1510 31 3 Louisa County Middle School 1191 24 3 Thomas Jefferson Elementary School 587 9 5 Jouett Elementary School 575 9 Louisa County Subtotal: 3,923 74 Spotsylvania County 12 Livingston Elementary 393 6 21 Post Oak Middle School 700 14 21 Spotsylvania High School 1300 26 21 Spotsylvania High School Governor's School 60 2 21 Berkeley Elementary 269 4 Spotsylvania County Subtotal: 2,722 52 EPZ TOTAL: 6,645 126 Table 39. Access and/or Functional Needs Demand Summary Population Group Vehicle Type Population Vehicles deployed Ambulatory Bus 276 463 Wheelchair bound Wheelchair Van 3 1 Bedridden Ambulance 31 16 Total: 310 63 3
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| Only 10 buses are needed from a capacity standpoint. However, 46 buses were considered to limit the number of stops made by each bus. See Section 8.2 for additional information. Also, buses are modeled as 2 passenger car equivalents in DYNEV.
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| Table 310. NAPS EPZ External Traffic Upstream Downstream Road VDOT4 Hourly External Node Node Name Direction AADT KFactor5 DFactor5 Volume Traffic6 8330 330 I64 EB 20,000 0.116 0.5 1,160 2,320 8329 329 I64 WB 20,000 0.116 0.5 1,160 2,320 8152 152 I95 NB 51,000 0.091 0.5 2,321 4,642 8146 146 I95 SB 51,000 0.091 0.5 2,321 4,642 8303 303 US1 NB 12,000 0.116 0.5 696 1,392 8265 265 US1 SB 12,000 0.116 0.5 696 1,392 TOTAL 16,708 4
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| https://www.virginiadot.org/info/2019_traffic_data_by_jurisdiction.asp 5
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| Highway Capacity Manual 2016 6
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| Interstate-64 and Interstate-95 are outside of the Shadow Region and only a small portion of US-1 is in the Shadow Region.
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| Table 311. Summary of Population Demand7 Schools Transit Seasonal Medical and Special Shadow8 External PAZ Residents Dependent Transients Transients Employees Facilities Preschools Event Population Traffic Total 2 463 3 9 0 0 0 60 0 0 0 535 3 1,524 11 0 0 0 0 3,288 0 0 0 4,823 4 1,322 9 0 134 0 0 0 0 0 0 1,465 5 1,476 10 0 6 0 0 575 0 0 0 2,067 6 575 4 0 109 0 0 0 0 0 0 688 7 668 5 0 65 0 0 0 0 0 0 738 8 464 3 0 161 591 0 0 0 0 0 1,219 9 238 2 175 44 0 0 0 0 0 0 459 10 487 3 0 264 0 0 0 0 0 0 754 11 1,017 7 125 193 0 0 0 0 0 0 1,342 12 1,681 12 275 27 0 8 393 0 0 0 2,396 13 1,412 10 35 26 0 0 0 0 0 0 1,483 14 867 6 2,961 128 0 0 0 1,100 0 0 5,062 15 843 6 255 183 0 0 0 0 0 0 1,287 16 1,860 13 2,000 85 0 0 0 0 0 0 3,958 17 214 2 0 36 0 0 0 0 0 0 252 18 2,592 18 110 263 0 0 0 0 0 0 2,983 19 456 3 0 0 0 0 0 0 0 0 459 20 1,113 8 0 0 0 0 0 0 0 0 1,121 21 2,386 17 0 0 0 0 2,329 0 0 0 4,732 22 1,718 12 0 9 0 0 0 0 0 0 1,739 23 264 2 0 0 0 0 0 0 0 0 266 24 925 6 0 0 0 0 0 0 0 0 931 25 573 4 203 190 0 0 0 0 0 0 970 26 2,351 17 0 33 0 0 0 0 0 0 2,400 Shadow Region 0 0 0 0 0 0 0 0 7,273 0 7,273 TOTAL: 27,489 193 6,148 1,956 591 8 6,645 1,100 7,273 0 51,403 7
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| Since the spatial distribution of the access and/or functional needs population is unknown, they are not included in this table.
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| 8 Shadow population has been reduced to 20%. Refer to Figure 2-1 for additional information.
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| Table 312. Summary of Vehicle Demand9 Schools Transit Seasonal Medical and Special Shadow11 External PAZ Residents Dependent10 Transients Transients Employees Facilities Preschools Event Population Traffic Total 2 264 2 5 0 0 0 2 0 0 0 273 3 862 2 0 0 0 0 128 0 0 0 992 4 746 2 0 75 0 0 0 0 0 0 823 5 831 2 0 3 0 0 18 0 0 0 854 6 325 2 0 61 0 0 0 0 0 0 388 7 380 2 0 36 0 0 0 0 0 0 418 8 263 2 0 90 537 0 0 0 0 0 892 9 134 2 120 25 0 0 0 0 0 0 281 10 276 2 0 150 0 0 0 0 0 0 428 11 576 2 45 109 0 0 0 0 0 0 732 12 951 2 110 15 0 4 12 0 0 0 1,094 13 799 2 27 15 0 0 0 0 0 0 843 14 491 2 979 72 0 0 0 249 0 0 1,793 15 478 2 141 102 0 0 0 0 0 0 723 16 1,050 2 800 48 0 0 0 0 0 0 1,900 17 121 2 0 20 0 0 0 0 0 0 143 18 1,467 2 45 148 0 0 0 0 0 0 1,662 19 258 2 0 0 0 0 0 0 0 0 260 20 630 2 0 0 0 0 0 0 0 0 632 21 1,348 2 0 0 0 0 92 0 0 0 1,442 22 973 2 0 5 0 0 0 0 0 0 980 23 149 2 0 0 0 0 0 0 0 0 151 24 524 2 0 0 0 0 0 0 0 0 526 25 323 2 140 107 0 0 0 0 0 0 572 26 1,331 2 0 19 0 0 0 0 0 0 1,352 Shadow Region 0 0 0 0 0 0 0 0 4,098 16,708 20,806 TOTAL: 15,550 50 2,412 1,100 537 4 252 249 4,098 16,708 40,960 9
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| Since the spatial distribution of the access and/or functional needs population is unknown, vehicles needed to evacuate access and/or functional needs population are not included in this table.
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| 10 Buses (including transit-dependent buses and school buses) represented as two passenger vehicles. Refer to Section 3.7 and Section 8 for additional information.
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| 11 Shadow vehicles have been reduced to 20%. Refer to Figure 2-1 for additional information.
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| Figure 31. PAZs Comprising the NAPS EPZ North Anna Power Station 320 KLD Engineering, P.C.
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| Figure 32. Permanent Resident Population by Sector North Anna Power Station 321 KLD Engineering, P.C.
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| Figure 33. Permanent Resident Vehicles by Sector North Anna Power Station 322 KLD Engineering, P.C.
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| Figure 34. Shadow Population by Sector North Anna Power Station 323 KLD Engineering, P.C.
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| Figure 35. Shadow Vehicles by Sector North Anna Power Station 324 KLD Engineering, P.C.
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| Figure 36. Transient Population by Sector North Anna Power Station 325 KLD Engineering, P.C.
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| Figure 37. Transient Vehicles by Sector North Anna Power Station 326 KLD Engineering, P.C.
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| Figure 38. Employee Population by Sector North Anna Power Station 327 KLD Engineering, P.C.
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| Figure 39. Employee Vehicles by Sector North Anna Power Station 328 KLD Engineering, P.C.
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| 4 ESTIMATION OF HIGHWAY CAPACITY The ability of the road network to service vehicle demand is a major factor in determining how rapidly an evacuation can be completed. The capacity of a road is defined as the maximum hourly rate at which persons or vehicles can reasonably be expected to traverse a point or uniform section of a lane of roadway during a given time period under prevailing roadway, traffic, and control conditions, as stated in the 2016 Highway Capacity Manual (HCM 2016). This section discusses how the capacity of the roadway network was estimated.
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| In discussing capacity, different operating conditions have been assigned alphabetical designations, A through F, to reflect the range of traffic operational characteristics. These designations have been termed "Levels of Service" (LOS). For example, LOS A connotes freeflow and highspeed operating conditions; LOS F represents a forced flow condition. LOS E describes traffic operating at or near capacity.
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| Another concept, closely associated with capacity, is Service Volume. Service volume (SV) is defined as The maximum hourly rate at which vehicles, bicycles or persons reasonably can be expected to traverse a point or uniform section of a roadway during an hour under specific assumed conditions while maintaining a designated level of service. This definition is similar to that for capacity. The major distinction is that values of SV vary from one LOS to another, while capacity is the SV at the upper bound of LOS E, only.
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| Thus, in simple terms, an SV is the maximum traffic that can travel on a road and still maintain a certain perceived level of quality to a driver based on the A, B, C, rating system (LOS). Any additional vehicles above the SV would drop the rating to a lower letter grade.
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| This distinction is illustrated in Exhibit 1237 of the HCM 2016. As indicated there, the SV varies with Free Flow Speed (FFS), and LOS. The SV is calculated by the DYNEV II simulation model, based on the specified link attributes, FFS, capacity, control device and traffic demand.
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| Other factors also influence capacity. These include, but are not limited to:
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| Lane width Shoulder width Pavement condition Horizontal and vertical alignment (curvature and grade)
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| Percent truck traffic Control device (and timing, if it is a signal)
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| Weather conditions (good, rain, snow, fog, wind speed)
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| These factors are considered during the road survey and in the capacity estimation process; some factors have greater influence on capacity than others. For example, lane and shoulder width have only a limited influence on Base Free Flow Speed (BFFS1) according to Exhibit 157 of the HCM 2016. Consequently, lane and shoulder widths at the narrowest points were observed during the road survey and these observations were recorded, but no detailed 1
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| A very rough estimate of BFFS might be taken as the posted speed limit plus 10 mph (HCM 2016 Page 15-15)
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| measurements of lane or shoulder width were taken. Horizontal and vertical alignment can influence both FFS and capacity. The estimated FFS were measured using the survey vehicles speedometer and observing local traffic, under free flow conditions. Free flow speeds ranged from 15 to 75 mph in the study area. Capacity is estimated from the procedures of the HCM 2016. For example, HCM Exhibit 71(b) shows the sensitivity of SV at the upper bound of LOS D to grade (capacity is the SV at the upper bound of LOS E).
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| The amount of traffic that can flow on a roadway is effectively governed by vehicle speed and spacing. The faster that vehicles can travel when closely spaced, the higher the amount of flow.
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| As discussed in Section 2.6, it is necessary to adjust capacity figures to represent the prevailing conditions. Adverse conditions like inclement weather, construction, and other incidents tend to slow traffic down and often, also increase vehicletovehicles separation, thus decreasing the amount of traffic flow. Based on limited empirical data, conditions such as rain reduce the values of freeflow speed and of highway capacity by approximately 10%. Over the last decade new studies have been made on the effects of rain on traffic capacity. These studies indicate a range of effects between 5% and 25% depending on wind speed and precipitation rates. As indicated in Section 2.6, we employ, a reduction in free speed and in highway capacity of 10%
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| for rain\light snow. The free speed and highway capacity reductions are 15% and 25%,
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| respectively, during heavy snow conditions.
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| Since congestion arising from evacuation may be significant, estimates of roadway capacity must be determined with great care. Because of its importance, a brief discussion of the major factors that influence highway capacity is presented in this section.
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| Rural highways generally consist of: (1) one or more uniform sections with limited access (driveways, parking areas) characterized by uninterrupted flow; and (2) approaches to at grade intersections where flow can be interrupted by a control device or by turning or crossing traffic at the intersection. Due to these differences, separate estimates of capacity must be made for each section. Often, the approach to the intersection is widened by the addition of one or more lanes (turn pockets or turn bays), to compensate for the lower capacity of the approach due to the factors there that can interrupt the flow of traffic. These additional lanes are recorded during the field survey and later entered as input to the DYNEV II system.
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| 4.1 Capacity Estimations on Approaches to Intersections Atgrade intersections are apt to become the first bottleneck locations under local heavy traffic volume conditions. This characteristic reflects the need to allocate access time to the respective competing traffic streams by exerting some form of control. During evacuation, control at critical intersections will often be provided by traffic control personnel assigned for that purpose, whose directions may supersede traffic control devices. See Appendix G for more information.
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| The perlane capacity of an approach to a signalized intersection can be expressed (simplistically) in the following form:
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| 3600 3600 where:
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| Qcap,m = Capacity of a single lane of traffic on an approach, which executes movement, m, upon entering the intersection; vehicles per hour (vph) hm = Mean queue discharge headway of vehicles on this lane that are executing movement, m; seconds per vehicle G = Mean duration of GREEN time servicing vehicles that are executing movement, m, for each signal cycle; seconds L = Mean "lost time" for each signal phase servicing movement, m; seconds C = Duration of each signal cycle; seconds Pm = Proportion of GREEN time allocated for vehicles executing movement, m, from this lane. This value is specified as part of the control treatment.
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| m = The movement executed by vehicles after they enter the intersection: through, leftturn, rightturn, and diagonal.
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| The turnmovementspecific mean discharge headway hm, depends in a complex way upon many factors: roadway geometrics, turn percentages, the extent of conflicting traffic streams, the control treatment, and others. A primary factor is the value of "saturation queue discharge headway", hsat, which applies to through vehicles that are not impeded by other conflicting traffic streams. This value, itself, depends upon many factors including motorist behavior.
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| Formally, we can write, where:
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| hsat = Saturation discharge headway for through vehicles; seconds per vehicle F1,F2 = The various known factors influencing hm fm( ) = Complex function relating hm to the known (or estimated) values of hsat, F1, F2, North Anna Power Station 43 KLD Engineering, P.C.
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| The estimation of hm for specified values of hsat, F1, F2, ... is undertaken within the DYNEV II simulation model by a mathematical model2. The resulting values for hm always satisfy the condition:
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| That is, the turnmovementspecific discharge headways are always greater than, or equal to the saturation discharge headway for through vehicles. These headways (or its inverse equivalent, saturation flow rate), may be determined by observation or using the procedures of the HCM 2016.
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| The above discussion is necessarily brief given the scope of this evacuation time estimate (ETE) report and the complexity of the subject of intersection capacity. In fact, Chapters 19, 20 and 21 in the HCM 2016 address this topic. The factors, F1, F2, , influencing saturation flow rate are identified in equation (198) of the HCM 2016.
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| The traffic signals within the EPZ and Shadow Region are modeled using representative phasing plans and phase durations obtained as part of the field data collection. Traffic responsive signal installations allow the proportion of green time allocated (Pm) for each approach to each intersection, to be determined by the expected traffic volumes on each approach during evacuation circumstances. The amount of green time (G) allocated is subject to maximum and minimum phase duration constraints; 2 seconds of yellow time are indicated for each signal phase and 1 second of allred time is assigned between signal phases, typically. If a signal is pre timed, the yellow and allred times observed during the road survey are used. A lost time (L) of 2.0 seconds is used for each signal phase in the analysis.
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| 4.2 Capacity Estimation along Sections of Highway The capacity of highway sections as distinct from approaches to intersections is a function of roadway geometrics, traffic composition (e.g., percent heavy trucks and buses in the traffic stream) and, of course, motorist behavior. There is a fundamental relationship which relates SV (i.e., the number of vehicles serviced within a uniform highway section in a given time period) to traffic density. The top curve in Figure 41 illustrates this relationship.
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| As indicated, there are two flow regimes: (1) Free Flow (left side of curve); and (2) Forced Flow (right side). In the Free Flow regime, the traffic demand is fully serviced; the SV increases as demand volume and density increase, until the SV attains its maximum value, which is the capacity of the highway section. As traffic demand and the resulting highway density increase beyond this "critical" value, the rate at which traffic can be serviced (i.e., the SV) can actually decline below capacity (capacity drop). Therefore, in order to realistically represent traffic performance during congested conditions (i.e., when demand exceeds capacity), it is necessary to estimate the service volume, VF, under congested conditions.
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| 2 Lieberman, E., "Determining Lateral Deployment of Traffic on an Approach to an Intersection", McShane, W. & Lieberman, E.,
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| "Service Rates of Mixed Traffic on the far Left Lane of an Approach". Both papers appear in Transportation Research Record 772, 1980. Lieberman, E., Xin, W., Macroscopic Traffic Modeling for Large-Scale Evacuation Planning, presented at the TRB 2012 Annual Meeting, January 22-26, 2012.
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| The value of VF can be expressed as:
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| where:
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| R = Reduction factor which is less than unity We have employed a value of R=0.90. The advisability of such a capacity reduction factor is based upon empirical studies that identified a falloff in the service flow rate when congestion occurs at bottlenecks or choke points on a freeway system. Zhang and Levinson3 describe a research program that collected data from a computerbased surveillance system (loop detectors) installed on the Interstate Highway System, at 27 active bottlenecks in the twin cities metro area in Minnesota over a 7week period. When flow breakdown occurs, queues are formed which discharge at lower flow rates than the maximum capacity prior to observed breakdown. These queue discharge flow (QDF) rates vary from one location to the next and also vary by day of week and time of day based upon local circumstances. The cited reference presents a mean QDF of 2,016 passenger cars per hour per lane (pcphpl). This figure compares with the nominal capacity estimate of 2,250 pcphpl estimated for the ETE. The ratio of these two numbers is 0.896 which translates into a capacity reduction factor of 0.90.
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| Since the principal objective of ETE analyses is to develop a realistic estimate of evacuation times, use of the representative value for this capacity reduction factor (R=0.90) is justified. This factor is applied only when flow breaks down, as determined by the simulation model.
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| Rural roads, like freeways, are classified as uninterrupted flow facilities. (This is in contrast with urban street systems which have closely spaced signalized intersections and are classified as interrupted flow facilities.) As such, traffic flow along rural roads is subject to the same effects as freeways in the event traffic demand exceeds the nominal capacity, resulting in queuing and lower QDF rates. As a practical matter, rural roads rarely break down at locations away from intersections. Any breakdowns on rural roads are generally experienced at intersections where other model logic applies, or at lane drops which reduce capacity there.
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| Therefore, the application of a factor of 0.90 is appropriate on rural roads, but rarely, if ever, activated.
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| The estimated value of capacity is based primarily upon the type of facility and on roadway geometrics. Sections of roadway with adverse geometrics are characterized by lower freeflow speeds and lane capacity. Exhibit 1546 in the HCM 2016 was referenced to estimate saturation flow rates. The impact of narrow lanes and shoulders on freeflow speed and on capacity is not material, particularly when flow is predominantly in one direction as is the case during an evacuation.
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| The procedure used here was to estimate "section" capacity, VE, based on observations made traveling over each section of the evacuation network, based on the posted speed limits and travel behavior of other motorists and by reference to the HCM 2016. The DYNEV II simulation model determines for each highway section, represented as a network link, whether its 3
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| Lei Zhang and David Levinson, Some Properties of Flows at Freeway Bottlenecks, Transportation Research Record 1883, 2004.
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| capacity would be limited by the "sectionspecific" service volume, VE, or by the intersectionspecific capacity. For each link, the model selects the lower value of capacity.
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| 4.3 Application to the NAPS Study Area As part of the development of the linknode analysis network for the study area, an estimate of roadway capacity is required. The source material for the capacity estimates presented herein is contained in:
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| 2016 Highway Capacity Manual (HCM 2016)
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| Transportation Research Board National Research Council Washington, D.C.
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| The highway system in the study area consists primarily of three categories of roads and, of course, intersections:
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| TwoLane roads: Local, State Multilane Highways (atgrade)
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| Freeways Each of these classifications will be discussed.
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| 4.3.1 TwoLane Roads Ref: HCM 2016 Chapter 15 Two lane roads comprise the majority of highways within the study area. The perlane capacity of a twolane highway is estimated at 1,700 passenger cars per hour (pc/h). This estimate is essentially independent of the directional distribution of traffic volume except that, for extended distances, the twoway capacity will not exceed 3,200 pc/h. The HCM 2016 procedures then estimate LOS and Average Travel Speed. The DYNEV II simulation model accepts the specified value of capacity as input and computes average speed based on the timevarying demand: capacity relations.
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| Based on the field survey and on expected traffic operations associated with evacuation scenarios:
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| Most sections of twolane roads within the study area is classified as Class I, with "level terrain"; some are rolling terrain.
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| Class II highways are mostly those within urban and suburban centers.
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| 4.3.2 Multilane Highway Ref: HCM 2016 Chapter 12 Exhibit 128 of the HCM 2016 presents a set of curves that indicate a perlane capacity ranging from approximately 1,900 to 2,300 pc/h, for freespeeds of 45 to 70 mph, respectively. Based on observation, the multilane highways outside of urban areas within the study area, service North Anna Power Station 46 KLD Engineering, P.C.
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| traffic with freespeeds in this range. The actual timevarying speeds computed by the simulation model reflect the demand and capacity relationship and the impact of control at intersections. A conservative estimate of perlane capacity of 1,900 pc/h is adopted for this study for multilane highways outside of urban areas.
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| 4.3.3 Freeways Ref: HCM 2016 Chapters 10, 12, 13, 14 Chapter 10 of the HCM 2016 describes a procedure for integrating the results obtained in Chapters 12, 13 and 14, which compute capacity and LOS for freeway components. Chapter 10 also presents a discussion of simulation models. The DYNEV II simulation model automatically performs this integration process.
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| Chapter 12 of the HCM 2016 presents procedures for estimating capacity and LOS for Basic Freeway Segments". Exhibit 1237 of the HCM 2016 presents capacity vs. free speed estimates, which are provided below.
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| Free Speed (mph): 55 60 65 70+
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| PerLane Capacity (pc/h): 2,250 2,300 2,350 2,400 The inputs to the simulation model are highway geometrics, freespeeds and capacity based on field observations. The simulation logic calculates actual timevarying speeds based on demand:
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| capacity relationships. A conservative estimate of perlane capacity of 2,250 pc/h is adopted for this study for freeways.
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| Chapter 13 of the HCM 2016 presents procedures for estimating capacity, speed, density and LOS for freeway weaving sections. The simulation model contains logic that relates speed to demand volume: capacity ratio. The value of capacity obtained from the computational procedures detailed in Chapter 13 depends on the "Type" and geometrics of the weaving segment and on the "Volume Ratio" (ratio of weaving volume to total volume).
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| Chapter 14 of the HCM 2016 presents procedures for estimating capacities of ramps and of "merge" areas. There are three significant factors to the determination of capacity of a ramp freeway junction: The capacity of the freeway immediately downstream of an onramp or immediately upstream of an offramp; the capacity of the ramp roadway; and the maximum flow rate entering the ramp influence area. In most cases, the freeway capacity is the controlling factor. Values of this merge area capacity are presented in Exhibit 1410 of the HCM 2016 and depend on the number of freeway lanes and on the freeway free speed. Ramp capacity is presented in Exhibit 1412 and is a function of the ramp FFS. The DYNEV II simulation model logic simulates the merging operations of the ramp and freeway traffic in accord with the procedures in Chapter 14 of the HCM 2016. If congestion results from an excess of demand relative to capacity, then the model allocates service appropriately to the two entering traffic streams and produces LOS F conditions (The HCM 2016 does not address LOS F explicitly).
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| 4.3.4 Intersections Ref: HCM 2016 Chapters 19, 20, 21, 22 Procedures for estimating capacity and LOS for approaches to intersections are presented in Chapter 19 (signalized intersections), Chapters 20, 21 (unsignalized intersections) and Chapter 22 (roundabouts). The complexity of these computations is indicated by the aggregate length of these chapters. The DYNEV II simulation logic is likewise complex.
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| The simulation model explicitly models intersections: Stop/yield controlled intersections (both 2way and allway) and traffic signal controlled intersections. Where intersections are controlled by fixed time controllers, traffic signal timings are set to reflect average (non evacuation) traffic conditions. Actuated traffic signal settings respond to the timevarying demands of evacuation traffic to adjust the relative capacities of the competing intersection approaches.
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| The model is also capable of modeling the presence of manned traffic control. At specific locations where it is advisable or where existing plans call for overriding existing traffic control to implement manned control, the model will use actuated signal timings that reflect the presence of traffic guides. At locations where a special traffic control strategy (continuous left turns, contraflow lanes) is used, the strategy is modeled explicitly. A list that includes the total number of intersections modeled that are unsignalized, signalized, or manned by response personnel is noted in Appendix K.
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| 4.4 Simulation and Capacity Estimation Chapter 6 of the HCM 2016 is entitled, HCM and Alternative Analysis Tools. The chapter discusses the use of alternative tools such as simulation modeling to evaluate the operational performance of highway networks. Among the reasons cited in Chapter 6 to consider using simulation as an alternative analysis tool is:
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| The system under study involves a group of different facilities or travel modes with mutual interactions involving several HCM chapters. Alternative tools are able to analyze these facilities as a single system.
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| This statement succinctly describes the analyses required to determine traffic operations across an area encompassing a study area operating under evacuation conditions. The model utilized for this study, DYNEV II is further described in Appendix C. It is essential to recognize that simulation models do not replicate the methodology and procedures of the HCM 2016 - they replace these procedures by describing the complex interactions of traffic flow and computing Measures of Effectiveness (MOE) detailing the operational performance of traffic over time and by location. The DYNEV II simulation model includes some HCM 2016 procedures only for the purpose of estimating capacity.
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| All simulation models must be calibrated properly with field observations that quantify the performance parameters applicable to the analysis network. Two of the most important of these are: (1) FFS; and (2) saturation headway, hsat. The first of these is estimated by direct North Anna Power Station 48 KLD Engineering, P.C.
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| observation during the road survey; the second is estimated using the concepts of the HCM, as described earlier. These parameters are listed in Appendix K, for each network link.
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| It is important to note that simulation represents a mathematical representation of an assumed set of conditions using the best available knowledge and understanding of traffic flow and available inputs. Simulation should not be assumed to be a prediction of what will happen under any event because a real evacuation can be impacted by an infinite number of things -
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| many of which will differ from these test cases - and many others cannot be taken into account with the tools available.
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| 4.5 Boundary Conditions As illustrated in Figure 12 and in Appendix K, the linknode analysis network used for this study is finite. The analysis network extends well beyond the 15mile radial study area in some locations in order to model intersections with other major evacuation routes beyond the study area. However, the network does have an end at the destination (exit) nodes as discussed in Appendix C. Beyond these destination nodes, there may be signalized intersections or merge points that impact the capacity of the evacuation routes leaving the study area. Rather than neglect these boundary conditions, this study assumes a 25% reduction in capacity on two lane roads (Section 4.3.1 above) and multilane highways (Section 4.3.2 above). The 25%
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| reduction in capacity is based on the prevalence of actuated traffic signals in the study area and the fact that the evacuating traffic volume (main street) will be more significant than the competing (side street) traffic volume at any downstream signalized intersections, thereby warranting a more significant percentage (75% in this case) of the signal green time. There is no reduction in capacity for freeways due to boundary conditions.
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| Volume, vph Capacity Drop Qmax R Qmax Qs Density, vpm Flow Regimes Speed, mph Free Forced vf R vc Density, vpm kf kopt kj ks Figure 41. Fundamental Diagrams North Anna Power Station 410 KLD Engineering, P.C.
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| 5 ESTIMATION OF TRIP GENERATION TIME Federal guidance (see NUREG/CR7002, Rev. 1) recommends that the ETE study estimate the distributions of elapsed times associated with mobilization activities undertaken by the public to prepare for the evacuation trip. The elapsed time associated with each activity is represented as a statistical distribution reflecting differences between members of the public.
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| The quantification of these activitybased distributions relies largely on the results of the demographic survey. We define the sum of these distributions of elapsed times as the Trip Generation Time Distribution.
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| ===5.1 Background===
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| In general, an accident at a nuclear power plant is characterized by the following Emergency Classification Levels (see Section C of Part IV of Appendix E of 10 CFR 50 for details):
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| : 1. Unusual Event
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| : 2. Alert
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| : 3. Site Area Emergency
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| : 4. General Emergency At each level, the Federal guidelines specify a set of Actions to be undertaken by the licensee, and by the state and local offsite agencies. As a Planning Basis, we will adopt a conservative posture, in accordance with Section 1.2 of NUREG/CR7002, Rev. 1, that a rapidly escalating accident at the plant wherein evacuation is ordered promptly, and no early protective actions have been implemented will be considered in calculating the Trip Generation Time. We will assume:
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| : 1. The ATE will be announced coincident with the siren notification.
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| : 2. Mobilization of the general population will commence within 15 minutes after the siren notification.
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| : 3. ETE are measured relative to the ATE.
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| We emphasize that the adoption of this planning basis is not a representation that these events will occur within the indicated time frame. Rather, these assumptions are necessary in order to:
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| : 1. Establish a temporal framework for estimating the Trip Generation distribution in the format recommended in Section 2.13 of NUREG/CR6863.
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| : 2. Identify temporal points of reference that uniquely define "Clear Time" and ETE.
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| It is likely that a longer time will elapse between the various classes of an emergency. For example, suppose one hour elapses from the siren alert to the ATE. In this case, it is reasonable to expect some degree of spontaneous evacuation by the public during this onehour period. As a result, the population within the EPZ will be lower when the ATE is announced, than at the time of the siren alert. In addition, many will engage in preparation activities to evacuate, in anticipation that an advisory will be broadcasted. Thus, the time needed to complete the mobilization activities and the number of people remaining to evacuate the EPZ North Anna Power Station 51 KLD Engineering, P.C.
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| after the ATE, will both be somewhat less than the estimates presented in this report.
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| Consequently, the ETE presented in this report are likely to be higher than the actual evacuation time, if this hypothetical situation were to take place.
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| The notification process consists of two events:
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| : 1. Transmitting information using the alert and notification systems (ANS) available within the EPZ (e.g., sirens, tone alerts, EAS broadcasts, loudspeakers).
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| : 2. Receiving and correctly interpreting the information that is transmitted.
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| The population within the EPZ is dispersed over an area of approximately 381 square miles and is engaged in a wide variety of activities. It must be anticipated that some time will elapse between the transmission and receipt of the information advising the public of an event.
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| The amount of elapsed time will vary from one individual to the next depending on where that person is, what that person is doing, and related factors. Furthermore, some persons who will be directly involved with the evacuation process may be outside the EPZ at the time the emergency is declared. These people may be commuters, shoppers and other travelers who reside within the EPZ and who will return to join the other household members upon receiving notification of an emergency.
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| As indicated in Section 2.13 of NUREG/CR6863, the estimated elapsed times for the receipt of notification can be expressed as a distribution reflecting the different notification times for different people within, and outside, the EPZ. By using time distributions, it is also possible to distinguish between different population groups and different dayofweek and timeofday scenarios, so that accurate ETE may be computed.
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| For example, people at home or at work within the EPZ will be notified by siren, and/or tone alert and/or radio (if available). Those well outside the EPZ will be notified by telephone, radio, TV and wordofmouth, with potentially longer time lags. Furthermore, the spatial distribution of the EPZ population will differ with time of day - families will be united in the evenings but dispersed during the day. In this respect, weekends will differ from weekdays.
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| As indicated in Section 4.1 of NUREG/CR7002, Rev. 1, the information required to compute trip generation times is typically obtained from a demographic survey of EPZ residents. Such a survey was conducted in support of this ETE study. Appendix F discusses the survey sampling plan, documents the survey instrument utilized, and provides the survey results. It is important to note that the shape and duration of the evacuation trip mobilization distribution is important at sites where traffic congestion is not expected to cause the evacuation time estimate to extend in time well beyond the trip generation period. The remaining discussion will focus on the application of the trip generation data obtained from the demographic survey to the development of the ETE documented in this report.
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| 5.2 Fundamental Considerations The environment leading up to the time that people begin their evacuation trips consists of a sequence of events and activities. Each event (other than the first) occurs at an instant in time and is the outcome of an activity.
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| Activities are undertaken over a period of time. Activities may be in "series" (i.e., to undertake an activity implies the completion of all preceding events) or may be in parallel (two or more activities may take place over the same period of time). Activities conducted in series are functionally dependent on the completion of prior activities; activities conducted in parallel are functionally independent of one another. The relevant events associated with the public's preparation for evacuation are:
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| Event Number Event Description 1 Notification 2 Awareness of Situation 3 Depart Work 4 Arrive Home 5 Depart on Evacuation Trip Associated with each sequence of events are one or more activities, as outlined in Table 51:
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| These relationships are shown graphically in Figure 51.
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| An Event is a state that exists at a point in time (e.g., depart work, arrive home)
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| An Activity is a process that takes place over some elapsed time (e.g., prepare to leave work, travel home)
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| As such, a completed Activity changes the state of an individual (i.e., the activity, travel home changes the state from depart work to arrive home). Therefore, an Activity can be described as an Event Sequence; the elapsed times to perform an event sequence vary from one person to the next and are described as statistical distributions on the following pages.
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| An employee who lives outside the EPZ will follow sequence (c) of Figure 51. A household within the EPZ that has one or more commuters at work and will await their return before beginning the evacuation trip will follow the first sequence of Figure 51(a). A household within the EPZ that has no commuters at work, or that will not await the return of any commuters, will follow the second sequence of Figure 51(a), regardless of day of week or time of day.
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| Households with no commuters on weekends or in the evening/nighttime, will follow the applicable sequence in Figure 51(b). Transients will always follow one of the sequences of Figure 51(b). Some transients away from their residence could elect to evacuate immediately without returning to the residence, as indicated in the second sequence.
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| It is seen from Figure 51, that the Trip Generation time (i.e., the total elapsed time from Event 1 to Event 5) depends on the scenario and will vary from one household to the next.
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| Furthermore, Event 5 depends, in a complicated way, on the time distributions of all activities preceding that event. That is, to estimate the time distribution of Event 5, we must obtain estimates of the time distributions of all preceding events. For this study, we adopt the conservative posture that all activities will occur in sequence.
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| In some cases, assuming certain events occur strictly sequential (for instance, commuter returning home before beginning preparation to leave, or removing snow only after the preparation to leave) can result in rather conservative (that is, longer) estimates of mobilization times. It is reasonable to expect that at least some parts of these events will overlap for many households, but that assumption is not made in this study.
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| 5.3 Estimated Time Distributions of Activities Preceding Event 5 The time distribution of an event is obtained by "summing" the time distributions of all prior contributing activities. (This "summing" process is quite different than an algebraic sum since it is performed on distributions - not scalar numbers).
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| Time Distribution No. 1, Notification Process: Activity 1 2 Federal regulations (10CFR50 Appendix E, Item IV.D.3) stipulate, [t]he design objective of the prompt public alert and notification system shall be to have the capability to essentially complete the initial alerting and initiate notification of the public within the plume exposure pathway EPZ within about 15 minutes. Furthermore, Part V, Section B.1, item 3 of the 2019 Federal Emergency Management Agency (FEMA) Radiological Emergency Preparedness Program Manual states that Notification methods will be established to ensure coverage within 45 minutes of essentially 100% of the population Given the federal regulations and guidance, and the presence of sirens within the EPZ, it is assumed that 100% of the population in the EPZ can be notified within 45 minutes. The notification distribution is provided in Table 52. The distribution is plotted in Figure 52.
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| Distribution No. 2, Prepare to Leave Work: Activity 2 3 It is reasonable to expect that the vast majority of business enterprises within the EPZ will elect to shut down following notification and most employees would leave work quickly. Commuters, who work outside the EPZ could, in all probability, also leave quickly since facilities outside the EPZ would remain open and other personnel would remain. Personnel or farmers responsible for equipment/livestock would require additional time to secure their facility. The distribution of Activity 2 3 shown in Table 53 reflects data obtained by the demographic survey. This distribution is also applicable for residents to leave stores, restaurants, parks and other locations within the EPZ. This distribution is plotted in Figure 52.
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| Distribution No. 3, Travel Home: Activity 3 4 These data are provided directly by those households which responded to the demographic survey. This distribution is plotted in Figure 52 and listed in Table 54.
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| Distribution No. 4, Prepare to Leave Home: Activity 2, 4 5 These data are provided directly by those households which responded to the demographic survey. This distribution is plotted in Figure 52 and listed in Table 55.
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| Distribution No. 5, Snow Clearance Time Distribution Inclement weather scenarios involving snowfall must address the time lags associated with snow clearance. It is assumed that snow equipment is mobilized and deployed during the snowfall to maintain passable roads. The general consensus is that the snowplowing efforts are generally successful for all but the most extreme blizzards when the rate of snow accumulation exceeds that of snow clearance over a period of many hours.
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| Consequently, it is reasonable to assume that the highway system will remain passable - albeit at a lower capacity - under the vast majority of snow conditions. Nevertheless, for the vehicles to gain access to the highway system, it may be necessary for driveways and employee parking lots to be cleared to the extent needed to permit vehicles to gain access to the roadways.
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| These clearance activities take time; this time must be incorporated into the trip generation time distributions. These data are provided by those households which responded to the demographic survey. This distribution is plotted in Figure 52 and listed in Table 56.
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| 5.4 Calculation of Trip Generation Time Distribution The time distributions for each of the mobilization activities presented herein must be combined to form the appropriate Trip Generation Distributions. As discussed above, this study assumes that the stated events take place in sequence such that all preceding events must be completed before the current event can occur. For example, if a household awaits the return of a commuter, the worktohome trip (Activity 3 4) must precede Activity 4 5.
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| To calculate the time distribution of an event that is dependent on two sequential activities, it is necessary to sum the distributions associated with these prior activities. The distribution summing algorithm is applied repeatedly as shown to form the required distribution. As an outcome of this procedure, new time distributions are formed; we assign letter designations to these intermediate distributions to describe the procedure. Table 57 presents the summing procedure to arrive at each designated distribution.
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| Table 58 presents a description of each of the final trip generation distributions achieved after the summing process is completed.
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| 5.4.1 Statistical Outliers As discussed in the footnote to Table 53, some portion of the survey respondents answer Decline to State to some questions or choose to not respond to a question. The mobilization activity distributions are based upon actual responses. But, it is the nature of surveys that a few numeric responses are inconsistent with the overall pattern of results. An example would be a case in which for 500 responses, almost all of them estimate less than two hours for a given answer, but three people say four hours and four people say six or more hours.
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| These outliers must be considered: are they valid responses, or so atypical that they should be dropped from the sample?
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| In assessing outliers, there are three alternates to consider:
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| : 1) Some responses with very long times may be valid, but reflect the reality that the respondent really needs to be classified in a different population subgroup, based upon special needs;
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| : 2) Other responses may be unrealistic (6 hours to return home from commuting distance, or 2 days to prepare the home for departure);
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| : 3) Some high values are representative and plausible, and one must not cut them as part of the consideration of outliers.
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| The issue of course is how to make the decision that a given response or set of responses are to be considered outliers for the component mobilization activities, using a method that objectively quantifies the process.
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| There is considerable statistical literature on the identification and treatment of outliers singly or in groups, much of which assumes the data is normally distributed and some of which uses non parametric methods to avoid that assumption. The literature cites that limited work has been done directly on outliers in sample survey responses.
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| In establishing the overall mobilization time/trip generation distributions, the following principles are used:
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| : 1) It is recognized that the overall trip generation distributions are conservative estimates, because they assume a household will do the mobilization activities sequentially, with no overlap of activities;
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| : 2) The individual mobilization activities (prepare to leave work, travel home, prepare home, clear snow) are reviewed for outliers, and then the overall trip generation distributions are created (see Figure 51, Table 57, and Table 58);
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| : 3) Outliers can be eliminated either because the response reflects a special population (e.g.
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| those with access and/or functional needs, transit dependent) or lack of realism, because the purpose is to estimate trip generation patterns for personal vehicles;
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| : 4) To eliminate outliers, a) the mean and standard deviation of the specific activity are estimated from the responses, b) the median of the same data is estimated, with its position relative to the mean noted, c) the histogram of the data is inspected, and d) all values greater than 3.0 standard deviations are flagged for attention, taking special note of whether there are gaps (categories with zero entries) in the histogram display.
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| In general, only flagged values more than 3 standard deviations from the mean are allowed to be considered outliers, with gaps in the histogram expected.
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| When flagged values are classified as outliers and dropped, steps a to d are repeated.
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| : 5) As a practical matter, even with outliers eliminated by the above, the resultant histogram, viewed as a cumulative distribution, is not a normal distribution. A typical situation that results is shown in Figure 53.
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| : 6) In particular, the cumulative distribution differs from the normal distribution in two key aspects, both very important in loading a network to estimate evacuation times:
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| Most of the real data is to the left of the normal curve above, indicating that the network loads faster for the first 8085% of the vehicles, potentially causing more (and earlier) congestion than otherwise modeled; The last 1015% of the real data tails off slower than the comparable normal curve, indicating that there is significant traffic still loading at later times.
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| Because these two features are important to preserve, it is the histogram of the data that is used to describe the mobilization activities, not a normal curve fit to the data. One could consider other distributions, but using the shape of the actual data curve is unambiguous and preserves these important features;
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| : 7) With the mobilization activities each modeled according to Steps 16, including preserving the features cited in Step 6, the overall (or total) mobilization times are constructed.
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| This is done by using the data sets and distributions under different scenarios (e.g., commuter returning, no commuter returning, no snow or snow in each). In general, these are additive, using weighting based upon the probability distributions of each element; Figure 54 presents the combined trip generation distributions designated A, C, D, E and F. These distributions are presented on the same time scale. (As discussed earlier, the use of strictly additive activities is a conservative approach, because it makes all activities sequential - preparation for departure follows the return of the commuter; snow clearance follows the preparation for departure, and so forth. In practice, it is reasonable that some of these activities are done in parallel, at least to some extent - for instance, preparation to depart begins by a household member at home while the commuter is still on the road.)
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| The mobilization distributions that result are used in their tabular/graphical form as direct inputs to later computations that lead to the ETE.
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| The DYNEV II simulation model is designed to accept varying rates of vehicle trip generation for each origin centroid, expressed in the form of histograms. These histograms, which represent Distributions A, C, D, E and F, properly displaced with respect to one another, are tabulated in Table 59 (Distribution B, Arrive Home, omitted for clarity).
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| The final time period (15) is 600 minutes long. This time period is added to allow the analysis network to clear, in the event congestion persists beyond the trip generation period. Note that there are no trips generated during this final time period.
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| 5.4.2 Staged Evacuation Trip Generation As defined in NUREG/CR7002 Rev. 1, staged evacuation consists of the following:
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| : 1. PAZs comprising the 2Mile Region are advised to evacuate immediately
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| : 2. PAZs comprising regions extending from 2 to 5 miles downwind are advised to shelter inplace while the 2Mile Region is cleared
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| : 3. As vehicles evacuate the 2Mile Region, sheltered people from 2 to 5 miles downwind continue preparation for evacuation
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| : 4. The population sheltering in the 2 to 5Mile Region are advised to begin evacuating when approximately 90% of those originally within the 2Mile Region evacuate across the 2Mile Region boundary
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| : 5. The population in the 5 to 10 mile region (to the EPZ boundary) shelters in place
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| : 6. Noncompliance with the shelter recommendation is the same as the shadow evacuation percentage of 20%
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| Assumptions
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| : 1. The EPZ population in PAZs beyond 5 miles will shelterinplace. A noncompliance voluntary evacuation percentage of 20% is assumed for this population.
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| : 2. The population in the shadow region beyond the EPZ boundary, extending to approximately 15 miles radially from the plant, will react as they do for all nonstaged evacuation scenarios. That is 20% of these households will elect to evacuate with no shelter delay.
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| : 3. The transient population will not be expected to stage their evacuation because of the limited sheltering options available to people who may be at parks, on a beach, or at other venues. Also, notifying the transient population of a staged evacuation would prove difficult.
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| : 4. Employees will also be assumed to evacuate without first sheltering.
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| Procedure
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| : 1. Trip generation for population groups in the 2Mile Region will be as computed based upon the results of the demographic survey and analysis.
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| : 2. Trip generation for the population subject to staged evacuation will be formulated as follows:
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| : a. Identify the 90th percentile evacuation time for the PAZs comprising the 2Mile Region. This value, TScen*, is obtained from simulation results. It will become the North Anna Power Station 58 KLD Engineering, P.C.
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| time at which the region being sheltered will be told to evacuate for each scenario.
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| : b. The resultant trip generation curves for staging are then formed as follows:
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| : i. The nonshelter trip generation curve is followed until a maximum of 20%
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| of the total trips are generated (to account for shelter noncompliance).
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| ii. No additional trips are generated until time TScen*
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| iii. Following time TScen*, the balance of trips are generated:
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| : 1. by stepping up and then following the nonshelter trip generation curve (if TScen* is < max trip generation time) or
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| : 2. by stepping up to 100% (if TScen* is > max trip generation time)
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| : c. Note: This procedure implies that there may be different staged trip generation distributions for different scenarios. NUREG/CR7002, Rev. 1 uses the statement approximately 90 percent as the time to end staging and begin evacuating.
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| The value of TScen* is 2:45 for nonheavy snow scenarios and 4:00 for heavy snow scenarios.
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| : 3. Staged trip generation distributions are created for the following population groups:
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| : a. Residents with returning commuters
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| : b. Residents without returning commuters
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| : c. Residents with returning commuters and heavy snow conditions
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| : d. Residents without returning commuters and heavy snow conditions Figure 55 presents the staged trip generation distributions for both residents with and without returning commuters; the 90th percentile twomile evacuation time is approximately 165 minutes for good weather/rain/light snow and approximately 240 minutes for heavy snow scenarios. At the approximate 90th percentile evacuation time for the 2Mile Region, approximately 20% of the population (who have completed their mobilization activities) advised to shelter has nevertheless departed the area. These people do not comply with the shelter advisory. Also included on the plot are the trip generation distributions for these groups as applied to the regions advised to evacuate immediately.
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| Since the 90th percentile evacuation time occurs before the end of the trip generation time, after the sheltered region is advised to evacuate, the shelter trip generation distribution rises to meet the balance of the nonstaged trip generation distribution. Following time TScen*, the balance of staged evacuation trips that are ready to depart are released within 15 minutes. After TScen*+15, the remainder of evacuation trips are generated in accordance with the unstaged trip generation distribution.
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| Table 510 provides the trip generation histograms for staged evacuation.
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| 5.4.3 Trip Generation for Waterways and Recreational Areas The Commonwealth of Virginia Radiological Emergency Response Plan describes the notification procedures for Lake Anna as follows:
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| : 1. The Department of Conservation and Recreation will warn and evacuate all personnel in the Lake Anna State Park when notified of an emergency affecting the park.
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| : 2. The Department of Wildlife Resources will assist in warning people in boats on Lake Anna in the vicinity of the North Anna Power Station.
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| : 3. The Police Department will assist Game and Inland Fisheries with warning of boaters on Lake Anna.
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| As indicated in Table 52, this study assumes 100% notification in 45 minutes. It is assumed that this timeframe is sufficient for the notification of boaters and that resident boaters will be able to start their evacuation trip within the 5 hour and 15 minute mobilization timeframe for residents with commuters (Table 59).
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| Table 59 indicates that all transients will have mobilized within 2 hours; it is assumed that this allows sufficient time for campers and other transients to return to their vehicles and begin their evacuation trip.
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| North Anna Power Station 510 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 51. Event Sequence for Evacuation Activities Event Sequence Activity Distribution 12 Receive Notification 1 23 Prepare to Leave Work 2 2,3 4 Travel Home 3 2,4 5 Prepare to Leave to Evacuate 4 N/A Snow Clearance 5 Table 52. Time Distribution for Notifying the Public Elapsed Time Percent of (Minutes) Population Notified 0 0%
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| 5 7%
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| 10 13%
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| 15 27%
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| 20 47%
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| 25 66%
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| 30 87%
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| 35 92%
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| 40 97%
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| 45 100%
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| North Anna Power Station 511 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 53. Time Distribution for Employees to Prepare to Leave Work and College Cumulative Cumulative Percent Percent Employees Employees Elapsed Time Leaving Work/ Elapsed Time Leaving Work/
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| (Minutes) College (Minutes) College 0 0% 35 87%
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| 5 31% 40 90%
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| 10 50% 45 93%
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| 15 63% 50 93%
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| 20 72% 55 93%
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| 25 75% 60 99%
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| 30 84% 75 100%
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| NOTE: The survey data was normalized to distribute the "Decline to State" response. That is, the sample was reduced in size to include only those households who responded to this question. The underlying assumption is that the distribution of this activity for the Decline to State responders, if the event takes place, would be the same as those responders who provided estimates.
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| Table 54. Time Distribution for Commuters to Travel Home Cumulative Cumulative Elapsed Time Percent Elapsed Time Percent (Minutes) Returning Home (Minutes) Returning Home 0 0% 45 63%
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| 5 2% 50 70%
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| 10 8% 55 74%
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| 15 14% 60 82%
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| 20 20% 75 88%
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| 25 25% 90 94%
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| 30 38% 105 96%
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| 35 46% 120 100%
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| 40 55%
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| NOTE: The survey data was normalized to distribute the "Decline to State" response North Anna Power Station 512 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 55. Time Distribution for Population to Prepare to Leave Home Cumulative Cumulative Elapsed Time Percent Prepared Elapsed Time Percent Prepared (Minutes) to Leave Home (Minutes) to Leave Home 0 0% 105 79%
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| 15 6% 120 86%
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| 30 25% 135 94%
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| 45 37% 150 96%
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| 60 58% 165 96%
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| 75 72% 180 98%
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| 90 76% 195 100%
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| NOTE: The survey data was normalized to distribute the "Decline to State" response Table 56. Time Distribution for Population to Clear 6"8" of Snow from Driveway Cumulative Percent Elapsed Time Completing Snow (Minutes) Removal 0 24%
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| 15 42%
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| 30 51%
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| 45 61%
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| 60 71%
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| 75 78%
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| 90 81%
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| 105 83%
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| 120 87%
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| 135 95%
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| 150 97%
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| 165 98%
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| 180 100%
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| NOTE: The survey data was normalized to distribute the "Decline to State" response North Anna Power Station 513 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 57. Mapping Distributions to Events Apply Summing Algorithm To: Distribution Obtained Event Defined Distributions 1 and 2 Distribution A Event 3 Distributions A and 3 Distribution B Event 4 Distributions B and 4 Distribution C Event 5 Distributions 1 and 4 Distribution D Event 5 Distributions C and 5 Distribution E Event 5 Distributions D and 5 Distribution F Event 5 Table 58. Description of the Distributions Distribution Description Time distribution of commuters departing place of work/college (Event 3). Also A applies to commuters who work/go to college within the EPZ who live outside, and to Transients within the EPZ.
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| B Time distribution of commuters arriving home (Event 4).
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| Time distribution of residents with commuters who return home, leaving home C
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| to begin the evacuation trip (Event 5).
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| Time distribution of residents without commuters returning home, leaving home D
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| to begin the evacuation trip (Event 5).
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| Time distribution of residents with commuters who return home, leaving home E
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| to begin the evacuation trip, after snow clearance activities (Event 5).
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| Time distribution of residents with no commuters returning home, leaving to F
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| begin the evacuation trip, after snow clearance activities (Event 5).
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| North Anna Power Station 514 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 59. Trip Generation Histograms for the EPZ Population for UnStaged Evacuation Percent of Total Trips Generated Within Indicated Time Period Residents Residents With Residents Residents with Without Commuters Without Time Duration Employees Transients Commuters Commuters Snow Commuters Snow Period (Min) (Distribution A) (Distribution A) (Distribution C) (Distribution D) (Distribution E) (Distribution F) 1 15 5% 5% 0% 0% 0% 0%
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| 2 15 29% 29% 0% 4% 0% 1%
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| 3 30 53% 53% 1% 27% 0% 11%
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| 4 30 12% 12% 10% 32% 4% 19%
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| 5 30 1% 1% 22% 15% 11% 18%
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| 6 30 0% 0% 23% 11% 15% 14%
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| 7 15 0% 0% 9% 5% 8% 7%
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| 8 60 0% 0% 25% 6% 30% 20%
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| 9 15 0% 0% 3% 0% 6% 3%
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| 10 60 0% 0% 6% 0% 17% 6%
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| 11 15 0% 0% 1% 0% 2% 0%
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| 12 60 0% 0% 0% 0% 5% 1%
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| 13 15 0% 0% 0% 0% 1% 0%
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| 14 30 0% 0% 0% 0% 1% 0%
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| 15 600 0% 0% 0% 0% 0% 0%
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| NOTE:
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| Shadow vehicles are loaded onto the analysis network (Figure 12) using Distributions C and E for good weather and snow, respectively.
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| Special event vehicles are loaded using Distribution A.
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| North Anna Power Station 515 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 510. Trip Generation Histograms for the EPZ Population for Staged Evacuation Percent of Total Trips Generated Within Indicated Time Period*
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| Residents Residents Residents with Without Residents With Without Time Duration Commuters Commuters Commuters Snow Commuters Snow Period (Min) (Distribution C) (Distribution D) (Distribution E) (Distribution F) 1 15 0% 0% 0% 0%
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| 2 15 0% 1% 0% 0%
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| 3 30 0% 5% 0% 2%
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| 4 30 2% 7% 1% 4%
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| 5 30 5% 3% 2% 4%
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| 6 30 4% 2% 3% 3%
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| 7 15 2% 1% 2% 1%
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| 8 60 77% 81% 6% 4%
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| 9 15 3% 0% 1% 1%
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| 10 60 6% 0% 76% 80%
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| 11 15 1% 0% 2% 0%
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| 12 60 0% 0% 5% 1%
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| 13 15 0% 0% 1% 0%
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| 14 30 0% 0% 1% 0%
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| 15 600 0% 0% 0% 0%
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| *Trip Generation for Employees and Transients (see Table 59) is the same for UnStaged and Staged Evacuation.
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| North Anna Power Station 516 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| 1 2 3 4 5 Residents Households wait 1
| |
| for Commuters Households without Residents 1 2 5 Commuters and households who do not wait for Commuters (a) Accident occurs during midweek, at midday; year round Residents, Transients 1 2 4 5 Return to residence, away from then evacuate Residence Residents, 1 2 5 Residents at home; Transients at transients evacuate directly Residence (b) Accident occurs during weekend or during the evening2 1 2 3, 5 (c) Employees who live outside the EPZ ACTIVITIES EVENTS 1 2 Receive Notification 1. Notification 2 3 Prepare to Leave Work 2. Aware of situation 2, 3 4 Travel Home 3. Depart work 2, 4 5 Prepare to Leave to Evacuate 4. Arrive home
| |
| : 5. Depart on evacuation trip Activities Consume Time 1
| |
| Applies for evening and weekends also if commuters are at work.
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| 2 Applies throughout the year for transients.
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| Figure 51. Events and Activities Preceding the Evacuation Trip North Anna Power Station 517 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Mobilization Activities 100%
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| Percent of Population Completing Mobilization Activity 80%
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| 60%
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| Notification Prepare to Leave Work Travel Home 40% Prepare Home Time to Clear Snow 20%
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| 0%
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| 0 30 60 90 120 150 180 210 Elapsed Time from Start of Mobilization Activity (min)
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| Figure 52. Time Distributions for Evacuation Mobilization Activities North Anna Power Station 518 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| 100.0%
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| 90.0%
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| 80.0%
| |
| 70.0%
| |
| Cumulative Percentage (%)
| |
| 60.0%
| |
| 50.0%
| |
| 40.0%
| |
| 30.0%
| |
| 20.0%
| |
| 10.0%
| |
| 0.0%
| |
| 112.5 2.5 7.5 12.5 17.5 22.5 27.5 32.5 37.5 42.5 47.5 52.5 57.5 67.5 82.5 97.5 Center of Interval (minutes)
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| Cumulative Data Cumulative Normal Figure 53. Comparison of Data Distribution and Normal Distribution North Anna Power Station 519 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Trip Generation Distributions Employees/Transients Residents with Commuters Residents with no Commuters Res with Comm and Snow Res no Comm with Snow 100 Percent of Population Beginning Evacuation Trip 80 60 40 20 0
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| 0 60 120 180 240 300 360 420 480 Elapsed Time from Evacuation Advisory (min)
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| Figure 54. Comparison of Trip Generation Distributions North Anna Power Station 520 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Staged and Unstaged Evacuation Trip Generation Employees / Transients Residents with Commuters Residents with no Commuters Res with Comm and Snow Res no Comm with Snow Staged Residents with Commuters Staged Residents with no Commuters Staged Residents with Commuters (Snow)
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| Staged Residents with no Commuters (Snow) 100 80
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| % of Population Evacuating 60 40 20 0
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| 0 30 60 90 120 150 180 210 240 270 300 330 360 390 420 450 480 Elapsed Time from Evacuation Advisory (min)
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| Figure 55. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5Mile Region North Anna Power Station 521 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| 6 EVACUATION CASES An evacuation case defines a combination of Evacuation Region and Evacuation Scenario.
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| The definitions of Region and Scenario are as follows:
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| Region A grouping of contiguous evacuating PAZ that forms either a keyhole sector based area, or a circular area within the EPZ, that must be evacuated in response to a radiological emergency.
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| Scenario A combination of circumstances, including time of day, day of week, season, and weather conditions. Scenarios define the number of people in each of the affected population groups and their respective mobilization time distributions.
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| A total of 55 Regions were defined which encompass all the groupings of PAZ considered.
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| These Regions are defined in Table 61. The PAZ configurations are identified in Figure 61.
| |
| Each keyhole sectorbased area consists of a central circle centered at the power plant, and three adjoining sectors, each with a central angle of 22.5 degrees, as per NUREG/CR7002 guidance. The central sector coincides with the wind direction. These sectors extend to 5 miles from the plant (Regions R04 through R15) or to the EPZ boundary (Regions R16 through R42).
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| Regions R01, R02 and R03 represent evacuations of circular areas with radii of 2, 5 and 10 miles, respectively. Regions R43 through R55 are identical to Regions R02 and R04 through R15, respectively; however, those PAZs between 2 miles and 5 miles are staged until 90% of the 2 Mile Region (Region R01) has evacuated.
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| Each PAZ that intersects the keyhole or radius is included in the Region, unless specified otherwise in the Protective Action Recommendation (PAR) determination flowchart. There are instances wherein a small portion (a sliver) of a PAZ is within the keyhole and the population within that small portion is low (500 people or 10% of PAZ population, whichever is less). Under those circumstances, the PAZ would not be included in the Region.
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| A total of 14 Scenarios were evaluated for all Regions. Thus, there are a total of 55 x 14 = 770 evacuation cases. Table 62 is a description of all Scenarios.
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| Each combination of Region and Scenario implies a specific population to be evacuated. The population group and the vehicle estimates presented in Section 3 and Appendix E are peak values. These peak values are adjusted depending on the scenario and region being considered, using scenario and region specific percentages, such that the average population is considered for each evacuation case. The scenario percentages are presented in Table 63, while the regional percentages are provided in Table H1.
| |
| Table 64 presents the vehicle counts for each scenario for an evacuation of Region R03 - the entire EPZ. The percentages presented in Table 63 were determined as follows:
| |
| The number of residents with commuters during the week (when workforce is at its peak) is equal to 34%, which is the product of 73% (the number of households with at least one commuter - see Appendix F, Figure F5) and 46% (the number of households with a commuter that would await the return of the commuter prior to evacuating - see Appendix F, Figure F11).
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| North Anna Power Station 61 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| See assumption 3 in Section 2.3. It is estimated for weekend and evening scenarios that 10% of households with returning commuters will have a commuter at work during those times.
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| It can be argued that the estimate of permanent residents overstates, somewhat, the number of evacuating vehicles, especially during the summer. It is certainly reasonable to assert that some portion of the population would be on vacation during the summer and would travel elsewhere. A rough estimate of this reduction can be obtained as follows:
| |
| Assume 50% of all households vacation for a period over the summer.
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| Assume these vacations, in aggregate, are uniformly dispersed over 10 weeks, i.e., 10 percent of the population is on vacation during each twoweek interval.
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| Assume half of these vacationers leave the area.
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| On this basis, the permanent resident population would be reduced by 5% in the summer and by a lesser amount in the offseason. Given the uncertainty in this estimate, we elected to apply no reductions in permanent resident population for the summer scenarios to account for residents who may be out of the area.
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| Employment is assumed to be at its peak (100%) during the winter, midweek, midday scenarios.
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| Employment is reduced slightly (96%) for summer, midweek, midday scenarios. This is based on the estimation that 50% of the employees commuting into the EPZ will be on vacation for a week during the approximate 12 weeks of summer. It is further estimated that those taking vacation will be uniformly dispersed throughout the summer with approximately 4% of employees vacationing each week. It is further estimated that only 10% of the employees are working in the evenings and during the weekends.
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| Transient activity is estimated to be at its peak (100%) during summer weekends during the day and less (70%) during the week. There are two large campgrounds in the EPZ and several small lodging facilities. As such, transient activity during summer evenings is relatively high at 55%.
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| Transient activity is significantly lower in the winter months - 20% during the week, 30% on weekends, and 15% in the evenings.
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| Seasonal population is estimated to be 100% during summer months and 0% during all other times.
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| As noted in the shadow footnote to Table 63, the shadow percentages are computed using a base of 20% (see assumption 7 in Section 2.2); to include the employees within the shadow region who may choose to evacuate, the voluntary evacuation is multiplied by a scenario specific proportion of employees to permanent residents in the shadow region. For example, using the values provided in Table 64 for Scenario 1, the shadow percentage is computed as follows:
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| 516 20% 1 21%
| |
| 5,217 10,333 One special event (Scenario 13) is considered for the ETE study - the Kinetic Triathlon at Lake Anna State Park. Thus, the special event traffic is 100% evacuated for Scenario 13, and 0% for all other scenarios. This special event includes an additional 249 vehicles being loaded at the North Anna Power Station 62 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| State Park, as shown in the Special Event column in Table 64.
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| It is estimated that summer school enrollment is approximately 10% of enrollment during the regular school year for summer, midweek, midday scenarios. School is not in session during weekends and evenings, thus no buses for schoolchildren are needed under those circumstances. As discussed in the footnote to Table 21, schools are in session during the winter season, midweek, midday and 100% of buses will be needed under those circumstances.
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| Transit vehicles for the transitdependent population and medical facilities are set to 100% for all scenarios as it is assumed that the transitdependent population and medical facility population are present in the EPZ for all scenarios.
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| External traffic is estimated to be 40% during evening scenarios and is 100% for all other scenarios.
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| North Anna Power Station 63 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 61. Description of Evacuation Regions Radial Regions Protection Action Zone (PAZ)
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| Region Description Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R01 2Mile Region N/A x x x x R02 5Mile Region N/A x x x x x x x x x x x x R03 Full EPZ N/A x x x x x x x x x x x x x x x x x x x x x x x x x Evacuate 2Mile Region and Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
| |
| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R04 NNW, N 327 11 x x x x x x R05 NNE 12 33 x x x x x R06 NE 34 56 x x x x x x R07 ENE 57 78 x x x x x R08 E 79 101 x x x x x x R09 ESE, SE 102 146 x x x x x x x R10 SSE 147 168 x x x x x x x R11 S, SSW 169 213 x x x x x x x R12 SW 214 236 x x x x x x x R13 WSW, W 237 281 x x x x x x R14 WNW 282 303 x x x x x x R15 NW 304 326 x x x x x x x Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R16 NNW, N 327 11 x x x x x x x x x R17 NNE 12 33 x x x x x x x x R18 NE 34 56 x x x x x x x x x x R19 ENE 57 78 x x x x x x x x x R20 E 79 101 x x x x x x x x x x x R21 ESE, SE 102 146 x x x x x x x x x x R22 SSE 147 168 x x x x x x x x x x R23 S 169 191 x x x x x x x x x x R24 SSW 192 213 x x x x x x x x x x x R25 SW 214 236 x x x x x x x x x x R26 WSW 237 258 x x x x x x x x x R27 W 259 281 x x x x x x x x x R28 WNW 282 303 x x x x x x x x x x x R29 NW 304 326 x x x x x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station 64 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuate 5Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R30 NNW, N 327 11 x x x x x x x x x x x x x x x R31 NNE 12 33 x x x x x x x x x x x x x x x x R32 NE, ENE 34 78 x x x x x x x x x x x x x x x x R33 E 79 101 x x x x x x x x x x x x x x x x x R34 ESE, SE 102 146 x x x x x x x x x x x x x x x R35 SSE 147 168 x x x x x x x x x x x x x x x R36 S 169 191 x x x x x x x x x x x x x x x R37 SSW 192 213 x x x x x x x x x x x x x x x x R38 SW 214 236 x x x x x x x x x x x x x x x R39 WSW 237 258 x x x x x x x x x x x x x x x R40 W 259 281 x x x x x x x x x x x x x x x R41 WNW 282 303 x x x x x x x x x x x x x x x x x R42 NW 304 326 x x x x x x x x x x x x x x x x Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
| |
| Region From: Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R43 5Mile Region N/A x x x x x x x x x x x x R44 NNW, N 327 11 x x x x x x R45 NNE 12 33 x x x x x R46 NE 34 56 x x x x x x R47 ENE 57 78 x x x x x R48 E 79 101 x x x x x x R49 ESE, SE 102 146 x x x x x x x R50 SSE 147 168 x x x x x x x R51 S, SSW 169 213 x x x x x x x R52 SW 214 236 x x x x x x x R53 WSW, W 237 281 x x x x x x R54 WNW 282 303 x x x x x x R55 NW 304 326 x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station 65 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 62. Evacuation Scenario Definitions Time of 1
| |
| Scenarios Season Day of Week Day Weather Special 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None Midweek, 5 Summer Evening Good None Weekend 6 Winter Midweek Midday Good None Rain/Light 7 Winter Midweek Midday None Snow Heavy 8 Winter Midweek Midday None Snow 9 Winter Weekend Midday Good None Rain/Light 10 Winter Weekend Midday None Snow Heavy 11 Winter Weekend Midday None Snow Midweek, 12 Winter Evening Good None Weekend Special Event: Kinetic 13 Winter Weekend Midday Good Triathlon at Lake Anna State Park Roadway Impact: One 14 Summer Midweek Midday Good Segment Closure on US 522 Northbound 1
| |
| Winter means that school is in session at normal enrollment levels (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).
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| North Anna Power Station 66 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 63. Percent of Population Groups Evacuating for Various Scenarios Households Households With Without External Returning Returning Special Seasonal Medical School Transit Through Scenario Commuters Commuters Employees Transients Shadow Event Transients Facilities Buses Buses Traffic 1 34% 66% 96% 70% 21% 0% 100% 100% 10% 100% 100%
| |
| 2 34% 66% 96% 70% 21% 0% 100% 100% 10% 100% 100%
| |
| 3 3% 97% 10% 100% 20% 0% 100% 100% 0% 100% 100%
| |
| 4 3% 97% 10% 100% 20% 0% 100% 100% 0% 100% 100%
| |
| 5 3% 97% 10% 55% 20% 0% 100% 100% 0% 100% 40%
| |
| 6 34% 66% 100% 20% 21% 0% 0% 100% 100% 100% 100%
| |
| 7 34% 66% 100% 20% 21% 0% 0% 100% 100% 100% 100%
| |
| 8 34% 66% 100% 20% 21% 0% 0% 100% 100% 100% 100%
| |
| 9 3% 97% 10% 30% 20% 0% 0% 100% 0% 100% 100%
| |
| 10 3% 97% 10% 30% 20% 0% 0% 100% 0% 100% 100%
| |
| 11 3% 97% 10% 30% 20% 0% 0% 100% 0% 100% 100%
| |
| 12 3% 97% 10% 15% 20% 0% 0% 100% 0% 100% 40%
| |
| 13 3% 97% 10% 30% 20% 100% 0% 100% 0% 100% 100%
| |
| 14 34% 66% 96% 70% 21% 0% 100% 100% 10% 100% 100%
| |
| Households with Returning Commuters ................................... Households of EPZ residents who await the return of commuters prior to beginning the evacuation trip.
| |
| Households without Returning Commuters .............................. Households of EPZ residents who do not have commuters or will not await the return of commuters prior to beginning the evacuation trip.
| |
| Employees ................................................................................. EPZ employees who live outside the EPZ Transients ................................................................................. People who are in the EPZ at the time of an accident for recreational or other (nonemployment) purposes.
| |
| Shadow ..................................................................................... Residents and employees in the Shadow Region (outside of the EPZ) who will spontaneously decide to relocate during the evacuation. The basis for the values shown is a 20% relocation of shadow residents along with a proportional percentage of shadow employees.
| |
| Special Event ............................................................................. Additional vehicles in the EPZ due to the identified special event.
| |
| Seasonal Transients .................................................................. People who are residents of the EPZ during the summer months but are not included in the permanent resident census numbers.
| |
| School Buses, Medical Facilities, Transit Buses ......................... Vehicleequivalents present on the road during evacuation servicing schools, preschools, medical facilities (except those evacuated in ambulances), and transit dependent people (1 bus is equivalent to 2 passenger vehicles).
| |
| External Through Traffic............................................................ Traffic passing through the study area on interstates/freeways and major arterial roads at the start of the evacuation. This traffic is stopped by access control approximately 2 hours after the evacuation begins.
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| North Anna Power Station 67 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 64. Vehicle Estimates by Scenario2 Households Households With Without Total Returning Returning Special Seasonal Medical School Transit External Scenario Scenario Commuters Commuters Employees Transients Shadow Event Transients Facilities Buses Buses Through Traffic Vehicles 1 5,217 10,333 516 1,688 4,234 0 1,100 0 25 50 16,708 39,871 2 5,217 10,333 516 1,688 4,234 0 1,100 0 25 50 16,708 39,871 3 522 15,028 54 2,412 4,113 0 1,100 0 0 50 16,708 39,987 4 522 15,028 54 2,412 4,113 0 1,100 0 0 50 16,708 39,987 5 522 15,028 54 1,327 4,113 0 1,100 0 0 50 6,683 28,877 6 5,217 10,333 537 482 4,240 0 0 4 252 50 16,708 37,823 7 5,217 10,333 537 482 4,240 0 0 4 252 50 16,708 37,823 8 5,217 10,333 537 482 4,240 0 0 4 252 50 16,708 37,823 9 522 15,028 54 724 4,113 0 0 0 0 50 16,708 37,199 10 522 15,028 54 724 4,113 0 0 0 0 50 16,708 37,199 11 522 15,028 54 724 4,113 0 0 0 0 50 16,708 37,199 12 522 15,028 54 362 4,113 0 0 0 0 50 6,683 26,812 13 522 15,028 54 724 4,113 249 0 0 0 50 16,708 37,448 14 5,217 10,333 516 1,688 4,234 0 1,100 0 25 50 16,708 39,871 2
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| Vehicles estimates are for an evacuation of the entire EPZ (Region R03).
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| Figure 61. PAZs Comprising the NAPS EPZ North Anna Power Station 69 KLD Engineering, P.C.
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| 7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE)
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| This section presents the ETE results of the computer analyses using the DYNEV II System described in Appendices B, C and D. These results cover 55 Evacuation Regions within the NAPS EPZ and the 14 Evacuation Scenarios discussed in Section 6.
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| The ETE for all Evacuation Cases are presented in Table 71 and Table 72. These tables present the estimated times to clear the indicated population percentages from the Evacuation Regions for all Evacuation Scenarios. The ETE of the 2Mile Region in both staged and unstaged regions are presented in Table 73 and Table 74. Table 75 defines the Evacuation Regions considered.
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| The tabulated values of ETE are obtained from the DYNEV II model outputs which are generated at 5minute intervals.
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| 7.1 Voluntary Evacuation and Shadow Evacuation Voluntary evacuees are permanent residents within the EPZ in PAZs for which an Advisory to Evacuate (ATE) has not been issued, yet who elect to evacuate. Shadow evacuation is the voluntary outward movement of some permanent residents from the Shadow Region (outside the EPZ) for whom no protective action recommendation has been issued. Both voluntary and shadow evacuations are assumed to take place over the same time frame as the evacuation from within the impacted Evacuation Region.
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| The ETE for the NAPS EPZ addresses the issue of voluntary evacuees in the manner shown in Figure 71. Within the EPZ, 20% of permanent residents located in PAZs outside of the evacuation region who are not advised to evacuate, are assumed to elect to evacuate. Similarly, it is assumed that 20% of those permanent residents in the Shadow Region will choose to leave the area.
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| Figure 72 presents the area identified as the Shadow Region. This region extends radially from the plant to cover a region between the EPZ boundary and approximately 15 miles. The population and number of evacuating vehicles in the Shadow Region were estimated using the same methodology that was used for permanent residents within the EPZ (see Section 3.1). As discussed in Section 3.2, it is estimated that a total of 36,364 people reside in the Shadow Region; 20% of them would evacuate. See Table 64 for the number of evacuating vehicles from the Shadow Region.
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| Traffic generated within this Shadow Region (including externalexternal traffic), traveling away from the NAPS location, has the potential for impeding evacuating vehicles from within the Evacuation Region. All ETE calculations include this shadow traffic movement.
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| 7.2 Staged Evacuation As defined in NUREG/CR7002, Rev. 1, staged evacuation consists of the following:
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| : 1. PAZs comprising the 2Mile Region are advised to evacuate immediately.
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| : 2. PAZs comprising regions extending from 2 to 5 miles downwind are advised to shelter inplace while the 2Mile Region is cleared.
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| : 3. As vehicles evacuate the 2Mile Region, people from 2 to 5 miles downwind continue preparation for evacuation while they shelter.
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| : 4. The population sheltering in the 2 to 5Mile Region is advised to begin evacuating when approximately 90% of those originally within the 2Mile Region evacuate across the 2 Mile Region boundary.
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| : 5. The population in the 5 to 10 Mile Region (to the EPZ boundary) shelters in place.
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| : 6. Noncompliance with the shelter recommendation is the same as the shadow evacuation percentage of 20%.
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| See Section 5.4.2 for additional information on staged evacuation.
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| 7.3 Patterns of Traffic Congestion during Evacuation Figure 73 through Figure 78 illustrate the patterns of traffic congestion that arise for the case when the entire EPZ (Region R03) is advised to evacuate during the summer, midweek, midday period under good weather conditions (Scenario 1).
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| Traffic congestion, as the term is used here, is defined as Level of Service (LOS) F. LOS F is defined as follows (HCM 2016, page 55):
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| The HCM uses LOS F to define operations that have either broken down (i.e., demand exceeds capacity) or have reached a point that most users would consider unsatisfactory, as described by a specified service measure value (or combination of service measure values). However, analysts may be interested in knowing just how bad the LOS F condition is, particularly for planning applications where different alternatives may be compared. Several measures are available for describing individually, or in combination, the severity of a LOS F condition:
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| * Demandtocapacity ratios describe the extent to which demand exceeds capacity during the analysis period (e.g., by 1%, 15%, etc.);
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| * Duration of LOS F describes how long the condition persists (e.g., 15 min, 1 h, 3 h); and
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| * Spatial extent measures describe the areas affected by LOS F conditions. These include measures such as the back of queue, and the identification of the specific intersection approaches or system elements experiencing LOS F conditions.
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| All highway "links" which experience LOS F are delineated in these figures by a thick red line; all others are lightly indicated. Congestion develops rapidly around concentrations of population and traffic bottlenecks.
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| At 30 minutes after the ATE, evacuees are beginning to mobilize. As shown in Figure 73, moderate traffic (LOS C) develops along US522 northbound from County Road 612 (CR 612) to CR 629 due to traffic volume northbound and evacuees turning onto US522 from CR 612, CR 719 and CR 629. At this time, about 6% of the evacuees have mobilized.
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| At 1 hour after the ATE, Figure 74 shows moderate levels of traffic congestion (LOS C to LOS E) in the town of Louisa in the Shadow Region. Congestion (LOS F) is exhibited on CR 612 westbound from Windway Drive to US522 as evacuees wait at a stop sign to turn onto US522.
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| Significant congestion (LOS F) is exhibited on CR 601 northbound from Hicks Road to State Route 608 (SR 608) due to evacuees leaving Lake Anna State Park and the presence of stopsign control at the intersection of Lawyers Road and SR 608. CR 612 westbound is also congested at the intersection with US522 as local evacuees wait at the stop sign for an acceptable gap to turn onto US522 or continue west on CR 612. US522 northbound from CR 612 to CR 719, SR 618 southeast from SR 701 to SR 680, and SR 613 westbound from US522 to SR 628 are operating at LOS C. At this time, about 29% of evacuees have mobilized.
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| At 1 hour and 30 minutes after the ATE, Figure 75 shows that there is no congestion within 5 miles of the plant. Congestion has cleared on CR 612 westbound. Congestion persists on CR 601 northbound from Hicks Road to CR 606. Traffic has lessened in the Town of Louisa. LOS F conditions now occur on SR 605 eastbound from CR 603 to US1 in the Shadow Region. LOS F conditions also occur at the intersection of SR 715 with US33 beyond the Shadow Region as evacuees try to access US33 at a stopcontrolled intersection.
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| At 2 hours after the ATE, Figure 76 shows that traffic has subsided in the Town of Louisa and all roadways in the EPZ are operating at LOS A or B. Congestion has cleared on State Route 605 eastbound from County Road 603 to US1. LOS F now occurs on CR 603 northbound from the intersection with US1 to SR 605 in the Shadow Region as evacuees encounter a stop sign at US 1 as they try to turn north to evacuate the area. SR 715 southbound is still operating at LOS F southbound at the intersection with US33 beyond the Shadow Region.
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| At 2 hours and 30 minutes after the ATE, Figure 77 shows SR 618 southbound in PAZ 26 and CR 680 southbound in PAZ 24 are the only roads in the EPZ operating at LOS B; all other roads in the EPZ are operating at LOS A at this time. Congestion persists on SR 715 southbound at the intersection with US33.
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| Figure 78 shows the last remnants of congestion at 3 hours after the ATE beyond the Shadow Region at the intersection of US33 and SR 715. This congestion clears 55 minutes later at 3 hours and 55 minutes after the ATE.
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| 7.4 Evacuation Rates Evacuation is a continuous process, as implied by Figure 79 through Figure 722. These figures display the rate at which traffic flows out of the indicated areas for the case of an evacuation of the full EPZ (Region R03) under the indicated conditions. One figure is presented for each scenario considered.
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| As indicated in Figure 79 through Figure 722, there is typically a long "tail" to these distributions. Vehicles begin to evacuate an area slowly at first, as people respond to the ATE at different rates. Then traffic demand builds rapidly (slopes of curves increase). When the system becomes congested, traffic exits the EPZ at rates somewhat below capacity until some evacuation routes have cleared. As more routes clear, the aggregate rate of egress slows since many vehicles have already left the EPZ. Towards the end of the process, relatively few evacuation routes service the remaining demand.
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| This decline in aggregate flow rate, towards the end of the process, is characterized by these curves flattening and gradually becoming horizontal. Ideally, it would be desirable to fully saturate all evacuation routes equally so that all will service traffic near capacity levels and all will clear at the same time. For this ideal situation, all curves would retain the same slope until the end - thus minimizing evacuation time. In reality, this ideal is generally unattainable reflecting the spatial variation in population density, mobilization rates and in highway capacity over the EPZ.
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| 7.5 Evacuation Time Estimate Results Table 71 and Table 72 present the ETE values for all 55 Evacuation Regions and all 14 Evacuation Scenarios. Table 73 and Table 74 present the ETE values for the 2Mile Region for both staged and unstaged keyhole regions downwind to 5 miles.
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| The tables are organized as follows:
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| Table Contents The ETE represents the elapsed time required for 90% of the 71 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.
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| The ETE represents the elapsed time required for 100% of the 72 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.
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| The ETE represents the elapsed time required for 90% of the population within the 2Mile Region, to evacuate from the 2Mile 73 Region with both Concurrent and Staged Evacuations of additional PAZs downwind in the keyhole Region.
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| The ETE represents the elapsed time required for 100% of the population within the 2Mile Region, to evacuate from the 2Mile 74 Region with both Concurrent and Staged Evacuations of additional PAZs downwind in the keyhole Region.
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| The animation snapshots described in Section 73 above reflect the ETE statistics for the concurrent (unstaged) evacuation scenarios and regions, which are displayed in Figure 73 through Figure 78. There is minimal traffic congestion within the EPZ, which results in 90th and 100th percentile ETE values which closely parallel mobilization time. Most of the congestion is located in PAZs 15, 16, 17, 18, 24, and 26 which are beyond the 2Mile Region; this is reflected in the ETE statistics:
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| The average 90th percentile ETE for Region R01 (2Mile Region), R02 (5Mile Region), and Region R03 (Full EPZ) are 2:50, 2:57 and 3:06. The less than 10 minute difference in ETE between these regions is indicative of minimal traffic congestion in the EPZ as it takes less than 10 minutes to travel from the 2mile boundary to the 5mile boundary and from the 5mile boundary to the 10mile boundary at free flow speed on the evacuation routes.
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| The 90th percentile ETE for weekday scenarios are approximately 30 minutes longer, on average, than weekend scenarios. As shown in Figure 54, 90% of residents with commuters mobilize in about 225 minutes, whereas about 90% of residents with no commuters mobilize in about 150 minutes. These factors lead to 90% of the population clearing the EPZ sooner in the weekend scenario as most commuters are home on the weekends and follow the residents with no commuters mobilization time.
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| The 100th percentile ETE for all regions range from 5:15 to 5:25 for all nonheavy snow scenarios and between 7:00 and 7:10 for all heavy snow scenarios. This reflects the time needed to mobilize (5 hours and 15 minutes in good weather and rain/light snow, and 7 hours in heavy snow) plus 5 or 10 minutes travel time to the EPZ boundary - see Section 5.
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| Comparison of Scenarios 9 and 13 in Table 71 and Table 72 indicates that the special event, the Kinetic Triathlon at Lake Anna State Park (see Section 3.8), has no impact on the ETE at the 90th or 100th percentile. The results indicate there is sufficient reserve roadway capacity to accommodate the additional special event vehicles.
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| Comparison of Scenarios 1 and 14 in Table 71 indicates that the roadway closure - one segment of US522 northbound from CR612 to CR719 - increases the 90th percentile by at most 5 minutes and has no effect on the 100th percentile ETE - not a significant impact. US522 experiences moderate traffic congestion, but there is sufficient reserve capacity on CR612 to service the additional evacuating traffic demand diverted from US522.
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| The results of the roadway impact scenario indicate that events such as adverse weather or traffic accidents which close a segment major evacuation route, could impact ETE. State and local police could consider traffic management tactics such as using the shoulder of the roadway as a travel lane or rerouting of traffic along other evacuation routes to avoid overwhelming any of the major evacuation routes.
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| 7.6 Staged Evacuation Results Table 73 and Table 74 present a comparison of the ETE compiled for the concurrent (un staged) and staged evacuation studies. Note that Regions R43 through R55 are the same geographic areas as Regions R02 and R04 through R15, respectively. The times shown in Table 73 and Table 74 are when the 2Mile Region is 90% clear and 100% clear, respectively.
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| The objective of a staged evacuation strategy is to ensure the ETE for the 2Mile Region is not significantly increased (30 minutes or 25%, whichever is less) when evacuating areas beyond 2 Miles. Additionally, staged evacuation should not significantly increase the ETE for people evacuating beyond 2Miles. In all cases, as shown in Table 73 and Table 74, the 90th and 100th percentile ETE for the 2Mile Region is unchanged when evacuating areas beyond 2Miles.
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| These results indicate that when an evacuation out to the 5Mile Region occurs, the congestion beyond the 2Mile Region does not extend upstream to the extent that it penetrates within the 2mile region enough to impact the ETE of the 2mile region. Evacuees from within the 2Mile Region are not impacted by those evacuating beyond 2 miles out to 5 miles. Therefore, staging the evacuation provides no benefit to evacuees from within the 2Mile Region.
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| To determine the effect of staged evacuation on residents beyond the 2Mile Region, the ETE for Regions R02 and R04 through R15 are compared to Regions R43 through R55, respectively, in Table 71 and Table 72. A comparison of ETE between these similar regions reveals that staging increases the ETE for those in the 2 to 5Mile Region by at most 1 hour and 10 minutes for the 90th percentile and has no impact on the 100th percentile.
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| The increase in the 90th percentile ETE is due to the evacuating vehicles, beyond the 2Mile Region, sheltering and delaying the start of their evacuation. As shown in Figure 55, staging the evacuation causes a significant spike (sharp increase) in mobilization (tripgeneration rate) of evacuating vehicles. Nearly 80% of the evacuating vehicles between 2 and 5 miles who have sheltered in place while residents within 2 miles evacuated, begin their evacuation trip over a 15minute timeframe. This spike oversaturates evacuation routes, which increases the traffic congestion and prolongs ETE.
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| In summary, staging evacuation provides no benefit to evacuees in the 2Mile Region while adversely impacting many evacuees located beyond 2Miles Region from the plant. Based on the guidance in NUREG0654, Supplement 3, this analysis would result in staged evacuation not being implemented for this site.
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| 7.7 Guidance on Using ETE Tables The user first determines the percentile of population for which the ETE is sought (NRC guidance calls for the 90th percentile). The applicable value of ETE within the chosen table may then be identified using the following procedure:
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| : 1. Identify the applicable Scenario:
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| * Season Summer Winter (also Autumn and Spring)
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| * Day of Week Midweek Weekend
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| * Time of Day Midday Evening
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| * Weather Condition Good Weather Rain/Light Snow Heavy Snow
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| * Special Event Kinetic Triathlon at Lake Anna State Park
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| * Roadway Impact One Segment Closure on US522 Northbound
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| * Evacuation Staging No, Staged Evacuation is not considered Yes, Staged Evacuation is considered While these Scenarios are designed, in aggregate, to represent conditions throughout the year, some further clarification is warranted:
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| * The conditions of a summer evening (either midweek or weekend) and rain are not explicitly identified in the tables. For these conditions, Scenarios (2) and (4) apply.
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| * The conditions of a winter evening (either midweek or weekend) and rain/light snow are not explicitly identified in the tables. For these conditions, Scenarios (7) and (10) for rain/light snow apply.
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| * The conditions of a winter evening (either midweek or weekend) and heavy snow are not explicitly identified in the tables. For these conditions, Scenarios (8) and (11) for heavy snow apply.
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| * The seasons are defined as follows:
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| Summer assumes public school is in session at summer school enrollment levels (lower than normal enrollment).
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| Winter (includes Spring and Autumn) considers that public schools are in session at normal enrollment levels.
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| * Time of Day: Midday implies the time over which most commuters are at work or North Anna Power Station 77 KLD Engineering, P.C.
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| are travelling to/from work.
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| : 2. With the desired percentile ETE and Scenario identified, now identify the Evacuation Region:
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| * Determine the projected azimuth direction of the plume (coincident with the wind direction). This direction is expressed in terms of compass orientation: from N, NNE, NE,
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| * Determine the distance that the Evacuation Region will extend from the nuclear power plant. The applicable distances and their associated candidate Regions are given below:
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| 2 Miles (Region R01)
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| To 5 Miles (Regions R02, R04 through R15, R43 through R55 for staged evacuation)
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| To EPZ Boundary (Regions R03, R16 through R42)
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| * Enter Table 75 and identify the applicable group of candidate Regions based on the distance that the selected Region extends from the plant. Select the Evacuation Region identifier in that row, based on the azimuth direction of the plume, from the first column of the table.
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| : 3. Determine the ETE Table based on the percentile selected. Then, for the Scenario identified in Step 1 and the Region identified in Step 2, proceed as follows:
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| * The columns of Table 71 through Table 74 are labeled with the Scenario numbers.
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| Identify the proper column in the selected table using the Scenario number defined in Step 1.
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| * Identify the row in this table that provides ETE values for the Region identified in Step 2.
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| * The unique data cell defined by the column and row so determined contains the desired value of ETE expressed in Hours:Minutes.
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| Example It is desired to identify the ETE for the following conditions:
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| * Sunday, August 10th at 4:00 AM.
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| * It is raining.
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| * Wind direction is from the northeast (NE).
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| * Wind speed is such that the distance to be evacuated is judged to be a 2Mile Region and downwind to 10 miles (to EPZ boundary).
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| * The desired ETE is that value needed to evacuate 90% of the population from within the impacted Region.
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| * A staged evacuation is not desired.
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| Table 71 is applicable because the 90th percentile ETE is desired. Proceed as follows:
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| : 1. Identify the Scenario as summer, weekend, evening and raining. Entering Table 71, it is seen that there is no match for these descriptors. However, the clarification given above assigns this combination of circumstances to Scenario 4.
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| : 2. Enter Table 75 and locate the Region described as Evacuate 2Mile Region and Downwind to the EPZ Boundary for wind direction from the NE and read Region R18 in the first column of that row.
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| : 3. Enter Table 71 to locate the data cell containing the value of ETE for Scenario 4 and Region R18. This data cell is in column (4) and in the row for Region R18; it contains the ETE value of 2:35.
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| Table 71. Time to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R02 2:55 2:55 2:30 2:30 2:30 3:10 3:10 4:15 2:40 2:40 3:50 2:40 2:40 2:55 R03 3:10 3:10 2:40 2:40 2:40 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:10 Evacuate 2Mile Region and Downwind to 5 Miles R04 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R05 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R06 2:55 2:55 2:35 2:35 2:35 3:05 3:05 4:10 2:40 2:40 3:55 2:40 2:40 2:55 R07 2:50 2:50 2:30 2:30 2:30 3:00 3:00 4:05 2:40 2:40 3:50 2:40 2:40 2:50 R08 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R09 2:45 2:45 2:25 2:25 2:30 3:00 3:05 4:05 2:35 2:35 3:50 2:40 2:35 2:45 R10 2:50 2:50 2:25 2:25 2:30 3:05 3:05 4:10 2:35 2:35 3:50 2:40 2:35 2:50 R11 2:50 2:55 2:25 2:25 2:30 3:05 3:05 4:10 2:35 2:35 3:50 2:40 2:35 2:55 R12 3:00 3:00 2:30 2:30 2:35 3:10 3:10 4:15 2:40 2:40 3:50 2:40 2:40 3:00 R13 3:00 3:00 2:30 2:35 2:35 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 3:00 R14 2:50 2:50 2:30 2:30 2:30 3:05 3:05 4:10 2:40 2:40 3:50 2:40 2:40 2:50 R15 2:55 2:55 2:30 2:30 2:30 3:05 3:10 4:15 2:40 2:40 3:50 2:40 2:40 2:55 Evacuate 2Mile Region and Downwind to the EPZ Boundary R16 3:10 3:10 2:45 2:45 2:45 3:15 3:15 4:25 2:45 2:50 4:00 2:50 2:45 3:10 R17 3:10 3:10 2:40 2:45 2:45 3:15 3:15 4:20 2:45 2:45 4:00 2:45 2:45 3:10 R18 3:05 3:05 2:35 2:35 2:40 3:10 3:10 4:20 2:45 2:45 3:55 2:45 2:45 3:05 R19 3:05 3:05 2:35 2:35 2:40 3:10 3:10 4:15 2:40 2:45 3:55 2:45 2:40 3:05 R20 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R21 3:00 3:00 2:30 2:30 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R22 3:00 3:00 2:30 2:30 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 North Anna Power Station 710 KLD Engineering, P.C.
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R23 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:45 2:40 3:05 R24 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R25 3:05 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R26 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:10 R27 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:20 2:45 2:45 3:55 2:45 2:45 3:10 R28 3:15 3:15 2:40 2:45 2:45 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:15 R29 3:10 3:15 2:40 2:45 2:45 3:20 3:20 4:25 2:45 2:45 4:00 2:45 2:45 3:10 Evacuate 5Mile Region and Downwind to the EPZ Boundary R30 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:25 2:45 2:45 3:55 2:45 2:45 3:05 R31 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:45 2:45 3:55 2:45 2:45 3:05 R32 3:00 3:05 2:35 2:35 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R33 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R34 3:00 3:00 2:30 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R35 3:00 3:00 2:30 2:35 2:35 3:10 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:00 R36 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R37 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:20 2:40 2:45 3:55 2:45 2:40 3:05 R38 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R39 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R40 3:05 3:05 2:35 2:35 2:35 3:15 3:15 4:20 2:40 2:40 3:55 2:40 2:40 3:05 R41 3:10 3:10 2:40 2:40 2:40 3:15 3:15 4:25 2:45 2:45 4:00 2:45 2:45 3:10 R42 3:05 3:05 2:35 2:35 2:40 3:15 3:15 4:25 2:40 2:45 3:55 2:45 2:40 3:05 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 3:40 3:40 3:35 3:35 3:40 3:40 3:45 5:00 3:40 3:40 4:55 3:40 3:40 3:40 R44 3:30 3:30 3:30 3:30 3:30 3:35 3:35 4:50 3:35 3:35 4:50 3:35 3:35 3:30 R45 3:25 3:30 3:25 3:25 3:25 3:35 3:35 4:45 3:30 3:30 4:45 3:30 3:30 3:30 R46 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 North Anna Power Station 711 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R47 3:30 3:30 3:30 3:30 3:30 3:35 3:35 4:50 3:35 3:35 4:50 3:35 3:35 3:30 R48 3:35 3:35 3:30 3:30 3:30 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R49 3:35 3:35 3:30 3:30 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:40 3:35 3:35 R50 3:35 3:35 3:30 3:30 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 R51 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 R52 3:40 3:40 3:35 3:35 3:35 3:40 3:40 4:55 3:40 3:40 4:55 3:40 3:40 3:40 R53 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R54 3:35 3:35 3:30 3:30 3:30 3:40 3:40 4:55 3:35 3:35 4:55 3:35 3:35 3:35 R55 3:35 3:35 3:35 3:35 3:35 3:40 3:40 4:55 3:35 3:40 4:55 3:40 3:35 3:35 North Anna Power Station 712 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 72. Time to Clear the Indicated Area of 100 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R02 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R03 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Evacuate 2Mile Region and Downwind to 5 Miles R04 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R05 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R06 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R07 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R08 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R09 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R10 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R11 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R12 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R13 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R14 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R15 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 Evacuate 2Mile Region and Downwind to the EPZ Boundary R16 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R17 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R18 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R19 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R20 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R21 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R22 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 North Anna Power Station 713 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R23 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R24 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R25 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R26 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R27 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R28 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R29 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Evacuate 5Mile Region and Downwind to the EPZ Boundary R30 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R31 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R32 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R33 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R34 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R35 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R36 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R37 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R38 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R39 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R40 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R41 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 R42 5:25 5:25 5:25 5:25 5:25 5:25 5:25 7:10 5:25 5:25 7:10 5:25 5:25 5:25 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R44 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R45 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R46 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 North Anna Power Station 714 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R47 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R48 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R49 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R50 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R51 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R52 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R53 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R54 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 R55 5:20 5:20 5:20 5:20 5:20 5:20 5:20 7:05 5:20 5:20 7:05 5:20 5:20 5:20 North Anna Power Station 715 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 73. Time to Clear 90 Percent of the 2Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2Mile Region and 5Mile Region R01 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R02 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R05 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R06 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R07 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R08 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R09 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R10 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R11 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R12 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R13 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R14 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R15 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R44 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R45 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R46 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R47 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R48 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R49 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R50 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 North Anna Power Station 716 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R51 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R52 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R53 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R54 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 R55 2:45 2:45 2:25 2:25 2:30 2:55 2:55 4:00 2:35 2:35 3:50 2:40 2:35 2:45 North Anna Power Station 717 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 74. Time to Clear 100 Percent of the 2Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2Mile Region and 5Mile Region R01 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R02 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R05 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R06 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R07 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R08 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R09 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R10 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R11 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R12 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R13 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R14 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R15 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles R43 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R44 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R45 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R46 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R47 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R48 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R49 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R50 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 North Anna Power Station 718 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)
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| Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact R51 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R52 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R53 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R54 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 R55 5:15 5:20 5:15 5:15 5:15 5:15 5:15 7:00 5:15 5:15 7:00 5:15 5:15 5:15 North Anna Power Station 719 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table 75. Description of Evacuation Regions Radial Regions Protection Action Zone (PAZ)
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| Region Description Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R01 2Mile Region N/A x x x x R02 5Mile Region N/A x x x x x x x x x x x x R03 Full EPZ N/A x x x x x x x x x x x x x x x x x x x x x x x x x Evacuate 2Mile Region and Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R04 NNW, N 327 11 x x x x x x R05 NNE 12 33 x x x x x R06 NE 34 56 x x x x x x R07 ENE 57 78 x x x x x R08 E 79 101 x x x x x x R09 ESE, SE 102 146 x x x x x x x R10 SSE 147 168 x x x x x x x R11 S, SSW 169 213 x x x x x x x R12 SW 214 236 x x x x x x x R13 WSW, W 237 281 x x x x x x R14 WNW 282 303 x x x x x x R15 NW 304 326 x x x x x x x Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R16 NNW, N 327 11 x x x x x x x x x R17 NNE 12 33 x x x x x x x x R18 NE 34 56 x x x x x x x x x x R19 ENE 57 78 x x x x x x x x x R20 E 79 101 x x x x x x x x x x x R21 ESE, SE 102 146 x x x x x x x x x x R22 SSE 147 168 x x x x x x x x x x R23 S 169 191 x x x x x x x x x x R24 SSW 192 213 x x x x x x x x x x x R25 SW 214 236 x x x x x x x x x x R26 WSW 237 258 x x x x x x x x x R27 W 259 281 x x x x x x x x x R28 WNW 282 303 x x x x x x x x x x x R29 NW 304 326 x x x x x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station 720 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuate 5Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R30 NNW, N 327 11 x x x x x x x x x x x x x x x R31 NNE 12 33 x x x x x x x x x x x x x x x x R32 NE, ENE 34 78 x x x x x x x x x x x x x x x x R33 E 79 101 x x x x x x x x x x x x x x x x x R34 ESE, SE 102 146 x x x x x x x x x x x x x x x R35 SSE 147 168 x x x x x x x x x x x x x x x R36 S 169 191 x x x x x x x x x x x x x x x R37 SSW 192 213 x x x x x x x x x x x x x x x x R38 SW 214 236 x x x x x x x x x x x x x x x R39 WSW 237 258 x x x x x x x x x x x x x x x R40 W 259 281 x x x x x x x x x x x x x x x R41 WNW 282 303 x x x x x x x x x x x x x x x x x R42 NW 304 326 x x x x x x x x x x x x x x x x Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region From: Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R43 5Mile Region N/A x x x x x x x x x x x x R44 NNW, N 327 11 x x x x x x R45 NNE 12 33 x x x x x R46 NE 34 56 x x x x x x R47 ENE 57 78 x x x x x R48 E 79 101 x x x x x x R49 ESE, SE 102 146 x x x x x x x R50 SSE 147 168 x x x x x x x R51 S, SSW 169 213 x x x x x x x R52 SW 214 236 x x x x x x x R53 WSW, W 237 281 x x x x x x R54 WNW 282 303 x x x x x x R55 NW 304 326 x x x x x x x PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station 721 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 71. Voluntary Evacuation Methodology North Anna Power Station 722 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 72. NAPS Shadow Region North Anna Power Station 723 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 73. Congestion Patterns at 30 Minutes after the Advisory to Evacuate North Anna Power Station 724 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 74. Congestion Patterns at 1 Hour after the Advisory to Evacuate North Anna Power Station 725 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 75. Congestion Patterns at 1 Hour and 30 Minutes after the Advisory to Evacuate North Anna Power Station 726 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 76. Congestion Patterns at 2 Hours after the Advisory to Evacuate North Anna Power Station 727 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 77. Congestion Patterns at 2 Hours and 30 Minutes after the Advisory to Evacuate North Anna Power Station 728 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure 78. Congestion Patterns at 3 Hours after the Advisory to Evacuate North Anna Power Station 729 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Summer, Midweek, Midday, Good (Scenario 1) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 25 20 Vehicles Evacuating 15 (Thousands) 10 5
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 79. Evacuation Time Estimates Scenario 1 for Region R03 Evacuation Time Estimates Summer, Midweek, Midday, Rain (Scenario 2) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 25 20 Vehicles Evacuating 15 (Thousands) 10 5
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 710. Evacuation Time Estimates Scenario 2 for Region R03 North Anna Power Station 730 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Summer, Weekend, Midday, Good (Scenario 3) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 25 20 Vehicles Evacuating 15 (Thousands) 10 5
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 711. Evacuation Time Estimates Scenario 3 for Region R03 Evacuation Time Estimates Summer, Weekend, Midday, Rain (Scenario 4) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 25 20 Vehicles Evacuating 15 (Thousands) 10 5
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 712. Evacuation Time Estimates Scenario 4 for Region R03 North Anna Power Station 731 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Summer, Midweek, Weekend, Evening, Good (Scenario 5) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 20 18 16 Vehicles Evacuating 14 12 10 (Thousands) 8 6
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| 4 2
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 713. Evacuation Time Estimates Scenario 5 for Region R03 Evacuation Time Estimates Winter, Midweek, Midday, Good (Scenario 6) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 20 18 16 Vehicles Evacuating 14 12 10 (Thousands) 8 6
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| 4 2
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 714. Evacuation Time Estimates Scenario 6 for Region R03 North Anna Power Station 732 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Winter, Midweek, Midday, Rain/Light Snow (Scenario 7) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 20 18 16 Vehicles Evacuating 14 12 10 (Thousands) 8 6
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| 4 2
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 715. Evacuation Time Estimates Scenario 7 for Region R03 Evacuation Time Estimates Winter, Midweek, Midday, Heavy Snow (Scenario 8) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 20 18 16 Vehicles Evacuating 14 12 10 (Thousands) 8 6
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| 4 2
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 7:00 7:30 8:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 716. Evacuation Time Estimates Scenario 8 for Region R03 North Anna Power Station 733 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Winter, Weekend, Midday, Good (Scenario 9) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 18 16 14 Vehicles Evacuating 12 10 8
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| (Thousands) 6 4
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| 2 0
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 717. Evacuation Time Estimates Scenario 9 for Region R03 Evacuation Time Estimates Winter, Weekend, Midday, Rain/Light Snow (Scenario 10) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 18 16 14 Vehicles Evacuating 12 10 8
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| (Thousands) 6 4
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| 2 0
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 718. Evacuation Time Estimates Scenario 10 for Region R03 North Anna Power Station 734 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Winter, Weekend, Midday, Heavy Snow (Scenario 11) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 18 16 14 Vehicles Evacuating 12 10 8
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| (Thousands) 6 4
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| 2 0
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 7:00 7:30 8:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 719. Evacuation Time Estimates Scenario 11 for Region R03 Evacuation Time Estimates Winter, Midweek, Weekend, Evening, Good (Scenario 12) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 18 16 14 Vehicles Evacuating 12 10 8
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| (Thousands) 6 4
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| 2 0
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 720. Evacuation Time Estimates Scenario 12 for Region R03 North Anna Power Station 735 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuation Time Estimates Winter, Weekend, Midday, Good, Special Event (Scenario 13) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 20 18 16 Vehicles Evacuating 14 12 10 (Thousands) 8 6
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| 4 2
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 721. Evacuation Time Estimates Scenario 13 for Region R03 Evacuation Time Estimates Summer, Midweek, Midday, Good, Roadway Impact (Scenario 14) 2Mile Region 5Mile Region Entire EPZ 90% 100%
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| 25 20 Vehicles Evacuating 15 (Thousands) 10 5
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| 0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time After Evacuation Recommendation (h:mm)
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| Figure 722. Evacuation Time Estimates Scenario 14 for Region R03 North Anna Power Station 736 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| 8 TRANSITDEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES This section details the analyses applied and the results obtained in the form of ETE for transit vehicles. The demand for transit service reflects the needs of three population groups:
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| residents with no vehicles available; residents of special facilities such as schools, preschools, and medical facilities; access and/or functional needs population.
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| These transit vehicles mix with the general evacuation traffic that is comprised mostly of passenger cars (pcs). The presence of each transit vehicle in the evacuating traffic stream is represented within the modeling paradigm described in Appendix D as equivalent to two pcs.
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| This equivalence factor represents the longer size and more sluggish operating characteristics of a transit vehicle, relative to those of a pc.
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| Transit vehicles must be mobilized in preparation for their respective evacuation missions.
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| Specifically:
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| * Bus drivers must be alerted
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| * They must travel to the bus depot
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| * They must be briefed there and assigned to a route or facility These activities consume time. It is estimated that vehicle mobilization time will average approximately 90 minutes for schools, preschools and medical facilities, and 150 minutes for transit dependent buses extending from the Advisory to Evacuate (ATE), to the time when buses first arrive at the facility to be evacuated.
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| During this mobilization period, other mobilization activities are taking place. One of these is the action taken by parents, neighbors, relatives and friends to pick up children from school prior to the arrival of buses, so that they may join their families. Virtually all studies of evacuations have concluded that this bonding process of uniting families is universally prevalent during emergencies and should be anticipated in the planning process. The current public information disseminated to residents of the NAPS EPZ indicates that schoolchildren will be evacuated to Evacuation Assembly Centers (EAC) at emergency action levels of Site Area Emergency or higher, and that parents should pick schoolchildren up at the EAC.
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| As discussed in Section 2, this study assumes a rapidly escalating accident. This report provides estimates of buses under the assumption that no children will be picked up by their parents (in accordance with NUREG/CR7002, Rev. 1), to present an upper bound estimate of buses required. This study assumes that preschools are also evacuated to EACs and parents will pick up these children at the EACs. Picking up children at schools or preschools could add to traffic congestion at these facilities, delaying the departure of the buses evacuating schoolchildren, which may have to return in a subsequent wave to the EPZ to evacuate the transitdependent population.
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| North Anna Power Station 81 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| The procedure for computing transitdependent ETE is to:
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| * Estimate demand for transit service (discussed in Section 3)
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| * Estimate time to perform all transit functions
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| * Estimate route travel times to the EPZ boundary and to the EACs 8.1 ETE for Schools, PreSchools, Transit Dependent People, and Medical Facilities The EPZ bus resources are assigned to evacuating children (if schools and preschools are in session at the time of the ATE) as the first priority in the event of an emergency. In the event that the allocation of buses dispatched from the depots to the various facilities and to the bus routes is somewhat inefficient, or if there is a shortfall of available drivers, then there may be a need for some buses to return to the EPZ from the EAC after completing their first evacuation trip, to complete a second wave of providing transport service to evacuees. For this reason, the ETE for the transitdependent population will be calculated for both a one wave transit evacuation and for two waves. Of course, if the impacted Evacuation Region is other than R03 (the entire EPZ), then there will likely be ample transit resources relative to demand in the impacted Region and this discussion of a second wave would likely not apply.
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| Transportation resources available were reviewed and approved by the EPZ county emergency management agencies for use in this study. The transportation resources available, as well as the number of vehicles needed to evacuate schools, preschools, medical facilities, the transit dependent population, and the access and/or functional needs population (discussed below in Section 8.2) are summarized in Table 81. These numbers indicate there are sufficient resources available to evacuate all transitdependent people in a single wave.
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| When school evacuation needs are satisfied, subsequent assignments of buses to service the transitdependent population should be sensitive to their mobilization time. Clearly, the buses should be dispatched after people have completed their mobilization activities and are in a position to board the buses when they arrive along the bus transit route.
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| Figure 81 presents the chronology of events relevant to transit operations. The elapsed time for each activity will now be discussed with reference to Figure 81.
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| Evacuation of Schools and PreSchools Activity: Mobilize Drivers (ABC)
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| Mobilization is the elapsed time from the ATE until the time the buses arrive at the school or preschool, to be evacuated. As previously stated, it is assumed that for a rapidly escalating radiological emergency with no observable indication before the fact, bus drivers would likely require 90 minutes to be contacted, to travel to the depot, be briefed, and to travel to the schools and preschools to be evacuated. Mobilization time is slightly longer in adverse weather
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| - 100 minutes in rain/light snow, and 110 minutes in heavy snow conditions.
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| Activity: Board Passengers (CD)
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| As discussed in Section 2.4 and 2.6v, a loading time of 15 minutes for good weather (20 minutes for rain/light snow and 25 minutes for heavy snow) for buses is used.
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| North Anna Power Station 82 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Activity: Travel to EPZ Boundary (DE)
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| The buses servicing the schools and preschools are ready to begin their evacuation trips at 105 minutes after the ATE - a 90minute mobilization time plus a 15minute loading time - in good weather. The UNITES software discussed in Section 1.3 was used to define bus routes along the most likely path from a school being evacuated to the EPZ boundary, traveling toward the appropriate EAC. This is done in UNITES by interactively selecting the series of nodes from the school/preschool to the EPZ boundary. Each bus route is given an identification number and is written to the DYNEV II input stream. DYNEV computes the route length and outputs the average speed for each 5minute interval, for each bus route. The specified bus routes are documented in Section 10 in Table 102 (refer to the maps of the linknode analysis network in Appendix K for node locations). Data provided by DYNEV during the appropriate timeframe depending on the mobilization and loading times (i.e., 100 to 105 minutes after the ATE for good weather) were used to compute the average speed for each route, as follows:
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| 60 .
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| 1 .
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| . 60 .
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| . . 1 .
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| The average speed1 computed (using this methodology) for the buses servicing each of the schools and preschools in the EPZ is shown in Table 82 through Table 84 for school and pre school evacuation. The travel time to the EPZ boundary was computed for each bus using the computed average speed and the distance to the EPZ boundary along the most likely route out of the EPZ. The travel time from the EPZ boundary to the EAC was computed assuming an average speed of 45 mph, 41 mph (10% decrease), and 38 mph (15% decrease) for good weather, rain/light snow and heavy snow, respectively. Speeds were reduced in Table 82 through Table 84 to 45 mph, 41 mph, and 38 mph for good weather, rain/light snow and heavy snow, respectively, for those calculated bus speeds which exceed 45 mph, as the school bus speed limit for state routes in Virginia is 45 mph.
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| Table 82 (good weather), Table 83 (rain/light snow) and Table 84 (heavy snow) present the following ETE (rounded up to the nearest 5 minutes) for schools and preschools in the EPZ:
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| : 1) The elapsed time from the ATE until the bus exits the EPZ; and
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| : 2) The elapsed time until the bus reaches the EAC (Estimated Time of Arrival - ETA - to the EAC).
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| 1 A winter, midweek, midday scenario was used for schools and pre-schools as that is when they are in session.
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| North Anna Power Station 83 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| The evacuation time out of the EPZ can be computed as the sum of times associated with Activities ABC, CD, and DE (For example: 90 minutes + 15 + 7 = 1:55 (rounded up to the nearest 5 minutes) for Mineral Christian Preschool, in good weather).
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| The average ETE for a singlewave evacuation of schools and preschools is 1 hour and 55 minutes, which is less than the 90th percentile ETE for the general population for an evacuation of the entire EPZ (Region R03) during Scenario 6 conditions. Thus, the evacuation of schools and preschools should not affect protective action decision making.
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| The evacuation time to the EAC is determined by adding the time associated with Activity EF (discussed below), to this EPZ evacuation time.
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| Activity: Travel to EACs (EF)
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| The distances from the EPZ boundary to the EACs are measured using GIS software along the most likely route from the EPZ exit point to the nearest appropriate EAC. The EACs are mapped in Figure 105. For a singlewave evacuation, this travel time outside the EPZ does not contribute to the ETE. Assumed bus speeds of 45 mph, 41 mph, and 38 mph for good weather, rain/light snow, and heavy snow, respectively, are applied for this activity for buses servicing the schools/preschools in the EPZ. The ETA to the EAC for each facility is also shown in Table 82 through Table 84.
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| Evacuation of TransitDependent People (Residents without access to a vehicle)
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| A detailed computation of the transit dependent people is discussed in Section 3.6. The total number of transit dependent people per PAZ was determined using a weighted distribution based on population. The number of buses required to evacuate this population was determined using a capacity of 30 people per bus. KLD designed 25 bus routes to service the major evacuation routes in each PAZ based on the bus routes map and description obtained from the county emergency plans, for the purposes of this study. These routes are described in Table 101 and mapped in Figure 102 through Figure 104. Those buses servicing the transit dependent evacuees will first travel along major evacuation routes, then proceed out of the EPZ.
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| Activity: Mobilize Drivers (ABC)
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| Mobilization time is the elapsed time from the ATE until the time the buses arrive at their designated route. The buses dispatched from the depots to service the transitdependent evacuees will be scheduled so that they arrive at their respective routes after their passengers have completed their mobilization. As shown in Figure 54 (Residents with no Commuters),
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| about 90% percent of the evacuees will complete their mobilization when the buses begin their routes, at approximately 150 minutes after the ATE. Those residents taking longer to mobilize are assumed to rideshare with a relative, friend or neighbor. Mobilization time is slightly longer in adverse weather - 160 minutes in rain/light snow, 170 minutes in heavy snow conditions.
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| The ETEs for transit trips were developed using both good weather and adverse weather conditions.
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| North Anna Power Station 84 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Activity: Board Passengers (CD)
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| For multiple stops along a pickup route, (transitdependent bus routes) estimation of travel time must allow for the delay associated with stopping and starting at each pickup point. The time, t, required for a bus to decelerate at a rate, a, expressed in ft/sec/sec, from a speed, v, expressed in ft/sec, to a stop, is t = v/a. Assuming the same acceleration rate and final speed following the stop yields a total time, T, to service boarding passengers:
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| 2 ,
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| Where B = Dwell time to service passengers. The total distance, s in feet, travelled during the deceleration and acceleration activities is: s = v2/a. If the bus had not stopped to service passengers, but had continued to travel at speed, v, then its travel time over the distance, s, would be: s/v = v/a. Then the total delay (i.e. pickup time, P) to service passengers is:
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| Assigning reasonable estimates:
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| * B = 50 seconds: a generous value for a single passenger, carrying personal items, to board per stop
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| * v = 25 mph = 37 ft/sec
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| * a = 4 ft/sec/sec, a moderate average rate Then, P 1 minute per stop. Allowing a 30 minute pickup time per bus run implies 30 stops per run, for good weather. It is assumed that bus acceleration and speed will be less in rain and snow; total loading time is 40 minutes per bus in rain/light snow, 50 minutes in heavy snow.
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| Activity: Travel to EPZ Boundary (DE)
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| The travel distance along the respective pickup routes within the EPZ is estimated using the UNITES software. Bus travel times within the EPZ are computed using average speeds computed by DYNEV, using the aforementioned methodology that was used for school and pre school evacuation.
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| Table 85 through Table 87 present the transitdependent population ETE for each bus route calculated using the procedures above for good weather, rain/light snow and heavy snow, respectively.
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| For example, the ETE for the bus route 1 is computed as 150 + 17 + 30 = 3:20 (rounded up to the nearest 5 minutes) for good weather. Here, 17 minutes is the time to travel 12.6 miles at 45 mph, the average speed output by the model for this route starting at 150 minutes. The ETE for a second wave (discussed below) is presented in the event there is a shortfall of available buses or bus drivers, as previously discussed.
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| The average singlewave ETE (3 hours and 30 minutes) for transit dependent population exceeds the general population ETE at the 90th percentile by 10 minutes (see Table 71) for an evacuation of the entire EPZ (Region R03) under Scenario 6 conditions (winter, midweek, midday, good weather) scenario. Thus, the evacuation of the transitdependent population could impact protect action decision making.
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| North Anna Power Station 85 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| The evacuation time to the EAC is determined by adding the time associated with Activity EF (discussed below), to this EPZ evacuation time.
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| Activity: Travel to EACs (EF)
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| The distances from the EPZ boundary to the EACs are measured using GIS software along the most likely route from the EPZ exit point to the EAC. The EACs are mapped in Figure 105. For a singlewave evacuation, this travel time outside the EPZ does not contribute to the ETE.
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| Assumed bus speeds of 45 mph, 41 mph, and 38 mph for good weather, rain/light snow, and heavy snow, respectively, are applied for this activity for buses servicing the transitdependent population. The estimated times to complete the second wave evacuation are presented in Table 85 through Table 87. The average second wave ETE exceed the 90th percentile general population ETE by 2 hours and 20 minutes and could impact protective action decision making if there are not sufficient buses or drivers to evacuate the transitdependent population in a single wave.
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| Evacuation of Medical Facilities Activity: Mobilize Drivers (ABC)
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| As discussed in Section 2.4 and Section 2.6, it is assumed that the mobilization time for medical facilities averages 90 minutes in good weather, 100 minutes in rain/light snow and 110 minutes in heavy snow.
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| Activity: Board Passengers (CD)
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| Item 5 of Section 2.4 discusses transit vehicle loading times for medical facilities. Loading times are assumed to be 1 minute per ambulatory passenger, 5 minutes per wheelchair bound passenger, and 15 minutes per bedridden passenger for ambulances. Item 3 of Section 2.4 discusses transit vehicle capacities to cap loading times per vehicle type.
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| Activity: Travel to EPZ Boundary (DE)
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| The travel distance along the respective evacuation routes within the EPZ is estimated using the UNITES software. Transit vehicle travel times within the EPZ are computed using average speeds computed by DYNEV, using the aforementioned methodology that was used for school and preschool evacuation.
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| Table 88 summarize the ETE for medical facilities within the EPZ for good weather, rain/light snow, and heavy snow. The travel time to the EPZ boundary is computed by dividing the distance to the EPZ boundary by the average travel speed. The ETE is the sum of the mobilization time, total passenger loading time, and travel time out of the EPZ. All ETE are rounded up to the nearest 5 minutes.
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| For example, the calculation of ETE for the Lake Anna Elder Care Inc with 8 bedridden residents during good weather is:
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| ETE: 90 + 15 x 2 (maximum capacity of an ambulance is 2 passengers) + 16 = 136 min.
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| or 2:20 (rounded up to the nearest 5 minutes)
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| The single wave ETE (2:20) for medical facilities in the EPZ does not exceed the 90th percentile ETE for the general population (3:20) for a winter, midweek, midday, good weather (Scenario 6) evacuation of the entire EPZ (Region R03) and should not impact protective action decision making.
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| 8.2 ETE for Access and/or Functional Needs Population Table 89 summarizes the ETE for access and/or functional needs people. The table is categorized by type of vehicle required and then broken down by weather condition. The table takes into consideration the deployment of multiple vehicles (not filled to capacity) to reduce the number of stops per vehicle. It is conservatively assumed that ambulatory and wheelchair bound households (HH) are spaced 3 miles apart and bedridden households are spaced 5 miles apart. Bus and wheelchair van speeds approximate 20 mph between households and ambulance speeds approximate 30 mph in good weather (10% slower in rain/light snow, 15%
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| slower in heavy snow). Mobilization times of 90 minutes were used (100 minutes for rain/light snow, and 110 minutes for heavy snow). Loading times of 5 minutes per person are assumed for ambulatory and wheelchair bound people and 15 minutes per person for bedridden people.
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| The last HH is assumed to be 5 miles from the EPZ boundary, and the networkwide average speed, capped at 45 mph (41 mph for rain/light snow and 38 mph for heavy snow), after the last pickup is used to compute travel time. ETE is computed by summing mobilization time, loading time at first HH, travel to subsequent HH, loading time at subsequent HH, and travel time to the EPZ boundary. All ETE are rounded to the nearest 5 minutes.
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| For example, assuming no more than one access and/or functional needs person per HH implies that 276 ambulatory, 3 wheelchair bound, and 31 bedridden HH need to be serviced. If 46 buses are deployed to service these access and/or functional needs HH, then each bus would require about 6 stops. The following outlines the ETE calculations for a bus:
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| : 1. Assume 46 buses are deployed, each with at most 6 stops, to service a total of 276 HH.
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| : 2. The ETE is calculated as follows:
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| * Buses arrive at the first pickup location: 90 minutes
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| * Load HH members at first pickup: 5 minutes
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| * Travel to subsequent pickup locations: 5 @ 9 minutes (3 miles @ 20 mph) = 45 minutes
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| * Load HH members at subsequent pickup locations: 5 @ 5 minutes = 25 minutes
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| * Travel to EPZ boundary: 7 minutes (5 miles @ 45 mph).
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| ETE: 90 + 5 + 45 + 25 + 7 = 2:55 rounded up to the nearest 5 minutes The average single wave ETE (2 hours and 45 minutes) in for access and/or functional needs population is less than the 90th percentile ETE for the general population evacuating for the entire EPZ (Region R03) under Scenario 6, Scenario 7 and Scenario 8 conditions and would likely not affect protective action decision making.
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| Table 81 indicates that there are sufficient transportation resources available in the EPZ to evacuate the school, preschools, medical facilities and the access and/or functional needs population in a single wave. As such, a second wave ETE for access and/or functional needs population is not considered.
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| Table 81. Summary of Transportation Resources Transportation Wheelchair Wheelchair Resource Buses Vans Buses Vans Ambulances Resources Available Louisa County 135 0 0 7 14 Caroline County 83 0 0 9 11 Hanover County 189 6 32 0 0 Livingston Elementary School 11 Berkeley Elementary School 7 Post Oak Elementary School 18 Spotsylvania High School 27 TOTAL: 470 6 32 16 25 Resources Needed Schools and Preschools (Table 38): 126 Medical Facilities (Table 36): 4 TransitDependent Population (Section 3.6, Table 312): 25 Access and/or Functional Needs Population (Table 39): 46 1 16 TOTAL TRANSPORTATION NEEDS: 197 0 0 1 20 North Anna Power Station 89 KLD Engineering, P.C.
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| Table 82. School and PreSchool Evacuation Time Estimates - Good Weather Travel Travel Dist. Time Dist. To Time to EPZ from Driver Loading EPZ Average EPZ Bdry to EPZ Bdry ETA to Mobilization Time Bdry Speed Bdry ETE EAC to EAC EAC School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)
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| LOUISA COUNTY SCHOOLS Mineral Christian Preschool 90 15 4.8 42.4 7 1:55 8.3 11 2:10 Louisa County High School 90 15 3.7 45.0 5 1:50 8.3 11 2:05 Louisa County Middle School 90 15 3.4 45.0 5 1:50 8.3 11 2:05 Thomas Jefferson Elementary School 90 15 1.5 45.0 2 1:50 8.6 11 2:05 Jouett Elementary School 90 15 0.3 39.9 0 1:45 21.0 28 2:15 SPOTSYLVANIA COUNTY SCHOOLS Livingston Elementary 90 15 9.1 45.0 12 2:00 9.1 12 2:15 Post Oak Middle School 90 15 3.4 45.0 5 1:50 9.1 12 2:05 Spotsylvania High School 90 15 3.2 44.9 4 1:50 8.0 11 2:05 Spotsylvania High School Governor's School 90 15 3.2 44.9 4 1:50 8.0 11 2:05 Berkeley Elementary 90 15 2.1 41.6 3 1:50 8.0 11 2:05 Maximum for EPZ: 2:00 Maximum: 2:15 Average for EPZ: 1:55 Average: 2:10 North Anna Power Station 810 KLD Engineering, P.C.
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| Table 83. School and PreSchool Evacuation Time Estimates - Rain/Light Snow Travel Travel Dist. Time Dist. To Time to EPZ from Driver Loading EPZ Average EPZ Bdry to EPZ Bdry ETA to Mobilization Time Bdry Speed Bdry ETE EAC to EAC EAC School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)
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| LOUISA COUNTY SCHOOLS Mineral Christian Preschool 100 20 4.8 38.4 8 2:10 8.3 12 2:25 Louisa County High School 100 20 3.7 41.0 5 2:05 8.3 12 2:20 Louisa County Middle School 100 20 3.4 41.0 5 2:05 8.3 12 2:20 Thomas Jefferson Elementary School 100 20 1.5 41.0 2 2:05 8.6 13 2:20 Jouett Elementary School 100 20 0.3 36.0 1 2:05 21.0 31 2:40 SPOTSYLVANIA COUNTY SCHOOLS Livingston Elementary 100 20 9.1 41.0 13 2:15 9.1 13 2:30 Post Oak Middle School 100 20 3.4 41.0 5 2:05 9.1 13 2:20 Spotsylvania High School 100 20 3.2 40.5 5 2:05 8.0 12 2:20 Spotsylvania High School Governor's 100 20 3.2 40.5 5 2:05 8.0 12 2:20 School Berkeley Elementary 100 20 2.1 37.7 3 2:05 8.0 12 2:20 Maximum for EPZ: 2:15 Maximum: 2:40 Average for EPZ: 2:10 Average: 2:25 North Anna Power Station 811 KLD Engineering, P.C.
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| Table 84. School and PreSchool Evacuation Time Estimates - Heavy Snow Travel Travel Dist. Time Dist. To Time to EPZ from Driver Loading EPZ Average EPZ Bdry to EPZ Bdry ETA to Mobilization Time Bdry Speed Bdry ETE EAC to EAC EAC School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)
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| LOUISA COUNTY SCHOOLS Mineral Christian Preschool 110 25 4.8 36.2 8 2:25 8.3 13 2:40 Louisa County High School 110 25 3.7 38.0 6 2:25 8.3 13 2:40 Louisa County Middle School 110 25 3.4 38.0 5 2:20 8.3 13 2:35 Thomas Jefferson Elementary School 110 25 1.5 38.0 2 2:20 8.6 14 2:35 Jouett Elementary School 110 25 0.3 33.8 1 2:20 21.0 33 2:55 SPOTSYLVANIA COUNTY SCHOOLS Livingston Elementary 110 25 9.1 38.0 14 2:30 9.1 14 2:45 Post Oak Middle School 110 25 3.4 38.0 5 2:20 9.1 14 2:35 Spotsylvania High School 110 25 3.2 38.0 5 2:20 8.0 13 2:35 Spotsylvania High School Governor's 110 25 3.2 38.0 5 2:20 8.0 13 2:35 School Berkeley Elementary 110 25 2.1 36.9 3 2:20 8.0 13 2:35 Maximum for EPZ: 2:30 Maximum: 2:55 Average for EPZ: 2:25 Average: 2:40 North Anna Power Station 812 KLD Engineering, P.C.
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| Table 85. TransitDependent Evacuation Time Estimates Good Weather OneWave TwoWave Route Route Pickup Distance Travel Driver Route Pickup Route Number Mobilization Length Speed Travel Time Time ETE to EAC Time to Unload Rest Travel Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) EAC (min) (min) (min) Time (min) (min) (hr:min) 1 1 150 12.6 45.0 17 30 3:20 12.9 17 5 10 51 30 5:15 2 1 150 17.3 43.5 24 30 3:25 12.9 17 5 10 63 30 5:30 3 1 150 20.2 45.0 27 30 3:30 8.0 11 5 10 65 30 5:35 4 1 150 15.3 45.0 20 30 3:20 12.9 17 5 10 58 30 5:20 5 1 150 15.9 45.0 21 30 3:25 8.0 11 5 10 54 30 5:15 6 1 150 21.9 45.0 29 30 3:30 12.9 17 5 10 75 30 5:50 7 1 150 19.8 45.0 26 30 3:30 8.0 11 5 10 64 30 5:30 8 1 150 32.2 45.0 43 30 3:45 13.6 18 5 10 104 30 6:35 9 1 150 22.8 45.0 30 30 3:30 8.0 11 5 10 72 30 5:40 10 1 150 26.3 41.0 38 30 3:40 13.6 18 5 10 90 30 6:15 11 1 150 17.3 45.0 23 30 3:25 13.7 18 5 10 64 30 5:35 12 1 150 27.6 42.6 39 30 3:40 12.9 17 5 10 92 30 6:15 13 1 150 17.0 41.7 24 30 3:25 8.0 11 5 10 57 30 5:20 14 1 150 36.6 45.0 49 30 3:50 12.9 17 5 10 115 30 6:50 15 1 150 17.5 45.0 23 30 3:25 8.0 11 5 10 58 30 5:20 16 1 150 23.2 44.4 31 30 3:35 12.9 17 5 10 79 30 6:00 17 1 150 19.1 43.3 26 30 3:30 8.0 11 5 10 63 30 5:30 18 1 150 26.3 45.0 35 30 3:35 9.5 13 5 10 83 30 6:00 19 1 150 18.5 45.0 25 30 3:25 8.3 11 5 10 60 30 5:25 20 1 150 29.2 45.0 39 30 3:40 8.3 11 5 10 89 30 6:05 21 1 150 10.7 45.0 14 30 3:15 13.5 18 5 10 47 30 5:05 22 1 150 5.1 45.0 7 30 3:10 8.3 11 5 10 25 30 4:35 23 1 150 8.8 45.0 12 30 3:15 7.8 10 5 10 34 30 4:45 24 1 150 8.0 33.5 14 30 3:15 7.8 10 5 10 35 30 4:45 25 1 150 17.0 43.1 24 30 3:25 21.8 29 5 10 75 30 5:55 Maximum ETE: 3:50 Maximum ETE: 6:50 Average ETE: 3:30 Average ETE: 5:40 North Anna Power Station 813 KLD Engineering, P.C.
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| Table 86. TransitDependent Evacuation Time Estimates - Rain/Light Snow OneWave TwoWave Route Route Pickup Distance Travel Driver Route Pickup Route Number Mobilization Length Speed Travel Time Time ETE to EAC Time to Unload Rest Travel Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) EAC (min) (min) (min) Time (min) (min) (hr:min) 1 1 160 12.6 40.9 18 40 3:40 12.9 19 5 10 54 40 5:50 2 1 160 17.3 39.5 26 40 3:50 12.9 19 5 10 68 40 6:15 3 1 160 20.2 41.0 30 40 3:50 8.0 12 5 10 68 40 6:05 4 1 160 15.3 41.0 22 40 3:45 12.9 19 5 10 62 40 6:05 5 1 160 15.9 40.9 23 40 3:45 8.0 12 5 10 57 40 5:50 6 1 160 21.9 41.0 32 40 3:55 12.9 19 5 10 80 40 6:30 7 1 160 19.8 41.0 29 40 3:50 8.0 12 5 10 67 40 6:05 8 1 160 32.2 41.0 47 40 4:10 13.6 20 5 10 1430 40 5:15 9 1 160 22.8 41.0 33 40 3:55 8.0 12 5 10 76 40 6:20 10 1 160 26.3 37.1 43 40 4:05 13.6 20 5 10 96 40 7:00 11 1 160 17.3 41.0 25 40 3:45 13.7 20 5 10 68 40 6:10 12 1 160 27.6 38.8 43 40 4:05 12.9 19 5 10 97 40 7:00 13 1 160 17.0 38.1 27 40 3:50 8.0 12 5 10 60 40 6:00 14 1 160 36.6 41.0 54 40 4:15 12.9 19 5 10 121 40 7:30 15 1 160 17.5 41.0 26 40 3:50 8.0 12 5 10 61 40 6:00 16 1 160 23.2 39.9 35 40 3:55 12.9 19 5 10 84 40 6:35 17 1 160 19.1 38.8 30 40 3:50 8.0 12 5 10 66 40 6:05 18 1 160 26.3 41.0 38 40 4:00 9.5 14 5 10 88 40 6:40 19 1 160 18.5 41.0 27 40 3:50 8.3 12 5 10 64 40 6:05 20 1 160 29.2 41.0 43 40 4:05 8.3 12 5 10 94 40 6:50 21 1 160 10.7 41.0 16 40 3:40 13.5 20 5 10 50 40 5:45 22 1 160 5.1 41.0 8 40 3:30 8.3 12 5 10 26 40 5:05 23 1 160 8.8 41.0 13 40 3:35 7.8 11 5 10 36 40 5:20 24 1 160 8.0 30.6 16 40 3:40 7.8 11 5 10 35 40 5:25 25 1 160 17.0 39.0 26 40 3:50 21.8 32 5 10 80 40 6:40 Maximum ETE: 4:15 Maximum ETE: 7:30 Average ETE: 3:55 Average ETE: 6:10 North Anna Power Station 814 KLD Engineering, P.C.
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| Table 87. Transit Dependent Evacuation Time Estimates - Heavy Snow OneWave TwoWave Route Route Pickup Distance Travel Driver Route Pickup Route Number Mobilization Length Speed Travel Time Time ETE to EAC Time to Unload Rest Travel Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) EAC (min) (min) (min) Time (min) (min) (hr:min) 1 1 170 12.6 38.0 20 50 4:00 12.9 20 5 10 57 50 6:25 2 1 170 17.3 37.3 28 50 4:10 12.9 20 5 10 71 50 6:50 3 1 170 20.2 38.0 32 50 4:15 8.0 13 5 10 72 50 6:45 4 1 170 15.3 38.0 24 50 4:05 12.9 20 5 10 65 50 6:35 5 1 170 15.9 38.0 25 50 4:05 8.0 13 5 10 59 50 6:25 6 1 170 21.9 38.0 35 50 4:15 12.9 20 5 10 84 50 7:05 7 1 170 19.8 38.0 31 50 4:15 8.0 13 5 10 71 50 6:45 8 1 170 32.2 38.0 51 50 4:35 13.6 22 5 10 116 50 8:00 9 1 170 22.8 38.0 36 50 4:20 8.0 13 5 10 79 50 7:00 10 1 170 26.3 35.3 45 50 4:25 13.6 22 5 10 100 50 7:35 11 1 170 17.3 37.3 28 50 4:10 13.7 22 5 10 72 50 6:50 12 1 170 27.6 36.7 45 50 4:25 12.9 20 5 10 100 50 7:30 13 1 170 17.0 36.0 28 50 4:10 8.0 13 5 10 64 50 6:35 14 1 170 36.6 38.0 58 50 4:40 12.9 20 5 10 126 50 8:15 15 1 170 17.5 38.0 28 50 4:10 8.0 13 5 10 64 50 6:35 16 1 170 23.2 38.0 37 50 4:20 12.9 20 5 10 88 50 7:15 17 1 170 19.1 37.2 31 50 4:15 8.0 13 5 10 70 50 6:45 18 1 170 26.3 38.0 42 50 4:25 9.5 15 5 10 92 50 7:20 19 1 170 18.5 38.0 29 50 4:10 8.3 13 5 10 67 50 6:35 20 1 170 29.2 38.0 46 50 4:30 8.3 13 5 10 98 50 7:30 21 1 170 10.7 38.0 17 50 4:00 13.5 21 5 10 52 50 6:20 22 1 170 5.1 38.0 8 50 3:50 8.3 13 5 10 28 50 5:40 23 1 170 8.8 38.0 14 50 3:55 7.8 12 5 10 38 50 5:50 24 1 170 8.0 29.0 17 50 4:00 7.8 12 5 10 39 50 6:00 25 1 170 17.0 38.0 27 50 4:10 21.8 34 5 10 84 50 7:15 Maximum ETE: 4:40 Maximum ETE: 8:15 Average ETE: 4:15 Average ETE: 6:55 North Anna Power Station 815 KLD Engineering, P.C.
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| Table 88. Medical Facilities Evacuation Time Estimates Total Travel Time to Mobilization Loading Rate Loading Dist. To EPZ EPZ Boundary ETE Medical Facility Patient Weather Conditions (min) (min per person) People Time (min) Bdry (mi) (min) (hr:min)
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| Good 90 15 8 30 12.1 16 2:20 Lake Anna Elder Care Inc Bedridden Rain 100 15 8 30 12.1 18 2:30 Snow 110 15 8 30 12.1 19 2:40 Table 89. Access and/or Functional Needs Population Evacuation Time Estimates Total Loading Travel Time People Loading Travel to Time at to EPZ Requiring Vehicles Weather Mobilization Time at 1st Subsequent Subsequent Boundary ETE Vehicle Type Vehicle deployed Stops Conditions Time (min) Stop (min) Stops (min) Stops (min) (min) (hr:min)
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| Good 90 45 7 2:55 Buses 276 46 6 Rain 100 5 50 25 7 3:10 Snow 110 55 8 3:25 Good 90 18 7 2:10 Wheelchair 3 1 3 Rain 100 5 20 10 7 2:25 Vans Snow 110 22 8 2:35 Good 90 10 7 2:20 Ambulances 31 16 2 Rain 100 15 11 15 7 2:30 Snow 110 13 8 2:45 Maximum ETE: 3:25 Average ETE: 2:45 North Anna Power Station 816 KLD Engineering, P.C.
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| (Subsequent Wave)
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| A B C D E F G Time Event A Advisory to Evacuate B Bus Dispatched from Depot C Bus Arrives at Facility/Pickup Route D Bus Departs for Evacuation Assembly Center E Bus Exits Region F Bus Arrives at Evacuation Assembly Center G Bus Available for Second Wave Evacuation Service Activity AB Driver Mobilization BC Travel to Facility or to Pickup Route CD Passengers Board the Bus DE Bus Travels Towards Region Boundary EF Bus Travels Towards Evacuation Assembly Center Outside the EPZ FG Passengers Leave Bus; Driver Takes a Break Figure 81. Chronology of Transit Evacuation Operations North Anna Power Station 817 KLD Engineering, P.C.
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| 9 TRAFFIC MANAGEMENT STRATEGY This section discusses the suggested Traffic Management Plan (TMP) that is designed to expedite the movement of evacuating traffic. The resources required to implement this strategy include:
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| * Personnel with the capabilities of performing the planned control functions of traffic guides (preferably, not necessarily, law enforcement officers).
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| * The Manual on Uniform Traffic Control Devices (MUTCD) published by the Federal Highway Administration (FHWA) of the U.S.D.O.T provides guidance for Traffic Control Devices to assist these personnel in the performance of their tasks. All state and most county transportation agencies have access to the MUTCD, which is available online:
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| http://mutcd.fhwa.dot.gov which provides access to the official PDF version.
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| * A plan that defines all Traffic and Access Control Point (TCPs/ACPs) locations, provides necessary details and is documented in a format that is readily understood by those assigned to perform traffic control.
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| The functions to be performed in the field are:
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| : 1. Facilitate evacuating traffic movements that safely expedite travel out of the EPZ.
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| : 2. Discourage traffic movements that move evacuating vehicles in a direction which takes them significantly closer to the power plant, or which interferes with the efficient flow of other evacuees.
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| The terms "facilitate" and "discourage" are employed rather than "enforce" and "prohibit" to indicate the need for flexibility in performing the traffic control function. There are always legitimate reasons for a driver to prefer a direction other than that indicated.
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| For example:
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| * A driver may be traveling home from work or from another location, to join other family members prior to evacuating.
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| * An evacuating driver may be travelling to pick up a relative, or other evacuees.
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| * The driver may be an emergency worker en route to perform an important activity.
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| The implementation of a plan must also be flexible enough for the application of sound judgment by the traffic guide.
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| The TMP is the outcome of the following process:
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| : 1. The existing TCPs and ACPs identified in the county emergency plans serve as the basis of the TMP, as per NUREG/CR7002, Rev. 1.
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| : 2. Evacuation simulations were run using DYNEV II to predict traffic congestion during evacuation (see Section 7.3 and Figures 73 through 78).
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| : 3. The existing TCPs and ACPs defined in the existing TMP, and how they were applied in this study, are discussed in Appendix G.
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| : 4. These simulations help to identify the best routing and critical intersections that experience pronounced congestion during evacuation. No additional TCPs and ACPs North Anna Power Station 91 KLD Engineering, P.C.
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| were identified which would benefit the ETE as part of this study. See Appendix G for more detail.
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| : 5. Prioritization of TCPs and ACPs.
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| Application of traffic and access control at some TCPs and ACPs will have a more pronounced influence on expediting traffic movements than at other TCPs and ACPs. For example, TCPs controlling traffic originating from areas in close proximity to the power plant could have a more beneficial effect on minimizing potential exposure to radioactivity than those TCPs located far from the power plant. These priorities should be assigned by state/county emergency management representatives and by law enforcement personnel.
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| Appendix G documents the existing TMP and a list of TCPs and/or ACPs using the process enumerated above.
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| 9.1 Assumptions The ETE calculations documented in Section 7 and 8 assume that the TMP is implemented during evacuation.
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| The ETE calculations reflect the assumptions that all externalexternal trips are interdicted and diverted after 2 hours have elapsed from the ATE.
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| All transit vehicles and other responders entering the EPZ to support the evacuation are assumed to be unhindered by personal manning TCPs and ACPs.
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| Study assumptions 1 through 3 in Section 2.5 discuss TCP and ACP operations.
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| 9.2 Additional Considerations The use of Intelligent Transportation Systems (ITS) technologies can reduce manpower and equipment needs, while still facilitating the evacuation process. Dynamic Message Signs (DMS) can be placed within the EPZ to provide information to travelers regarding traffic conditions, route selection, and EAC information. DMS can also be placed outside of the EPZ to warn motorists to avoid using routes that may conflict with the flow of evacuees away from the power plant. Highway Advisory Radio (HAR) can be used to broadcast information to evacuees during egress through their vehicle stereo systems. Automated Traveler Information Systems (ATIS) can also be used to provide evacuees with information. Internet websites can provide traffic and evacuation route information before the evacuee begins their trip, while the on board navigation systems (GPS units), and smartphones can be used to provide information during the evacuation trip.
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| These are only several examples of how ITS technologies can benefit the evacuation process.
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| Consideration should be given that ITS technologies be used to facilitate the evacuation process, and any additional signage placed should consider evacuation needs.
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| 10 EVACUATION ROUTES AND EVACUATION ASSEMBLY CENTERS 10.1 Evacuation Routes Evacuation routes are comprised of two distinct components:
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| * Routing from a PAZ being evacuated to the boundary of the Evacuation Region and thence out of the EPZ.
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| * Routing of transitdependent evacuees (schools, preschools, medical facilities, and residents who do not own or have access to a private vehicle) from the EPZ boundary to Evacuation Assembly Centers (EACs).
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| Evacuees will select routes within the EPZ in such a way as to minimize their exposure to risk.
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| This expectation is met by the DYNEV II model routing traffic away from the location of the plant to the extent practicable. The DTRAD model satisfies this behavior by routing traffic so as to balance traffic demand relative to the available highway capacity to the extent possible. See Appendices B through D for further discussion.
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| The major evacuation routes for the EPZ are shown in Figure 101. These routes will be used by the general population evacuating in private vehicles, and by the transitdependent population evacuating in buses, wheelchair buses/vans, and ambulances. Transitdependent evacuees will be routed to EACs. General population may evacuate to either an EAC or some alternate destination (i.e., lodging facility, relatives home, campground) outside the EPZ.
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| The routing of transitdependent evacuees from the EPZ boundary to EACs is designed to minimize the amount of travel outside the EPZ, from the points where these routes cross the EPZ boundary.
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| Table 101 summarizes the transitdependent bus routes servicing the EPZ. These bus routes are mapped by county in Figure 102 through Figure 104.
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| It is assumed that residents will walk to these routes to flag down a bus, and that they can arrive at the roadway within the 150minute bus mobilization time (good weather).
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| Schools, preschools, and medical facilities were routed along the most likely path from the facility being evacuated to the EPZ boundary, traveling toward the EAC, in order to compute ETE.
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| The specified bus routes for all the transitdependent population are documented in Table 102 (refer to the maps of the linknode analysis network in Appendix K for node locations).
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| North Anna Power Station 101 KLD Engineering, P.C.
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| 10.2 Evacuation Assembly Centers Transitdependent evacuees are transported to the nearest EAC for each county.
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| The Radiological Emergency Response Plan (RERP) for the State of Virginia indicates evacuees will be received, monitored for contamination, decontaminated, if necessary, and provided with emergency medical and nursing coverage, clothing, and supplies at the EACs.
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| Table 103 presents a list of the EACs for each school and preschool in the EPZ. It is assumed that all school/preschool evacuees will be taken to the appropriate EAC and subsequently be picked up by parents or guardians.
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| Figure 105 presents an overview of the general population EACs (listed in the public information and the state RERP) servicing the EPZ. Note EACs serve both the school population and the general public.
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| North Anna Power Station 102 KLD Engineering, P.C.
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| Table 101. Summary of TransitDependent Bus Routes No. of Length Route Buses Route Description (mi.)
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| 1 1 Spotsylvania County 1 pick up residents in PAZ 11, 12, 21, 22 12.6 2 1 Spotsylvania County 2 pick up residents in PAZ 11, 12, 21 17.3 3 1 Spotsylvania County 3 pick up residents in PAZ 9, 11, 12, 22 20.2 4 1 Spotsylvania County 4 pick up residents in PAZ 9, 11, 12, 13, 20, 21 15.3 5 1 Spotsylvania County 5 pick up residents in PAZ 11, 21, 22 15.9 6 1 Spotsylvania County 6 pick up residents in PAZ 12, 13, 14, 18 21.9 7 1 Spotsylvania County 7 pick up residents in PAZ 13, 18, 19 19.8 8 1 Spotsylvania County 8 pick up residents in PAZ 14, 18 32.2 9 1 Spotsylvania County 9 pick up residents in PAZ 13, 14, 18 22.8 10 1 Spotsylvania County 10 pick up residents in PAZ 13, 14, 18, 20 26.3 11 1 Louisa County 1 pick up residents in PAZ 3, 5 17.3 12 1 Louisa County 2 pick up residents in PAZ 6, 7, 10, 25 27.6 13 1 Louisa County 3 pick up residents in PAZ 4, 6, 8, 10 17.0 14 1 Louisa County 4 pick up residents in PAZ 5, 7, 26 36.6 15 1 Louisa County 5 pick up residents in PAZ 2, 4, 8, 10, 15, 16 17.5 16 1 Louisa County 6 pick up residents in PAZ 4, 8, 15, 16 23.2 17 1 Louisa County 7 pick up residents in PAZ 15, 16 19.1 18 1 Louisa County 8 pick up residents in PAZ 3, 5, 7, 26 26.3 19 1 Louisa County 9 pick up residents in PAZ 2, 3, 5, 16 18.5 20 1 Louisa County 10 pick up residents in PAZ 3 29.2 21 1 Orange County 1 pick up residents in PAZ 17 10.7 22 1 Orange County 2 pick up residents in PAZ 17 5.1 23 1 Hanover County 1 pick up residents in PAZ 24 8.8 24 1 Hanover County 2 pick up residents in PAZ 24 8.0 25 1 Caroline County 1 pick up residents in PAZ 23 17.0 Total: 25 North Anna Power Station 103 KLD Engineering, P.C.
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| Table 102. Bus Route Descriptions Bus Route Number Description Nodes Traversed from Route Start to EPZ Boundary 108, 406, 899, 900, 901, 1069, 107, 390, 389, 388, 106, 588, 383, 587, 586, 1 Spotsylvania County 1 Transit Route 585, 584, 583, 582, 387, 386, 105, 10 399, 912, 400, 1063, 1062, 1061, 490, 1060, 1059, 1092, 1058, 1057, 1056, 2 Spotsylvania County 2 Transit Route 388, 106, 588, 383, 587, 586, 585, 584, 583, 582, 387, 386, 105, 10 153, 916, 918, 915, 914, 399, 398, 555, 397, 392, 774, 393, 394, 619, 395, 3 Spotsylvania County 3 Transit Route 910, 396, 108, 406, 899, 900, 901, 1069, 107, 390, 389, 388, 106, 588, 383, 587, 586, 585, 584, 583, 582, 387, 386, 105, 10 203, 5, 283, 160, 6, 1014, 1013, 276, 1019, 171, 1020, 1022, 7, 1023, 378, 4 Spotsylvania County 4 Transit Route 1028, 377, 174, 8, 497, 1030, 9, 717, 818, 820, 819, 10 394, 619, 395, 910, 396, 108, 406, 899, 900, 901, 1069, 107, 390, 389, 388, 5 Spotsylvania County 5 Transit Route 106, 588, 383, 587, 586, 585, 584, 583, 582, 387, 386, 105, 10 158, 159, 556, 557, 160, 6, 144, 622, 141, 140, 71, 939, 559, 74, 79, 91, 760, 6 Spotsylvania County 6 Transit Route 761, 96, 762, 99, 1113, 100, 1123, 21 7 Spotsylvania County 7 Transit Route 23, 951, 950, 489, 949, 948, 104, 103, 22, 192, 458, 21 203, 5, 283, 160, 6, 1014, 1013, 276, 1019, 171, 1020, 1022, 7, 1023, 378, 8 Spotsylvania County 8 Transit Route 1028, 377, 174, 8 72, 938, 937, 558, 71, 140, 141, 622, 144, 6, 1014, 1013, 276, 1019, 171, 9 Spotsylvania County 9 Transit Route 1020, 1022, 7, 1023, 378, 1028, 377, 174, 8, 497, 1030, 9, 717, 818, 820, 819, 10 136, 943, 942, 130, 941, 940, 125, 74, 944, 945, 486, 946, 101, 102, 103, 22, 10 Spotsylvania County 10 Transit Route 192, 458, 21 11 Louisa County 1 Transit Route 165, 1011, 163, 80, 1120, 313, 1119 37, 604, 60, 248, 271, 272, 889, 273, 59, 600, 274, 1164, 58, 281, 601, 602, 12 Louisa County 2 Transit Route 434, 885, 57, 603, 56, 48, 335, 305, 870, 517, 63, 64, 312, 1117, 342, 182, 519 36, 433, 428, 429, 430, 1087, 431, 432, 434, 885, 57, 603, 56, 48, 335, 305, 13 Louisa County 3 Transit Route 870, 517, 63, 64, 312, 1117, 342, 182, 519 14 Louisa County 4 Transit Route 81, 278, 92, 93, 1090, 539 36, 199, 607, 321, 4, 347, 348, 511, 3, 510, 299, 345, 346, 344, 881, 343, 46, 15 Louisa County 5 Transit Route 878, 298, 47, 513, 1121, 297, 48, 335, 305, 870, 517, 63, 64, 312, 1117, 342, 182, 519 16 Louisa County 6 Transit Route 447, 758, 757, 228, 227, 525, 524, 522, 222, 521, 520, 221, 1122, 220, 219 510, 756, 241, 447, 758, 757, 228, 227, 525, 524, 522, 222, 521, 520, 221, 17 Louisa County 7 Transit Route 1122, 220, 219 18 Louisa County 8 Transit Route 81, 278, 92, 93, 1090, 539 19 Louisa County 9 Transit Route 163, 1011, 165, 188, 81, 278, 92, 93, 1090, 539 20 Louisa County 10 Transit Route 81, 278, 92, 93, 1090, 539 21 Orange County 1 Transit Route 35, 1161, 14, 482, 1078, 239, 240 22 Orange County 2 Transit Route 482, 1078, 239, 240 23 Hanover County 1 Transit Route 438, 546, 547, 41 North Anna Power Station 104 KLD Engineering, P.C.
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| Bus Route Number Description Nodes Traversed from Route Start to EPZ Boundary 24 Hanover County 2 Transit Route 154, 868, 41, 771 25 Caroline County 1 Transit Route 110, 1162, 840, 839 26 Mineral Christian Preschool 297, 48, 335, 305, 870, 517, 63, 64, 312, 1117, 342, 182, 519 27 Louisa County High School 516, 517, 63, 64, 312, 1117, 342, 182, 519 28 Louisa County Middle School 517, 63, 64, 312, 1117, 342, 182, 519 29 Thomas Jefferson Elementary School 163, 80, 1120, 313 30 Jouett Elementary School 640, 641, 495 171, 1020, 1022, 7, 1023, 378, 1028, 377, 174, 8, 497, 1030, 9, 717, 818, 31 Livingston Elementary 820, 819, 10 32 Post Oak Middle School 497, 1030, 9, 717, 818, 820, 819, 10 Spotsylvania High School, Spotsylvania 33 581, 497, 1030, 9, 717, 818, 820, 819, 10 High School Governor's School 34 Berkeley Elementary 582, 387, 386, 105, 10 556, 557, 160, 6, 1014, 1013, 276, 1019, 171, 1020, 1022, 7, 1023, 378, 35 Lake Anna Elder Care Inc 1028, 377, 174, 8, 497, 1030, 9, 717, 818, 820, 819, 10 North Anna Power Station 105 KLD Engineering, P.C.
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| Table 103. School and Preschool Evacuation Assembly Centers School Evacuation Assembly Center Mineral Christian Preschool Louisa County High School Louisa County Middle School MossNuckols Elementary School Thomas Jefferson Elementary School Jouett Elementary School Livingston Elementary Post Oak Middle School Spotsylvania High School Massaponax High School Spotsylvania High School Governor's School Berkeley Elementary North Anna Power Station 106 KLD Engineering, P.C.
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| Figure 101. Major Evacuation Routes within the NAPS EPZ North Anna Power Station 107 KLD Engineering, P.C.
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| Figure 102. TransitDependent Bus Routes - Spotsylvania County North Anna Power Station 108 KLD Engineering, P.C.
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| Figure 103. TransitDependent Bus Routes - Louisa County North Anna Power Station 109 KLD Engineering, P.C.
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| Figure 104. TransitDependent Bus Routes - Caroline, Hanover and Orange Counties North Anna Power Station 1010 KLD Engineering, P.C.
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| Figure 105. General Population Evacuation Assembly Centers North Anna Power Station 1011 KLD Engineering, P.C.
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| APPENDIX A Glossary of Traffic Engineering Terms
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| A. GLOSSARY OF TRAFFIC ENGINEERING TERMS Table A1. Glossary of Traffic Engineering Terms Term Definition Analysis Network A graphical representation of the geometric topology of a physical roadway system, which is comprised of directional links and nodes.
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| Link A network link represents a specific, onedirectional section of roadway. A link has both physical (length, number of lanes, topology, etc.) and operational (turn movement percentages, service rate, freeflow speed) characteristics.
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| Measures of Effectiveness Statistics describing traffic operations on a roadway network.
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| Node A network node generally represents an intersection of network links. A node has control characteristics, i.e., the allocation of service time to each approach link.
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| Origin A location attached to a network link, within the EPZ or Shadow Region, where trips are generated at a specified rate in vehicles per hour (vph). These trips enter the roadway system to travel to their respective destinations.
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| Prevailing Roadway and Relates to the physical features of the roadway, the nature (e.g.,
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| Traffic Conditions composition) of traffic on the roadway and the ambient conditions (weather, visibility, pavement conditions, etc.).
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| Service Rate Maximum rate at which vehicles, executing a specific turn maneuver, can be discharged from a section of roadway at the prevailing conditions, expressed in vehicles per second (vps) or vph.
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| Service Volume Maximum number of vehicles which can pass over a section of roadway in one direction during a specified time period with operating conditions at a specified Level of Service (The Service Volume at the upper bound of Level of Service, E, equals Capacity).
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| Service Volume is usually expressed as vph.
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| Signal Cycle Length The total elapsed time to display all signal indications, in sequence.
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| The cycle length is expressed in seconds.
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| Signal Interval A single combination of signal indications. The interval duration is expressed in seconds. A signal phase is comprised of a sequence of signal intervals, usually green, yellow, red.
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| Term Definition Signal Phase A set of signal indications (and intervals) which services a particular combination of traffic movements on selected approaches to the intersection. The phase duration is expressed in seconds.
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| Traffic (Trip) Assignment A process of assigning traffic to paths of travel in such a way as to satisfy all trip objectives (i.e., the desire of each vehicle to travel from a specified origin in the network to a specified destination) and to optimize some stated objective or combination of objectives. In general, the objective is stated in terms of minimizing a generalized "cost". For example, "cost" may be expressed in terms of travel time.
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| Traffic Density The number of vehicles that occupy one lane of a roadway section of specified length at a point in time, expressed as vehicles per mile (vpm).
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| Traffic (Trip) Distribution A process for determining the destinations of all traffic generated at the origins. The result often takes the form of a Trip Table, which is a matrix of origindestination traffic volumes.
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| Traffic Simulation A computer model designed to replicate the realworld operation of vehicles on a roadway network, so as to provide statistics describing traffic performance. These statistics are called Measures of Effectiveness (MOE).
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| Traffic Volume The number of vehicles that pass over a section of roadway in one direction, expressed in vph. Where applicable, traffic volume may be stratified by turn movement.
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| Travel Mode Distinguishes between private auto, bus, rail, pedestrian and air travel modes.
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| Trip Table or Origin A rectangular matrix or table, whose entries contain the number Destination Matrix of trips generated at each specified origin, during a specified time period, that are attracted to (and travel toward) each of its specified destinations. These values are expressed in vph or in vehicles.
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| Turning Capacity The capacity associated with that component of the traffic stream which executes a specified turn maneuver from an approach at an intersection.
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| APPENDIX B DTRAD: Dynamic Traffic Assignment and Distribution Model
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| B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL This appendix describes the integrated dynamic trip assignment and distribution model named DTRAD (Dynamic TRaffic Assignment and Distribution) that is expressly designed for use in analyzing evacuation scenarios. DTRAD employs logitbased pathchoice principles and is one of the models of the DYNEV II System. The DTRAD module implements pathbased Dynamic Traffic Assignment (DTA) so that time dependent OriginDestination (OD) trips are assigned to routes over the network based on prevailing traffic conditions.
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| To apply the DYNEV II System, the analyst must specify the highway network, link capacity information, the timevarying volume of traffic generated at all origin centroids and, optionally, a set of accessible candidate destination nodes on the periphery of the Emergency Planning Zone (EPZ) for selected origins. DTRAD calculates the optimal dynamic trip distribution (i.e., trip destinations) and the optimal dynamic trip assignment (i.e., trip routing) of the traffic generated at each origin node traveling to its set of candidate destination nodes, so as to minimize evacuee travel cost.
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| B.1 Overview of Integrated Distribution and Assignment Model The underlying premise is that the selection of destinations and routes is intrinsically coupled in an evacuation scenario. That is, people in vehicles seek to travel out of an area of potential risk as rapidly as possible by selecting the best routes. The model is designed to identify these best routes in a manner that realistically distributes vehicles from origins to destinations and routes them over the highway network, in a consistent and optimal manner, reflecting evacuee behavior.
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| For each origin, a set of candidate destination nodes is selected by the software logic and by the analyst to reflect the desire by evacuees to travel away from the power plant and to access major highways. The specific destination nodes within this set that are selected by travelers and the selection of the connecting paths of travel, are both determined by DTRAD. This determination is made by a logitbased path choice model in DTRAD, so as to minimize the trip cost, as discussed later.
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| The traffic loading on the network and the consequent operational traffic environment of the network (density, speed, throughput on each link) vary over time as the evacuation takes place.
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| The DTRAD model, which is interfaced with the DYNEV simulation model, executes a succession of sessions wherein it computes the optimal routing and selection of destination nodes for the conditions that exist at that time.
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| B.2 Interfacing the DYNEV Simulation Model with DTRAD The DYNEV II system reflects Nuclear Regulatory Commission (NRC) guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. An algorithm was developed to support the DTRAD model in dynamically varying the Trip Table (O D matrix) over time from one DTRAD session to the next. Another algorithm executes a mapping from the specified geometric network (linknode analysis network) that represents the physical highway system, to a path network that represents the vehicle [turn]
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| movements. DTRAD computations are performed on the path network: DYNEV simulation model, on the geometric network.
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| B.2.1 DTRAD Description DTRAD is the DTA module for the DYNEV II System.
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| When the road network under study is large, multiple routing options are usually available between trip origins and destinations. The problem of loading traffic demands and propagating them over the network links is called Network Loading and is addressed by DYNEV II using macroscopic traffic simulation modeling. Traffic assignment deals with computing the distribution of the traffic over the road network for given OD demands and is a model of the route choice of the drivers. Travel demand changes significantly over time, and the road network may have time dependent characteristics, e.g., timevarying signal timing or reduced road capacity because of lane closure, or traffic congestion. To consider these time dependencies, DTA procedures are required.
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| The DTRAD DTA module represents the dynamic route choice behavior of drivers, using the specification of dynamic origindestination matrices as flow input. Drivers choose their routes through the network based on the travel cost they experience (as determined by the simulation model). This allows traffic to be distributed over the network according to the timedependent conditions. The modeling principles of DTRAD include:
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| It is assumed that drivers not only select the best route (i.e., lowest cost path) but some also select less attractive routes. The algorithm implemented by DTRAD archives several efficient routes for each OD pair from which the drivers choose.
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| The choice of one route out of a set of possible routes is an outcome of discrete choice modeling. Given a set of routes and their generalized costs, the percentages of drivers that choose each route is computed. The most prevalent model for discrete choice modeling is the logit model. DTRAD uses a variant of PathSizeLogit model (PSL). PSL overcomes the drawback of the traditional multinomial logit model by incorporating an additional deterministic path size correction term to address path overlapping in the random utility expression.
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| DTRAD executes the traffic assignment (TA) algorithm on an abstract network representation called "the path network" which is built from the actual physical link node analysis network. This execution continues until a stable situation is reached: the volumes and travel times on the edges of the path network do not change significantly from one iteration to the next. The criteria for this convergence are defined by the user.
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| Travel cost plays a crucial role in route choice. In DTRAD, path cost is a linear summation of the generalized cost of each link that comprises the path. The generalized cost for a link, a, is expressed as ca t a la s a ,
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| where is the generalized cost for link and , , and are cost coefficients for link travel time, distance, and supplemental cost, respectively. Distance and supplemental costs are defined as invariant properties of the network model, while travel time is a dynamic property dictated by prevailing traffic conditions. The DYNEV simulation model computes travel times on all edges in the network and DTRAD uses that information to constantly update the costs of paths. The route choice decision model in the next simulation iteration uses these updated values to adjust the route choice behavior. This way, traffic demands are dynamically reassigned based on time dependent conditions.
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| The interaction between the DTRAD traffic assignment and DYNEV II simulation models is depicted in Figure B1. Each round of interaction is called a Traffic Assignment Session (TA session). A TA session is composed of multiple iterations, marked as loop B in the figure.
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| The supplemental cost is based on the survival distribution (a variation of the exponential distribution). The Inverse Survival Function is a cost term in DTRAD to represent the potential risk of travel toward the plant:
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| sa = ln (p), 0 p l ; 0 p=
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| dn = Distance of node, n, from the plant d0 = Distance from the plant where there is zero risk
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| = Scaling factor The value of do = 13 miles, the outer distance of the EPZ. Note that the supplemental cost, sa, of link, a, is (high, low), if its downstream node, n, is (near, far from) the power plant.
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| B.2.2 Network Equilibrium In 1952, John Wardrop wrote:
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| Under equilibrium conditions traffic arranges itself in congested networks in such a way that no individual tripmaker can reduce his path costs by switching routes.
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| The above statement describes the User Equilibrium definition, also called the Selfish Driver Equilibrium. It is a hypothesis that represents a [hopeful] condition that evolves over time as drivers search out alternative routes to identify those routes that minimize their respective costs. It has been found that this equilibrium objective to minimize costs is largely realized by most drivers who routinely take the same trip over the same network at the same time (i.e.,
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| commuters). Effectively, such drivers learn which routes are best for them over time. Thus, the traffic environment settles down to a nearequilibrium state.
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| Clearly, since an emergency evacuation is a sudden, unique event, it does not constitute a long term learning experience which can achieve an equilibrium state. Consequently, DTRAD was not designed as an equilibrium solution, but to represent drivers in a new and unfamiliar situation, who respond in a flexible manner to realtime information (either broadcast or observed) in such a way as to minimize their respective costs of travel.
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| Start of next DTRAD Session A
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| Set T0 Clock time.
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| Archive System State at T0 Define latest Link Turn Percentages Execute Simulation Model from B time, T0 to T1 (burn time)
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| Provide DTRAD with link MOE at time, T1 Execute DTRAD iteration; Get new Turn Percentages Retrieve System State at T0 ;
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| Apply new Link Turn Percents DTRAD iteration converges?
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| No Yes Next iteration Simulate from T0 to T2 (DTA session duration)
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| Set Clock to T2 B A Figure B1. Flow Diagram of SimulationDTRAD Interface North Anna Power Station B5 KLD Engineering, P.C.
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| APPENDIX C DYNEV Traffic Simulation Model
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| C. DYNEV TRAFFIC SIMULATION MODEL This appendix describes the DYNEV traffic simulation model. The DYNEV traffic simulation model is a macroscopic model that describes the operations of traffic flow in terms of aggregate variables: vehicles, flow rate, mean speed, volume, density, queue length, on each link, for each turn movement, during each Time Interval (simulation time step). The model generates trips from sources and from Entry Links and introduces them onto the analysis network at rates specified by the analyst based on the mobilization time distributions. The model simulates the movements of all vehicles on all network links over time until the network is empty. At intervals, the model outputs Measures of Effectiveness (MOE) such as those listed in Table C1.
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| Model Features Include:
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| Explicit consideration is taken of the variation in density over the time step; an iterative procedure is employed to calculate an average density over the simulation time step for the purpose of computing a mean speed for moving vehicles.
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| Multiple turn movements can be serviced on one link; a separate algorithm is used to estimate the number of (fractional) lanes assigned to the vehicles performing each turn movement, based, in part, on the turn percentages provided by the Dynamic TRaffic Assignment and Distribution (DTRAD) model.
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| At any point in time, traffic flow on a link is subdivided into two classifications: queued and moving vehicles. The number of vehicles in each classification is computed. Vehicle spillback, stratified by turn movement for each network link, is explicitly considered and quantified. The propagation of stopping waves from link to link is computed within each time step of the simulation. There is no vertical stacking of queues on a link.
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| Any link can accommodate source flow from zones via side streets and parking facilities that are not explicitly represented. This flow represents the evacuating trips that are generated at the source.
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| The relation between the number of vehicles occupying the link and its storage capacity is monitored every time step for every link and for every turn movement. If the available storage capacity on a link is exceeded by the demand for service, then the simulator applies a metering rate to the entering traffic from both the upstream feeders and source node to ensure that the available storage capacity is not exceeded.
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| A path network that represents the specified traffic movements from each network link is constructed by the model; this path network is utilized by the DTRAD model.
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| A twoway interface with DTRAD: (1) provides link travel times; (2) receives data that translates into link turn percentages.
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| Provides MOE to animation software, EVacuation Animator (EVAN).
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| Calculates Evacuation Time Estimates (ETE) statistics.
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| All traffic simulation models are dataintensive. Table C2 outlines the necessary input data elements.
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| To provide an efficient framework for defining these specifications, the physical highway environment is represented as a network. The unidirectional links of the network represent roadway sections: rural, multilane, urban streets or freeways. The nodes of the network generally represent intersections or points along a section where a geometric property changes (e.g. a lane drop, change in grade or free flow speed).
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| Figure C1 is an example of a small network representation. The freeway is defined by the sequence of links, (20, 21), (21, 22), and (22, 23). Links (8001, 19) and (3, 8011) are Entry and Exit links, respectively. An arterial extends from node 3 to node 19 and is partially subsumed within a grid network. Note that links (21, 22) and (17, 19) are gradeseparated.
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| C.1 Methodology C.1.1 The Fundamental Diagram It is necessary to define the fundamental diagram describing flowdensity and speeddensity relationships. Rather than settling for a triangular representation, a more realistic representation that includes a capacity drop, (IR)Qmax, at the critical density when flow conditions enter the forced flow regime, is developed and calibrated for each link. This representation, shown in Figure C2, asserts a constant free speed up to a density, k , and then a linear reduction in speed in the range, k k k 45 vpm, the density at capacity. In the flowdensity plane, a quadratic relationship is prescribed in the range, k k 95 vpm which roughly represents the stopandgo condition of severe congestion. The value of flow rate, Q , corresponding to k , is approximated at 0.7 RQ . A linear relationship between k and k completes the diagram shown in Figure C2. Table C3 is a glossary of terms.
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| The fundamental diagram is applied to moving traffic on every link. The specified calibration values for each link are: (1) Free speed, v ; (2) Capacity, Q ; (3) Critical density, k 45 vpm ; (4) Capacity Drop Factor, R = 0.9 ; (5) Jam density, k . Then, v , k k
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| . Setting k k k , then Q RQ k for 0 k k 50 . It can be shown that Q 0.98 0.0056 k RQ for k k k , where k 50 and k 175.
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| C.1.2 The Simulation Model The simulation model solves a sequence of unit problems. Each unit problem computes the movement of traffic on a link, for each specified turn movement, over a specified time interval (TI) which serves as the simulation time step for all links. Figure C3 is a representation of the unit problem in the timedistance plane. Table C3 is a glossary of terms that are referenced in the following description of the unit problem procedure.
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| The formulation and the associated logic presented below are designed to solve the unit problem for each sweep over the network (discussed below), for each turn movement serviced on each link that comprises the evacuation network, and for each TI over the duration of the evacuation.
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| Given Q , M , L , TI , E , LN , G C , h , L , R , L , E , M Compute O , Q , M Define O O O O ; E E E
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| : 1. For the first sweep, s = 1, of this TI, get initial estimates of mean density, k , the R - factor, R and entering traffic, E , using the values computed for the final sweep of the prior TI.
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| For each subsequent sweep, s 1 , calculate E P O S where P , O are the relevant turn percentages from feeder link, i, and its total outflow (possibly metered) over this TI; S is the total source flow (possibly metered) during the current TI.
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| Set iteration counter, n = 0, k k , and E E .
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| : 2. Calculate v k such that k 130 using the analytical representations of the fundamental diagram.
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| Q TI G Calculate Cap C LN , in vehicles, this value may be reduced 3600 due to metering Set R 1.0 if G C 1 or if k k ; Set R 0.9 only if G C 1 and k k L
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| Calculate queue length, L Q LN
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| : 3. Calculate t TI . If t 0 , set t E O 0 ; Else, E E .
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| : 4. Then E E E ; t TI t
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| : 5. If Q Cap , then O Cap , O O 0 If t 0 , then Q Q M E Cap Else Q Q Cap End if Calculate Q and M using Algorithm A below
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| : 6. Else Q Cap O Q , RCap Cap O
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| : 7. If M RCap , then t Cap
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| : 8. If t 0, O M ,O min RCap M , 0 TI Q E O If Q 0 , then Calculate Q , M with Algorithm A North Anna Power Station C3 KLD Engineering, P.C.
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| Else Q 0, M E End if Else t 0 O M and O 0 M M O E; Q 0 End if
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| : 9. Else M O 0 If t 0 , then O RCap , Q M O E Calculate Q and M using Algorithm A
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| : 10. Else t 0 M M If M ,
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| O RCap Q M O Apply Algorithm A to calculate Q and M Else O M M M O E and Q 0 End if End if End if End if
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| : 11. Calculate a new estimate of average density, k k 2k k ,
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| where k = density at the beginning of the TI k = density at the end of the TI k = density at the midpoint of the TI All values of density apply only to the moving vehicles.
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| If k k and n N where N max number of iterations, and is a convergence criterion, then
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| : 12. set n n 1 , and return to step 2 to perform iteration, n, using k k .
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| End if Computation of unit problem is now complete. Check for excessive inflow causing spillback.
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| : 13. If Q M , then North Anna Power Station C4 KLD Engineering, P.C.
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| The number of excess vehicles that cause spillback is: SB Q M ,
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| where W is the width of the upstream intersection. To prevent spillback, meter the outflow from the feeder approaches and from the source flow, S, during this TI by the amount, SB. That is, set SB M 1 0 , where M is the metering factor over all movements .
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| E S This metering factor is assigned appropriately to all feeder links and to the source flow, to be applied during the next network sweep, discussed later.
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| Algorithm A This analysis addresses the flow environment over a TI during which moving vehicles can join a standing or discharging queue. For the case Qb vQ shown, Q Cap, with t 0 and a queue of Qe Qe length, Q , formed by that portion of M and E that reaches the stopbar within the TI, but could v not discharge due to inadequate capacity. That is, Mb Q M E . This queue length, Q v Q M E Cap can be extended to Q by L3 traffic entering the approach during the current TI, traveling at speed, v, and reaching the rear of the t1 t3 queue within the TI. A portion of the entering TI vehicles, E E , will likely join the queue. This analysis calculates t , Q and M for the input values of L, TI, v, E, t, L , LN, Q .
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| When t 0 and Q Cap:
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| L L Define: L Q . From the sketch, L v TI t t L Q E .
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| LN LN Substituting E E yields: vt E L v TI t L . Recognizing that the first two terms on the right hand side cancel, solve for t to obtain:
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| L t such that 0 t TI t E L v
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| TI LN If the denominator, v 0, set t TI t .
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| t t t Then, Q Q E , M E 1 TI TI The complete Algorithm A considers all flow scenarios; space limitation precludes its inclusion, here.
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| C.1.3 Lane Assignment The unit problem is solved for each turn movement on each link. Therefore, it is necessary to calculate a value, LN , of allocated lanes for each movement, x. If in fact all lanes are specified by, say, arrows painted on the pavement, either as full lanes or as lanes within a turn bay, then the problem is fully defined. If, however there remain unchannelized lanes on a link, then an analysis is undertaken to subdivide the number of these physical lanes into turn movement specific virtual lanes, LNx.
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| C.2 Implementation C.2.1 Computational Procedure The computational procedure for this model is shown in the form of a flow diagram as Figure C4. As discussed earlier, the simulation model processes traffic flow for each link independently over TI that the analyst specifies; it is usually 60 seconds or longer. The first step is to execute an algorithm to define the sequence in which the network links are processed so that as many links as possible are processed after their feeder links are processed, within the same network sweep. Since a general network will have many closed loops, it is not possible to guarantee that every link processed will have all of its feeder links processed earlier.
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| The processing then continues as a succession of time steps of duration, TI, until the simulation is completed. Within each time step, the processing performs a series of sweeps over all network links; this is necessary to ensure that the traffic flow is synchronous over the entire network. Specifically, the sweep ensures continuity of flow among all the network links; in the context of this model, this means that the values of E, M, and S are all defined for each link such that they represent the synchronous movement of traffic from each link to all of its outbound links. These sweeps also serve to compute the metering rates that control spillback.
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| Within each sweep, processing solves the unit problem for each turn movement on each link.
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| With the turn movement percentages for each link provided by the DTRAD model, an algorithm allocates the number of lanes to each movement serviced on each link. The timing at a signal, if any, applied at the downstream end of the link, is expressed as a G/C ratio, the signal timing needed to define this ratio is an input requirement for the model. The model also has the capability of representing, with macroscopic fidelity, the actions of actuated signals responding to the timevarying competing demands on the approaches to the intersection.
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| The solution of the unit problem yields the values of the number of vehicles, O, that discharge from the link over the time interval and the number of vehicles that remain on the link at the end of the time interval as stratified by queued and moving vehicles: Q and M . The procedure considers each movement separately (multipiping). After all network links are processed for a given network sweep, the updated consistent values of entering flows, E; metering rates, M; and source flows, S are defined so as to satisfy the no spillback condition.
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| The procedure then performs the unit problem solutions for all network links during the following sweep.
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| Experience has shown that the system converges (i.e. the values of E, M and S settle down for all network links) in just two sweeps if the network is entirely undersaturated or in four sweeps in the presence of extensive congestion with link spillback. (The initial sweep over each link uses the final values of E and M, of the prior TI). At the completion of the final sweep for a TI, the procedure computes and stores all MOEs for each link and turn movement for output purposes. It then prepares for the following time interval by defining the values of Q and M for the start of the next TI as being those values of Q and M at the end of the prior TI. In this manner, the simulation model processes the traffic flow over time until the end of the run.
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| Note that there is no spacediscretization other than the specification of network links.
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| C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD)
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| The DYNEV II system reflects Nuclear Regulatory Commission (NRC) guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. Thus, an algorithm was developed to identify an appropriate set of destination nodes for each origin based on its location and on the expected direction of travel. This algorithm also supports the DTRAD model in dynamically varying the Trip Table (OD matrix) over time from one DTRAD session to the next.
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| Figure B1 depicts the interaction of the simulation model with the DTRAD model in the DYNEV II system. As indicated, DYNEV II performs a succession of DTRAD sessions; each such session computes the turn link percentages for each link that remain constant for the session duration, T , T , specified by the analyst. The end product is the assignment of traffic volumes from each origin to paths connecting it with its destinations in such a way as to minimize the networkwide cost function. The output of the DTRAD model is a set of updated link turn percentages which represent this assignment of traffic.
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| As indicated in Figure B1, the simulation model supports the DTRAD session by providing it with operational link MOE that are needed by the path choice model and included in the DTRAD cost function. These MOE represent the operational state of the network at a time, T T , which lies within the session duration, T , T . This burn time, T T , is selected by the analyst. For each DTRAD iteration, the simulation model computes the change in network operations over this burn time using the latest set of link turn percentages computed by the DTRAD model. Upon convergence of the DTRAD iterative procedure, the simulation model accepts the latest turn percentages provided by the Dynamic Traffic Assignment (DTA) model, returns to the origin time, T , and executes until it arrives at the end of the DTRAD session duration at time, T . At this time the next DTA session is launched and the whole process repeats until the end of the DYNEV II run.
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| Additional details are presented in Appendix B.
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| Table C1. Selected Measures of Effectiveness Output by DYNEV II Measure Units Applies To Vehicles Discharged Vehicles Link, Network, Exit Link Speed Miles/Hours (mph) Link, Network Density Vehicles/Mile/Lane Link Level of Service LOS Link Content Vehicles Network Travel Time Vehiclehours Network Evacuated Vehicles Vehicles Network, Exit Link Trip Travel Time Vehicleminutes/trip Network Capacity Utilization Percent Exit Link Attraction Percent of total evacuating vehicles Exit Link Max Queue Vehicles Node, Approach Time of Max Queue Hours:minutes Node, Approach Length (mi); Mean Speed (mph); Travel Route Statistics Route Time (min)
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| Mean Travel Time Minutes Evacuation Trips; Network North Anna Power Station C8 KLD Engineering, P.C.
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| Table C2. Input Requirements for the DYNEV II Model HIGHWAY NETWORK Links defined by upstream and downstream node numbers Link lengths Number of lanes (up to 9) and channelization Turn bays (1 to 3 lanes)
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| Destination (exit) nodes Network topology defined in terms of downstream nodes for each receiving link Node Coordinates (X,Y)
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| Nuclear Power Plant Coordinates (X,Y)
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| GENERATED TRAFFIC VOLUMES On all entry links and source nodes (origins), by Time Period TRAFFIC CONTROL SPECIFICATIONS Traffic signals: linkspecific, turn movement specific Signal control treated as fixed time or actuated Location of traffic control points (these are represented as actuated signals)
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| Stop and Yield signs Rightturnonred (RTOR)
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| Route diversion specifications Turn restrictions Lane control (e.g. lane closure, movementspecific)
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| DRIVERS AND OPERATIONAL CHARACTERISTICS Drivers (vehiclespecific) response mechanisms: freeflow speed, discharge headway Bus route designation.
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| DYNAMIC TRAFFIC ASSIGNMENT Candidate destination nodes for each origin (optional)
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| Duration of DTA sessions Duration of simulation burn time Desired number of destination nodes per origin INCIDENTS Identify and Schedule of closed lanes Identify and Schedule of closed links North Anna Power Station C9 KLD Engineering, P.C.
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| Table C3. Glossary The maximum number of vehicles, of a particular movement, that can discharge Cap from a link within a time interval.
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| The number of vehicles, of a particular movement, that enter the link over the E
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| time interval. The portion, ETI, can reach the stopbar within the TI.
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| The green time: cycle time ratio that services the vehicles of a particular turn G/C movement on a link.
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| h The mean queue discharge headway, seconds.
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| k Density in vehicles per lane per mile.
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| The average density of moving vehicles of a particular movement over a TI, on a k
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| link.
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| L The length of the link in feet.
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| The queue length in feet of a particular movement, at the [beginning, end] of a L ,L time interval.
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| The number of lanes, expressed as a floating point number, allocated to service a LN particular movement on a link.
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| L The mean effective length of a queued vehicle including the vehicle spacing, feet.
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| M Metering factor (Multiplier): 1.
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| The number of moving vehicles on the link, of a particular movement, that are M ,M moving at the [beginning, end] of the time interval. These vehicles are assumed to be of equal spacing, over the length of link upstream of the queue.
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| The total number of vehicles of a particular movement that are discharged from a O
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| link over a time interval.
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| The components of the vehicles of a particular movement that are discharged from a link within a time interval: vehicles that were Queued at the beginning of O ,O ,O the TI; vehicles that were Moving within the link at the beginning of the TI; vehicles that Entered the link during the TI.
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| The percentage, expressed as a fraction, of the total flow on the link that P
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| executes a particular turn movement, x.
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| The number of queued vehicles on the link, of a particular turn movement, at the Q ,Q
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| [beginning, end] of the time interval.
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| in the absence of a control device. It is specified by the analyst as an estimate of link capacity, based upon a field survey, with reference to the Highway Capacity Manual (HCM) 2016.
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| R The factor that is applied to the capacity of a link to represent the capacity drop when the flow condition moves into the forced flow regime. The lower capacity at that point is equal to RQ .
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| RCap The remaining capacity available to service vehicles of a particular movement after that queue has been completely serviced, within a time interval, expressed as vehicles.
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| S Service rate for movement x, vehicles per hour (vph).
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| t Vehicles of a particular turn movement that enter a link over the first t seconds of a time interval, can reach the stopbar (in the absence of a queue down stream) within the same time interval.
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| TI The time interval, in seconds, which is used as the simulation time step.
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| v The mean speed of travel, in feet per second (fps) or miles per hour (mph), of moving vehicles on the link.
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| v The mean speed of the last vehicle in a queue that discharges from the link within the TI. This speed differs from the mean speed of moving vehicles, v.
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| W The width of the intersection in feet. This is the difference between the link length which extends from stopbar to stopbar and the block length.
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| 8011 8009 2 3 8104 8107 6 5 8008 8010 8 9 10 8007 8012 12 11 8006 8005 13 14 8014 15 25 8004 16 24 8024 17 8003 23 22 21 20 8002 Entry, Exit Nodes are 19 numbered 8xxx 8001 Figure C1. Representative Analysis Network North Anna Power Station C12 KLD Engineering, P.C.
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| Volume, vph Capacity Drop Qmax R Qmax Qs Density, vpm Flow Regimes Speed, mph Free Forced vf R vc Density, vpm kf kc kj ks Figure C2. Fundamental Diagrams Distance OQ OM OE Down Qb vQ Qe v
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| v L
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| Mb Me Up t1 t2 Time E1 E2 TI Figure C3. A UNIT Problem Configuration with t1 > 0 North Anna Power Station C13 KLD Engineering, P.C.
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| Sequence Network Links Next Timestep, of duration, TI A
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| Next sweep; Define E, M, S for all B
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| Links C Next Link D Next Turn Movement, x Get lanes, LNx Service Rate, Sx ; G/Cx Get inputs to Unit Problem:
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| Q b , Mb , E Solve Unit Problem: Q e , Me , O No D Last Movement ?
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| Yes No Last Link ? C Yes No B Last Sweep ?
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| Yes Calc., store all Link MOE Set up next TI :
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| No A Last Time - step ?
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| Yes DONE Figure C4. Flow of Simulation Processing (See Glossary: Table C3)
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| APPENDIX D Detailed Description of Study Procedure
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| D. DETAILED DESCRIPTION OF STUDY PROCEDURE This appendix describes the activities that were performed to compute Evacuation Time Estimates (ETE). The individual steps of this effort are represented as a flow diagram in Figure D1. Each numbered step in the description that follows corresponds to the numbered element in the flow diagram.
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| Step 1 The first activity was to obtain the Emergency Planning Zone (EPZ) boundary information and create a Geographic Information System (GIS) base map. The base map extends beyond the Shadow Region which extends approximately 15 miles (radially) from the power plant location.
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| The base map incorporates the local roadway topology, a suitable topographic background and the EPZ boundary and PAZ boundaries.
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| Step 2 The 2020 Census block information was obtained in GIS format. This information was used to estimate the permanent resident population within the EPZ and Shadow Region and to define the spatial distribution and demographic characteristics of the population within the study area. Transient, employment, and special facility data were obtained from Dominion Energy, the state and counties within the EPZ, and phone calls to individual facilities, supplemented with internet search where data was missing.
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| Step 3 A kickoff meeting was conducted with major stakeholders (state and county emergency management officials and Dominion Energy). The purpose of the kickoff meeting was to present an overview of the work effort, identify key agency personnel, and indicate the data requirements for the study. Specific requests for information were presented to the state and county emergency management officials. Unique features of the study area were discussed to identify the local concerns that should be addressed by the ETE study.
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| Step 4 Next, a physical survey of the roadway system in the study area was conducted to determine any changes to the roadway network since the previous study. This survey included consideration of the geometric properties of the highway sections, the channelization of lanes on each section of roadway, whether there are any turn restrictions or special treatment of traffic at intersections, the type and functioning of traffic control devices, gathering signal timings for pretimed traffic signals (if any exist within the study area), and to make the necessary observations needed to estimate realistic values of roadway capacity. Roadway characteristics were also verified using aerial imagery.
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| Step 5 A demographic survey of households within the EPZ was conducted to identify household dynamics, trip generation characteristics, and evacuationrelated demographic information of the EPZ population for this study. This information was used to determine important study North Anna Power Station D1 KLD Engineering, P.C.
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| factors including the average number of evacuating vehicles used by each household, and the time required to perform preevacuation mobilization activities.
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| Step 6 A computerized representation of the physical roadway system, called a linknode analysis network, was developed using the most recent UNITES software (see Section 1.3) developed by KLD. Once the geometry of the network was completed, the network was calibrated using the information gathered during the road survey (Step 4) and information obtained from aerial imagery. Estimates of highway capacity for each link and other linkspecific characteristics were introduced to the network description. Traffic signal timings were input accordingly. The link node analysis network was imported into a GIS map. The 2020 permanent resident population estimates (Step 2) were overlaid in the map, and origin centroids where trips would be generated during the evacuation process were assigned to appropriate links.
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| Step 7 The EPZ is subdivided into 25 PAZs. Based on wind direction and speed, Regions (groupings of PAZs) that may be advised to evacuate, were developed.
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| The need for evacuation can occur over a range of timeofday, dayofweek, seasonal and weatherrelated conditions. Scenarios were developed to capture the variation in evacuation demand, highway capacity and mobilization time, for different time of day, day of the week, time of year, and weather conditions.
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| Step 8 The input stream for the DYNEV II system, which integrates the dynamic traffic assignment and distribution model, DTRAD, with the evacuation simulation model, was created for a prototype evacuation case - the evacuation of the entire EPZ for a representative scenario.
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| Step 9 After creating this input stream, the DYNEV II System was executed on the prototype evacuation case to compute evacuating traffic routing patterns consistent with the appropriate NRC guidelines. DYNEV II contains an extensive suite of data diagnostics which check the completeness and consistency of the input data specified. The analyst reviews all warning and error messages produced by the model and then corrects the database to create an input stream that properly executes to completion.
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| The model assigns destinations to all origin centroids consistent with a (general) radial evacuation of the EPZ and Shadow Region. The analyst may optionally supplement and/or replace these modelassigned destinations, based on professional judgment, after studying the topology of the analysis highway network. The model produces link and networkwide measures of effectiveness as well as estimates of evacuation time.
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| Step 10 The results generated by the prototype evacuation case are critically examined. The examination includes observing the animated graphics (using the EVAN software - See Section 1.3) and reviewing the statistics output by the model. This is a laborintensive activity, requiring the direct participation of skilled engineers who possess the necessary practical experience to interpret the results and to determine the causes of any problems reflected in the results.
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| Essentially, the approach is to identify those bottlenecks in the network that represent locations where congested conditions are pronounced and to identify the cause of this congestion. This cause can take many forms, either as excess demand due to high rates of trip generation, improper routing, a shortfall of capacity, or as a quantitative flaw in the way the physical system was represented in the input stream. This examination leads to one of two conclusions:
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| The results are satisfactory; or The input stream must be modified accordingly.
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| This decision requires, of course, the application of the user's judgment and experience based upon the results obtained in previous applications of the model and a comparison of the results of the latest prototype evacuation case iteration with the previous ones. If the results are satisfactory in the opinion of the user, then the process continues with Step 13. Otherwise, proceed to Step 11.
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| Step 11 There are many "treatments" available to the user in resolving apparent problems. These treatments range from decisions to reroute the traffic by assigning additional evacuation destinations for one or more sources, imposing turn restrictions where they can produce significant improvements in capacity, changing the control treatment at critical intersections so as to provide improved service for one or more movements, or adding minor routes (which are paved and traversable) that were not previously modelled but may assist in the evacuation and increase the available roadway network capacity, or in prescribing specific treatments for channelizing the flow so as to expedite the movement of traffic along major roadway systems.
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| Such "treatments" take the form of modifications to the original prototype evacuation case input stream. All treatments are designed to improve the representation of evacuation behavior.
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| Step 12 As noted above, the changes to the input stream must be implemented to reflect the modifications undertaken in Step 11. At the completion of this activity, the process returns to Step 9 where the DYNEV II System is again executed.
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| Step 13 Evacuation of transitdependent evacuees and special facilities are included in the evacuation analysis. Fixed routing for transit buses, school buses, ambulances, and other transit vehicles are introduced into the final prototype evacuation case data set. DYNEV II generates route North Anna Power Station D3 KLD Engineering, P.C.
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| specific speeds over time for use in the estimation of evacuation times for the transit dependent and special facility population groups.
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| Step 14 The prototype evacuation case was used as the basis for generating all region and scenario specific evacuation cases to be simulated. This process was automated through the UNITES user interface. For each specific case, the population to be evacuated, the trip generation distributions, the highway capacity and speeds, and other factors are adjusted to produce a customized casespecific data set.
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| Step 15 All evacuation cases are executed using the DYNEV II System to compute ETE. Once results are available, quality control procedures are used to assure the results are consistent, dynamic routing is reasonable, and traffic congestion/bottlenecks are addressed properly. Traffic management plans are analyzed, and traffic control points are prioritized, if applicable.
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| Additional analysis is conducted to identify the sensitivity of the ETE to change in some base evacuation conditions and model assumptions.
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| Step 16 Once vehicular evacuation results are accepted, average travel speeds for transit and special facility routes are used to compute ETE for transitdependent permanent residents, schools, medical facilities, and other special facilities.
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| Step 17 The simulation results are analyzed, tabulated, and graphed. The results are then documented, as required by NUREG/CR7002, Rev.1.
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| Step 18 Following the completion of documentation activities, the ETE criteria checklist (see Appendix N) is completed. An appropriate report reference is provided for each criterion provided in the checklist.
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| A Step 10 Examine Prototype Evacuation Case using EVAN Step 1 and Create GIS Base Map DYNEV II Output Step 2 Results Satisfactory Gather Census Block and Demographic Data for Step 11 Study Area.
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| Modify Evacuation Destinations and/or Develop Step 3 Traffic Control Treatments Conduct Kickoff Meeting with Stakeholders Step 12 Modify Database to Reflect Changes to Prototype Evacuation Case Field Survey of Roadways within Study Area Step 5 B Conduct and Analyze Demographic Survey and Step 13 Develop Trip Generation Characteristics Establish Transit and Special Facility Evacuation Step 6 Routes and Update DYNEVII Database Update and Calibrate LinkNode Analysis Step 14 Network Step 7 Generate DYNEVII Input Streams for All Evacuation Cases Develop Evacuation Regions and Scenarios Step 15 Step 8 Use DYNEVII to Simulate All Evacuation Cases and Compute ETE Create and Debug DYNEVII Input Stream Step 16 Use DYNEVII Results to Estimate Transit and Step 9 Special Facilities Evacuation Time Estimates B Execute DYNEV II for Prototype Evacuation Case Step 17 Documentation A Step 18 Complete ETE Criteria Checklist Figure D1. Flow Diagram of Activities North Anna Power Station D5 KLD Engineering, P.C.
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| APPENDIX E Special Facility Data
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| E. SPECIAL FACILITY DATA The following tables list population information, as of June 2022, for special facilities that are located within the NAPS EPZ. Special facilities are defined as schools, preschools, and medical facilities. Transient population data is included in the tables for recreational areas (campgrounds, marinas, parks) and lodging facilities. Summer seasonal transients along the shores of Lake Anna were determined using 2020 U.S. Census data and are not discussed in this section; Section 3.3.1 provides information for this transient population group. Employment data is included in the table for major employers. Each table is grouped by county. The location of the facility is defined by its straightline distance (miles) and direction (magnetic bearing) from the center point of the plant. Maps of each school, preschool, medical facility, major employer, recreational area (campground, marina, park) and lodging facility are also provided.
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| Table E1. Schools and Preschools within the EPZ Distance Dire Enroll PAZ (miles) ction School Name Street Address Municipality ment LOUISA COUNTY 2 7.2 WSW Mineral Christian Preschool 51 Louisa Ave Mineral 60 3 7.8 WSW Louisa County High School 757 Davis Hwy Louisa 1,510 3 7.9 WSW Louisa County Middle School 1009 Davis Hwy Mineral 1,191 3 10.5 WSW Thomas Jefferson Elementary School 1782 Jefferson Hwy Louisa 587 5 11.6 SSW Jouett Elementary School 315 Jouett School Rd Mineral 575 Louisa County Subtotal: 3,923 SPOTSYLVANIA COUNTY 12 5.2 NNE Livingston Elementary 6057 Courthouse Rd Spotsylvania 393 21 9.7 NE Post Oak Middle School 6959 Courthouse Rd Spotsylvania 700 21 10.1 NE Spotsylvania High School 6975 Courthouse Rd Spotsylvania 1,300 21 10.1 NE Spotsylvania High School Governor's School 6975 Courthouse Rd Spotsylvania 60 21 10.3 ENE Berkeley Elementary 5979 Partlow Rd Spotsylvania 269 Spotsylvania County Subtotal: 2,722 EPZ TOTAL: 6,645 Table E2. Medical Facilities within the EPZ Ambul Wheel Bed Distance Dire Cap Current atory chair ridden PAZ (miles) ction Facility Name Street Address Municipality acity Census Patients Patients Patients SPOTSYLVANIA COUNTY 12 3.3 NNE Lake Anna Elder Care Inc 5232 Lewiston Rd Bumpass 8 8 0 0 8 Spotsylvania County Subtotal: 8 8 0 0 8 EPZ TOTAL: 8 8 0 0 8 North Anna Power Station E2 KLD Engineering, P.C.
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| Table E3. Major Employers within the EPZ
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| % Employee Employees Employees Vehicles Distance Dire Employees Commuting Commuting Commuting PAZ (miles) ction Facility Name Street Address Municipality (Max Shift) into the EPZ into the EPZ into the EPZ LOUISA COUNTY 8 North Anna Power Station State Hwy 700 & State Hwy 652 Mineral 762 77.6% 591 537 Louisa County Subtotal: 762 591 537 EPZ TOTAL: 762 591 537 Table E4. Recreational Areas within the EPZ Distance Dire PAZ (miles) ction Facility Name Street Address Municipality Facility Type Transients Vehicles LOUISA COUNTY 15 2.5 NW Lake Anna Yacht Club 200 Lake Front Dr Suite 203 Mineral Marina 255 141 16 6.0 WNW Christopher Run Campground 6478 Zachary Taylor Hwy Mineral Campground 2,000 800 25 5.4 SE Pleasant Landing at Lake Anna 349 Pleasant Landing Rd Bumpass Marina 203 140 Louisa County Subtotal: 2,458 1,081 SPOTSYLVANIA COUNTY 9 1.4 NNE Lake Anna Marina 4303 Boggs Dr Bumpass Marina 175 120 11 2.1 E Duke's Creek Marina 3831 Breaknock Rd Bumpass Marina 125 45 12 2.0 N Sturgeon Creek Marina 5107 Courthouse Rd Spotsylvania Marina 150 50 12 2.2 NNE Rocky Branch Marina & Campground 5153 Courthouse Rd Spotsylvania Marina 125 60 14 2.2 NW Highpoint Marina 4634 Courthouse Rd Mineral Marina 390 195 14 2.3 NNW Anna Point Marina 13721 Anna Point Ln Mineral Marina 175 60 14 4.0 NNW Lake Anna State Park 6800 Lawyers Rd Spotsylvania Park 2,000 580 14 4.0 NNW Lake Anna State Park (Campground) 6800 Lawyers Rd Spotsylvania Campground 368 130 18 6.7 NW Hunter's Landing 6320 Belmont Rd (Route 719) Mineral Marina 90 35 18 8.1 NW Heron Pointe Marina 15908 Days Bridge Rd Mineral Marina 20 10 Spotsylvania County Subtotal: 3,618 1,285 EPZ TOTAL: 6,076 2,366 North Anna Power Station E3 KLD Engineering, P.C.
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| Table E5. Lodging Facilities within the EPZ Distance Dire PAZ (miles) ction Facility Name Street Address Municipality Transients Vehicles LOUISA COUNTY 2 7.7 WSW Dunnlora Inn 903 Mineral Ave Mineral 9 5 Louisa County Subtotal: 9 5 SPOTSYLVANIA COUNTY 13 2.3 N Lake Anna Lodge 5152 Courthouse Rd Spotsylvania 35 27 14 2.2 NNW Lighthouse Inn 4634 Courthouse Rd Mineral 28 14 Spotsylvania County Subtotal: 63 41 EPZ TOTAL: 72 46 North Anna Power Station E4 KLD Engineering, P.C.
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| Figure E1. Schools and Preschools within the EPZ North Anna Power Station E5 KLD Engineering, P.C.
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| Figure E2. Medical Facilities within the EPZ North Anna Power Station E6 KLD Engineering, P.C.
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| Figure E3. Major Employers within the EPZ North Anna Power Station E7 KLD Engineering, P.C.
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| Figure E4. Recreational Areas within the EPZ North Anna Power Station E8 KLD Engineering, P.C.
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| Figure E5. Lodging Facilities within the EPZ North Anna Power Station E9 KLD Engineering, P.C.
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| APPENDIX F Demographic Survey
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| F. DEMOGRAPHIC SURVEY F.1 Introduction The development of ETE for the North Anna Power Station (NAPS) EPZ requires the identification of travel patterns, car ownership and household size of the population within the EPZ.
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| Demographic information can be obtained from Census data; however, the use of this data has several limitations when applied to emergency planning. First, the Census data do not encompass the range of information needed to identify the time required for preliminary activities (mobilization) that must be undertaken prior to evacuating the area. Secondly, Census data do not contain attitudinal responses needed from the population of the EPZ and consequently may not accurately represent the anticipated behavioral characteristics of the evacuating populace.
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| These concerns are addressed by conducting a demographic survey of a representative sample of the EPZ population. The survey is designed to elicit information from the public concerning family demographics and estimates of response times to well defined events. The design of the survey includes a limited number of questions of the form What would you do if ? and other questions regarding activities with which the respondent is familiar (How long does it take you to?)
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| F.2 Survey Instrument and Sampling Plan Attachment A presents the final survey instrument used in this study. A draft of the instrument was submitted to stakeholders for comment. Comments were received and the survey instrument was modified accordingly, prior to conducting the survey.
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| Following the completion of the instrument, a sampling plan was developed. A sample size of approximately 379 completed survey forms yields results with a sampling error of about +/-5.0%
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| at the 95% confidence level. Ideally, the sample should be drawn from the EPZ population.
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| Consequently, a list of zip codes in the EPZ was developed using geographic information system (GIS) software. This list is shown in Table F1. Along with each zip code, an estimate of the population and number of households in each area was determined by overlaying 2010 Census data (when the survey began in early 2021, 2020 Census data had not yet been released), 2020 Census data (once released) and the EPZ boundary, again using GIS software. The proportional number of desired completed survey interviews for each area was identified, as shown in Table F1. Note that the average household size computed in Table F1 was an estimate for sampling purposes and was not used in the ETE study.
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| The number of samples obtained was less than the desired sampling plan despite a good faith effort put forward by the offsite response organizations (OROs) and Dominion Energy. A total of 264 completed samples were obtained from zip codes within 15 miles of NAPS corresponding to a sampling error of +/-6.0% at the 95% confidence level based on the 2020 Census data. Table F1 shows the number of samples obtained within each zip code.
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| F.3 Survey Results The results of the survey fall into two categories. First, the household demographics of the area can be identified. Demographic information includes such factors as household size, automobile ownership, and automobile availability. The distributions of the time to perform certain pre evacuation activities are the second category of survey results. These data are processed to develop the trip generation distributions used in the evacuation modeling effort, as discussed in Section 5.
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| A review of the survey instrument reveals that several questions have a decline to state entry for a response. It is accepted practice in conducting surveys of this type to accept the answers of a respondent who offers a decline to state response for a few questions or who refuses to answer a few questions. To address the issue of occasional decline to state responses from a large sample, the practice is to assume that the distribution of these responses is the same as the underlying distribution of the positive responses. In effect, the decline to state responses are ignored, and the distributions are based upon the positive data that is acquired.
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| F.3.1 Household Demographic Results Household Size Figure F1 presents the distribution of household size within the EPZ, based on the responses to the demographic survey. The average household contains 2.90 people. The estimated household size for the whole study area (2.67 persons) used to determine the survey sample (Table F1) was drawn from the 2020 Census data. The difference between the Census data and survey data is 8.6%, which exceeds the sampling error of 6.0%. Dominion Energy and the OROs agreed to use the results from the demographic survey for the ETE study. A sensitivity study was conducted to determine the impact of the average household size on ETE. See Appendix M, Table M4.
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| Automobile Ownership The average number of automobiles available per household in the EPZ is 2.61. It should be noted that all households in the EPZ have access to an automobile according to the demographic survey.
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| The distribution of automobile ownership is presented in Figure F2. Figure F3 presents the automobile availability by household size.
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| Ridesharing Approximately 77% of households surveyed responded that they would share a ride with a neighbor, relative, or a friend if a car was not available to them when advised to evacuate in the event of an emergency. Figure F4 presents this response.
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| Commuters Figure F5 presents the distribution of the number of commuters in each household. Commuters are defined as household members who travel to work or college on a daily basis. The data shows an average of 1.34 commuters per household in the EPZ, and approximately 73% of households have at least one commuter.
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| Commuter Travel Modes Figure F6 presents the mode of travel that commuters use on a daily basis. The vast majority of commuters use their private automobiles to travel to work. The data shows an average of 1.10 employees per vehicle, assuming 2 people per vehicle - on average - for carpools.
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| Impact of COVID19 on Commuters Figure F7 presents the distribution of the number of commuters in each household that were temporarily impacted by the COVID19 pandemic. Approximately 40% of households indicated someone in their household had a work and/or school commute that was temporarily impacted by the COVID19 pandemic. Considering a minority of the commuter households surveyed were impacted by COVID19, we do not compare commuter mobilization times in this study with the results from the previous study.
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| Functional or Transportation Needs Figure F8 presents the distribution of the number of individuals with functional or transportation needs. The responses indicate that 13 households (approximately 5% of those surveyed) have functional or transportation needs, with 29 people in those households who would need assistance in an emergency evacuation. The responses from households with functional or transportation needs indicated that 17 people require a bus, 1 person requires a medical bus/van, 4 people require a wheelchair accessible van, nobody requires an ambulance, and 7 people would need other functional or transportation needs.
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| Seasonal Residents Approximately 8% (20 households) of the households surveyed indicated they have seasonal residents as shown in Figure F9. As shown in Figure F10, 35% stated that 1 household member is considered a seasonal resident; 30% have 2 seasonal residents; and 35% have 3 or more seasonal residents. Approximately 75% of the households surveyed indicated that they have seasonal residents during the summer season while the remaining 25% declined to state.
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| F.3.2 Evacuation Response Several questions were asked to gauge the populations response to an emergency. These are now discussed:
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| How many of the vehicles would your household use during an evacuation? The response is shown in Figure F11. On average, evacuating households would use 1.64 vehicles.
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| Would your family await the return of other family members prior to evacuating the area?
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| Of the survey participants who responded, 45.67% said they would await the return of other family members before evacuating and 54.33% indicated that they would not await the return of other family members, as shown in Figure F12.
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| If you had a household pet, would you take your pet with you if you were asked to evacuate the area? Based on responses from the survey, approximately 73% of households have a family pet. Of the households with pets, approximately 16% indicated that they would take their pets North Anna Power Station F3 KLD Engineering, P.C.
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| with them to a shelter, approximately 81% indicated that they would take their pets somewhere else and approximately 3% would leave their pet at home. Of the households with pets, approximately 89% indicated that they have sufficient room in their vehicle to evacuate with their pet(s)/animal(s); the remaining 11% do not have room or would need to use a trailer.
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| What type of pet(s) and/or animal(s) do you have? Based on responses from the survey, approximately 80% have a household pet (dog, cat, etc.), approximately 16% of households have farm animals (horse, chicken, etc.), approximately 3% have other small pets/animals, and approximately 1% have other large pets/animals.
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| Emergency officials advise you to take shelter at home in an emergency. Would you? This question is designed to elicit information regarding compliance with instructions to shelter in place. The results, as shown in Figure F13, indicate that 82.19% of households who are advised to shelter in place would do so; the remaining 17.81% would choose to evacuate the area. Note the baseline ETE study assumes 20% of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR7002, Rev. 1. Thus, the data obtained through the survey is in good agreement with the federal guidance recommendation. A sensitivity study was conducted to estimate the impact of shadow evacuation noncompliance of shelter advisory on ETE - see Table M2 in Appendix M.
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| Emergency officials advise you to take shelter at home now in an emergency and possibly evacuate later while people in other areas are advised to evacuate now. Would you? This question is designed to elicit information specifically related to the possibility of a staged evacuation. That is, asking a population to shelter in place now and then to evacuate after a specified period of time. As shown in Figure F14, the results indicate that 55.42% of households would follow instructions and delay the start of evacuation until so advised, while the balance of 44.58% would choose to begin evacuating immediately.
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| Emergency officials advise you to evacuate due to an emergency. Where would you evacuate to? This question is designed to elicit information regarding the destination of evacuees in case of an evacuation. As shown in Figure F15, 44.40% of households indicated that they would evacuate to a friend or relatives home, 6.95% to an evacuation assembly center, 21.24% to a hotel, motel or campground, 5.79% to a second or seasonal home, 0.77% of people indicated they would not evacuate, and the remaining 20.85% of people answered other/dont know.
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| F.3.3 Time Distribution Results The survey asked several questions about the amount of time it takes to perform certain pre evacuation activities. These activities involve actions taken by residents during the course of their daytoday lives. Thus, the answers fall within the realm of the responders experience.
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| The mobilization distributions provided below are the result of having applied the analysis described in Section 5.4.1 on the component activities of the mobilization.
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| How long does it take the commuter to complete preparation for leaving work? Figure F16 presents the cumulative distribution; in all cases, the activity is completed by about 75 minutes.
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| Approximately, 85% can leave within 30 minutes.
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| How long would it take the commuter to travel home? Figure F17 presents the work to home travel time for the EPZ. About 82% of commuters can arrive home within about 60 minutes of leaving work; all within 120 minutes.
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| How long would it take the family to pack clothing, secure the house, and load the car? Figure F18 presents the time required to prepare for leaving on an evacuation trip. In many ways this activity mimics a familys preparation for a short holiday or weekend away from home. Hence, the responses represent the experience of the responder in performing similar activities.
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| The distribution shown in Figure F18 has a long tail. About 86% of households can be ready to leave home within 120 minutes; the remaining households require up to an additional hour and 15 minutes.
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| How long would it take you to clear 6 to 8 inches of snow from your driveway? During heavy snow conditions, an additional activity must be performed before residents can depart on the evacuation trip. Although snow scenarios assume that the roads and highways have been plowed and are passable (albeit at lower speeds and capacities), it may be necessary to clear a private driveway prior to leaving the home so that the vehicle can access the street.
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| Approximately 24% of households said they will not shovel the driveway prior to evacuation; therefore, those households will have zero shovel time. Figure F19 presents the time distribution for removing 6 to 8 inches of snow from a driveway. Approximately 71% of households can have their driveway passable within one hour; the remaining 29% of households would require up to an additional two hours to begin their evacuation trip.
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| F.3.4 Emergency Communications At your place of residence, how reliable is your cell phone signal? This question is designed to elicit information regarding the ability to be notified in case of an evacuation.
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| 68.94% of households indicated that they have very reliable signal to receive texts and phone calls, 8.71% indicated that their signal is reliable for text messages only, 21.21% indicated that they do not always receive cell communications at their residence, and remaining 1.14% do not have cell service at their residence, as shown in Figure F20.
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| Emergency management officials in your state may send text messages, similar to AMBER Alerts, with emergency directions for the public during a radiological emergency at the North Anna Power Station. How likely would you be to take actions on these directions, if you received the message? This question is designed to elicit information regarding the likelihood of an individual to take action based on emergency management officials guidelines.
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| 72.73% of households indicated that they are highly likely to take action on these directions, 23.86% indicated likely, 3.03% indicated neither likely nor unlikely (neutral), and 0.38% indicated unlikely, and none (0%) indicated highly unlikely to take action on emergency management officials directions as shown in Figure F21.
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| Which of the following emergency communication methods do you think is most likely to alert you at your residence? This question is designed to elicit information regarding the most efficient way to alert residents within the study area.
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| 19.28% of households indicated that a siren sounding near their home would be the most likely method to alert them at their residence, 39.93% indicated that a text message from emergency officials would be the most likely method, 20.14% indicated an alert broadcast on the TV or radio, 7.40% indicated that information on Twitter or Facebook would be the most likely way to be alerted, 12.05% indicated that a phone call/text message from a family member, friend or neighbor would be the most likely way to alert them at their residence, and 1.20% by other methods, as shown in Figure F22.
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| Table F1. North Anna Power Station Demographic Survey Sampling Plan and Results 2010 EPZ 2010 EPZ 2020 EPZ 2020 EPZ Population Desired Achieved Zip Code Households in Population Households in Zip Samples Sample Zip Code in Zip Code in Zip Code Code EPZ 22534 2,796 916 2949 1007 37 9 22546 72 27 56 27 1 5 22551 6,332 2,222 6914 2470 89 40 22567 18 5 28 2 1 7 22960 456 170 579 205 7 36 23015 1,775 620 1726 641 25 26 23024 4788 1875 5332 2107 75 25 23093 1705 647 1780 705 26 12 23117 7260 2932 8125 3385 118 58 EPZ Total: 25,202 9,414 27,489 10,549 379 218 Shadow 22546 7392 2628 8866 3162 22551 8590 2984 9660 3432 22567 1734 606 1906 696 22960 573 223 651 244 Included 23015 987 370 1022 389 in EPZ1 23024 1271 488 1405 540 23093 5427 2141 6296 2496 N/A 23117 937 341 943 354 22508 660 227 674 241 14 22542 148 51 169 64 5 22553 1447 505 2045 752 17 22580 1492 527 1484 538 1 23192 1289 473 1243 481 9 Shadow Total: 31,947 11,564 36,364 13,389 0 46 Total: 57,149 20,978 63,853 23,938 379 264 Average 2.72 2.67 Household Size:
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| 1 Some zip codes are located within the EPZ boundary as well as the Shadow Region boundary therefore the samples achieved were only listed once to avoid double counting.
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| Household Size 50%
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| 44.11%
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| 40%
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| Percent of Households 30%
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| 20% 16.35%
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| 15.97%
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| 9.89%
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| 10%
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| 6.84% 6.84%
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| 0%
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| 1 2 3 4 5 6+
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| People Figure F1. Household Size in the EPZ Vehicle Availability 50%
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| 42.15%
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| 40%
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| Percent of Households 32.95%
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| 30%
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| 20%
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| 9.96% 9.58%
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| 10%
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| 5.36%
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| 0.00%
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| 0%
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| 0 1 2 3 4 5+
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| Vehicles Figure F2. Household Vehicle Availability North Anna Power Station F8 KLD Engineering, P.C.
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| Distribution of Vehicles by HH Size 16+ Person Households 1 Person 2 People 3 People 4 People 5 People 6+ People 100%
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| 80%
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| Percent of Households 60%
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| 40%
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| 20%
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| 0%
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| 1 2 3 4 5+
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| Vehicles Figure F3. Vehicle Availability 1 to 6+ Person Households Rideshare with Neighbor/Friend 100%
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| 80% 77.17%
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| Percent of Households 60%
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| 40%
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| 22.83%
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| 20%
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| 0%
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| Yes No Figure F4. Household Ridesharing Preference North Anna Power Station F9 KLD Engineering, P.C.
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| Commuters Per Household 50%
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| 40%
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| Percent of Households 27.4% 30.9%
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| 27.8%
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| 30%
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| 20%
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| 7.7%
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| 10%
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| 6.2%
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| 0%
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| 0 1 2 3 4+
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| Commuters Figure F5. Commuters in Households in the EPZ Travel Mode to Work 100%
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| 85.81%
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| 80%
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| Percent of Commuters 60%
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| 40%
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| 20%
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| 10.00%
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| 2.26% 1.61% 0.32%
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| 0%
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| Rail Bus Walk/Bike Drive Alone Carpool (2+)
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| Mode of Travel Figure F6. Modes of Travel in the EPZ North Anna Power Station F10 KLD Engineering, P.C.
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| COVID19 Impact to Commuters 70%
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| 59.68%
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| 60%
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| 50%
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| Percent of Households 40%
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| 30%
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| 24.51%
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| 20%
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| 9.09%
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| 10%
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| 3.16% 3.56%
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| 0%
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| 0 1 2 3 4+
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| Commuters Figure F7. Impact to Commuters due to COVID19 Pandemic Functional or Transportation Needs 18 17 16 14 12 Number of People 10 8 7 6
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| 4 4
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| 2 1
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| 0 0
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| Bus Medical Bus/Van Wheelchair Ambulance Other Accessible Vehicle Figure F8. Households with Functional or Transportation Needs North Anna Power Station F11 KLD Engineering, P.C.
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| Seasonal Residents 100%
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| 92.31%
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| 80%
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| Percent of Households 60%
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| 40%
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| 20%
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| 7.69%
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| 0%
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| Yes No Figure F9. Seasonal Residents in the EPZ Seasonal Residents Per Household 40%
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| 35.0%
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| 30.0%
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| 30%
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| Percent of Households 20%
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| 15.0% 15.0%
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| 10%
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| 5.0%
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| 0.0%
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| 0%
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| 1 2 3 4 5 6 People Figure F10. Seasonal Residents Per Household North Anna Power Station F12 KLD Engineering, P.C.
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| Evacuating Vehicles Per Household 60%
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| 47.50%
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| 50%
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| Percent of Households 43.30%
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| 40%
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| 30%
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| 20%
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| 9.20%
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| 10%
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| 0.00%
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| 0%
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| 0 1 2 3+
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| Vehicles Figure F11. Number of Vehicles Used for Evacuation Await Returning Commuter 60%
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| 54.33%
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| 50%
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| 45.67%
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| Percent of Households 40%
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| 30%
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| 20%
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| 10%
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| 0%
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| Yes, would await return No, would evacuate Figure F12. Percent of Households that Await Returning Commuter Before Leaving North Anna Power Station F13 KLD Engineering, P.C.
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| Shelter in Place Characteristics 100%
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| 82.19%
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| Percent of Households 80%
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| 60%
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| 40%
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| 17.81%
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| 20%
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| 0%
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| Shelter Evacuate Figure F13. Shelter in Place Characteristics Shelter then Evacuate Characteristics 100%
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| 80%
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| Percent of Households 55.42%
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| 60%
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| 44.58%
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| 40%
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| 20%
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| 0%
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| Shelter, then Evacuate Evacuate Immediately Figure F14. Shelter in Place Characteristics - Staged Evacuation North Anna Power Station F14 KLD Engineering, P.C.
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| Evacuation Destinations 50%
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| 44.40%
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| 40%
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| Percent of Households 30%
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| 21.24% 20.85%
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| 20%
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| 10% 6.95% 5.79%
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| 0.77%
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| 0%
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| Friend/Relative's Evacuation Hotel, Motel, or Second/Seasonal Would not Other/Don't Know Home Assembly Center Campground Home Evacuate Figure F15. Study Area Evacuation Destinations Time to Prepare to Leave Work/College 100%
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| 80%
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| Percent of Commuters 60%
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| 40%
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| 20%
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| 0%
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| 0 15 30 45 60 75 Preparation Time (min)
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| Figure F16. Time Required to Prepare to Leave Work/College North Anna Power Station F15 KLD Engineering, P.C.
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| Time to Commute Home From Work/College 100%
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| 80%
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| Percent of Commuters 60%
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| 40%
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| 20%
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| 0%
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| 0 15 30 45 60 75 90 105 120 Travel Time (min)
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| Figure F17. Time to Commute Home from Work/College Time to Prepare to Leave Home 100%
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| 80%
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| Percent of Households 60%
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| 40%
| |
| 20%
| |
| 0%
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| 0 15 30 45 60 75 90 105 120 135 150 165 180 195 Preparation Time (min)
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| Figure F18. Time to Prepare Home for Evacuation North Anna Power Station F16 KLD Engineering, P.C.
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| Time to Remove Snow from Driveway 100%
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| 80%
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| Percent of Households 60%
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| 40%
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| 20%
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| 0%
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| 0 30 60 90 120 150 180 Time (min)
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| Figure F19. Time to Remove 68 of Snow from Driveway Cell Phone Signal Reliability 100%
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| 80%
| |
| 68.94%
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| Percent of Households 60%
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| 40%
| |
| 21.21%
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| 20%
| |
| 8.71%
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| 1.14%
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| 0%
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| VERY RELIABLE TO RELIABLE FOR TEXT I DO NOT ALWAYS I DO NOT HAVE CELL RECEIVE TEXTS AND MESSAGES ONLY RECEIVE CELL SERVICE AT MY PHONE CALLS COMMUNICATIONS AT RESIDENCE MY RESIDENCE Figure F20. Cell Phone Signal Reliability (for Phone Calls and/or Text Messages North Anna Power Station F17 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Likelihood to Take Action Based off Guidelines 100%
| |
| 80%
| |
| 72.73%
| |
| Percent of Households 60%
| |
| 40%
| |
| 23.86%
| |
| 20%
| |
| 3.03%
| |
| 0.38% 0.00%
| |
| 0%
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| HIGHLY LIKELY LIKELY NEITHER LIKELY UNLIKELY HIGHLY UNLIKELY NOR UNLIKELY Figure F21. Residents Compliance to Given Instruction (by Emergency Officials)
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| Perception of Public Alert Method 60%
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| Percent of Households 39.93%
| |
| 40%
| |
| 19.28%
| |
| 20%
| |
| 12.39% 12.05%
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| 7.75% 7.40%
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| 1.20%
| |
| 0%
| |
| A SIREN A TEXT MESSAGE ALERT ALERT INFORMATION PHONE OTHER SOUNDING NEAR FROM BROADCAST ON BROADCAST ON ON TWITTER OR CALL/TEXT YOUR HOME EMERGENCY RADIO TV FACEBOOK MESSAGE FROM OFFICIALS FAMILY, FRIEND, OR NEIGHBOR Figure F22. Perception of Public Alert Method North Anna Power Station F18 KLD Engineering, P.C.
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| ATTACHMENT A Demographic Survey Instrument North Anna Power Station F19 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Noh Anna Power Station Demographic Survey
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| * Required Purpose The purpose of this survey is to identify local behavior during emergency situations. The information gathered in this survey will be shared with Dominion Energy and local emergency management agencies to enhance emergency response plans in your area. Your responses will greatly contribute to local emergency preparedness.
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| . ( ) . Do not provide your name or any personal information, and the survey will take less than 5 minutes to complete.
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| : 1. 1. What is your gender?
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| Mark only one oval.
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| Male Female Decline to State Other:
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| : 2. 2. What is your home zip code? *
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| : 3. 3A. In total, how many running cars, or other vehicles are usually available to the household?
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| Mark only one oval.
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| ONE TWO THREE FOUR FIVE SIX SEVEN EIGHT NINE OR MORE ZERO (NONE)
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| DECLINE TO STATE
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| : 4. 3B. In an emergency, could you get a ride out of the area with a neighbor or friend?
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| Mark only one oval.
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| YES NO DECLINE TO STATE
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| : 5. 4. How many vehicles would your household use during an evacuation?
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| Mark only one oval.
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| ONE TWO THREE FOUR FIVE SIX SEVEN EIGHT NINE OR MORE ZERO (NONE)
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| I WOULD EVACUATE BY BICYCLE I WOULD EVACUATE BY BUS DECLINE TO STATE
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| : 6. 5A. How many people usually live in this household?
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| Mark only one oval.
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| ONE TWO THREE FOUR FIVE SIX SEVEN EIGHT NINE TEN ELEVEN TWELVE THIRTEEN FOURTEEN FIFTEEN SIXTEEN SEVENTEEN EIGHTEEN NINETEEN OR MORE DECLINE TO STATE
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| : 7. 5B. Of these people that live in this household, are any of them seasonal residents?
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| seasonal residents refers to the residents who do not reside in the household the majority of the year.
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| Mark only one oval.
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| Yes No Skip to question 10 Decline to State Skip to question 10 Skip to question 10 Seasonal Population
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| : 8. 5C. How many of the household residents are seasonal?
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| Mark only one oval.
| |
| ONE TWO THREE FOUR FIVE SIX SEVEN EIGHT NINE TEN ELEVEN TWELVE THIRTEEN FOURTEEN FIFTEEN SIXTEEN SEVENTEEN EIGHTEEN NINETEEN OR MORE DECLINE TO STATE
| |
| : 9. 5D. What season do the seasonal residents live in this home?
| |
| Mark only one oval.
| |
| Summer Fall Winter Spring Decline to State COVID-19
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| : 10. 6. How many people in your household have a work and/or school commute that has been temporarily impacted due to the COVID-19 pandemic?
| |
| Mark only one oval.
| |
| ZERO ONE TWO THREE FOUR OR MORE DECLINE TO STATE Skip to question 11 Commuters
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| : 11. 7. How many people in the household normally (during non-COVID conditions) commute
| |
| * to a job, or to college on a daily basis?
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| Mark only one oval.
| |
| ZERO Skip to question 56 ONE Skip to question 12 TWO Skip to question 13 THREE Skip to question 14 FOUR OR MORE Skip to question 15 DECLINE TO STATE Skip to question 56 Mode of Travel
| |
| : 12. 8. Thinking about each commuter, how does each person usually travel to work or college?
| |
| Mark only one oval per row.
| |
| Carpool-2 Drive Dont Rail Bus Walk/Bicycle or more Alone know people Commuter 1
| |
| Skip to question 16 Mode of Travel
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| : 13. 8. Thinking about each commuter, how does each person usually travel to work or college?
| |
| Mark only one oval per row.
| |
| Carpool-2 Drive Dont Rail Bus Walk/Bicycle or more Alone know people Commuter 1
| |
| Commuter 2
| |
| Skip to question 18 Mode of Travel
| |
| : 14. 8. Thinking about each commuter, how does each person usually travel to work or college?
| |
| Mark only one oval per row.
| |
| Carpool-2 Drive Dont Rail Bus Walk/Bicycle or more Alone know people Commuter 1
| |
| Commuter 2
| |
| Commuter 3
| |
| Skip to question 22 Mode of Travel
| |
| : 15. 8. Thinking about each commuter, how does each person usually travel to work or college?
| |
| Mark only one oval per row.
| |
| Carpool-2 Drive Dont Rail Bus Walk/Bicycle or more Alone know people Commuter 1
| |
| Commuter 2
| |
| Commuter 3
| |
| Commuter 4
| |
| Skip to question 28 Travel Home From Work/College
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| : 16. 9-1. How much time on average, would it take Commuter #1 to travel home from work or college?
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| Mark only one oval.
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| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 17. If Over 2 Hours for Question 9-1, Specify Here leave blank if your answer for Question 9-1, is under 2 hours.
| |
| Skip to question 36 Travel Home From Work/College
| |
| : 18. 9-1. How much time on average, would it take Commuter #1 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 19. If Over 2 Hours for Question 9-1, Specify Here leave blank if your answer for Question 9-1, is under 2 hours.
| |
| : 20. 9-2. How much time on average, would it take Commuter #2 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 21. If Over 2 Hours for Question 9-2, Specify Here leave blank if your answer for Question 9-2, is under 2 hours.
| |
| Skip to question 38 Travel Home From Work/College
| |
| : 22. 9-1. How much time on average, would it take Commuter #1 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 23. If Over 2 Hours for Question 9-1, Specify Here leave blank if your answer for Question 9-1, is under 2 hours.
| |
| : 24. 9-2. How much time on average, would it take Commuter #2 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 25. If Over 2 Hours for Question 9-2, Specify Here leave blank if your answer for Question 9-2, is under 2 hours.
| |
| : 26. 9-3. How much time on average, would it take Commuter #3 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 27. If Over 2 Hours for Question 9-3, Specify Here leave blank if your answer for Question 9-3, is under 2 hours.
| |
| Skip to question 42 Travel Home From Work/College
| |
| : 28. 9-1. How much time on average, would it take Commuter #1 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 29. If Over 2 Hours for Question 9-1, Specify Here leave blank if your answer for Question 9-1, is under 2 hours.
| |
| : 30. 9-2. How much time on average, would it take Commuter #2 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 31. If Over 2 Hours for Question 9-2, Specify Here leave blank if your answer for Question 9-2, is under 2 hours.
| |
| : 32. 9-3. How much time on average, would it take Commuter #3 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 33. If Over 2 Hours for Question 9-3, Specify Here leave blank if your answer for Question 9-3, is under 2 hours.
| |
| : 34. 9-4. How much time on average, would it take Commuter #4 to travel home from work or college?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 35. If Over 2 Hours for Question 9-4, Specify Here leave blank if your answer for Question 9-4, is under 2 hours.
| |
| Skip to question 48 Preparation to leave Work/College
| |
| : 36. 10-1. Approximately how much time would it take Commuter #1 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 37. If Over 2 Hours for Question 10-1, Specify Here leave blank if your answer for Question 10-1, is under 2 hours.
| |
| Skip to question 56 Preparation to leave Work/College
| |
| : 38. 10-1. Approximately how much time would it take Commuter #1 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 39. If Over 2 Hours for Question 10-1, Specify Here leave blank if your answer for Question 10-1, is under 2 hours.
| |
| : 40. 10-2. Approximately how much time would it take Commuter #2 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 41. If Over 2 Hours for Question 10-2, Specify Here leave blank if your answer for Question 10-2, is under 2 hours.
| |
| Skip to question 56 Preparation to leave Work/College
| |
| : 42. 10-1. Approximately how much time would it take Commuter #1 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 43. If Over 2 Hours for Question 10-1, Specify Here leave blank if your answer for Question 10-1, is under 2 hours.
| |
| : 44. 10-2. Approximately how much time would it take Commuter #2 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 45. If Over 2 Hours for Question 10-2, Specify Here leave blank if your answer for Question 10-2, is under 2 hours.
| |
| : 46. 10-3. Approximately how much time would it take Commuter #3 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 47. If Over 2 Hours for Question 10-3, Specify Here leave blank if your answer for Question 10-3, is under 2 hours.
| |
| Skip to question 56 Preparation to leave Work/College
| |
| : 48. 10-1. Approximately how much time would it take Commuter #1 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 49. If Over 2 Hours for Question 10-1, Specify Here leave blank if your answer for Question 10-1, is under 2 hours.
| |
| : 50. 10-2. Approximately how much time would it take Commuter #2 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 51. If Over 2 Hours for Question 10-2, Specify Here leave blank if your answer for Question 10-2, is under 2 hours.
| |
| : 52. 10-3. Approximately how much time would it take Commuter #3 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 53. If Over 2 Hours for Question 10-3, Specify Here leave blank if your answer for Question 10-3, is under 2 hours.
| |
| : 54. 10-4. Approximately how much time would it take Commuter #4 to complete preparation for leaving work or college prior to starting the trip home?
| |
| Mark only one oval.
| |
| 5 MINUTES OR LESS 6-10 MINUTES 11-15 MINUTES 16-20 MINUTES 21-25 MINUTES 26-30 MINUTES 31-35 MINUTES 36-40 MINUTES 41-45 MINUTES 46-50 MINUTES 51-55 MINUTES 56 - 1 HOUR OVER 1 HOUR, BUT LESS THAN 1 HOUR 15 MINUTES BETWEEN 1 HOUR 16 MINUTES AND 1 HOUR 30 MINUTES BETWEEN 1 HOUR 31 MINUTES AND 1 HOUR 45 MINUTES BETWEEN 1 HOUR 46 MINUTES AND 2 HOURS OVER 2 HOURS DECLINE TO STATE
| |
| : 55. If Over 2 Hours for Question 10-4, Specify Here leave blank if your answer for Question 10-4, is under 2 hours.
| |
| Skip to question 56 Additional Questions
| |
| : 56. 11. If you were advised by local authorities to evacuate, how much time would it take the household to pack clothing, medications, secure the house, load the car, and complete preparations prior to evacuating the area?
| |
| Mark only one oval.
| |
| LESS THAN 15 MINUTES 15-30 MINUTES 31-45 MINUTES 46 MINUTES - 1 HOUR 1 HOUR TO 1 HOUR 15 MINUTES 1 HOUR 16 MINUTES TO 1 HOUR 30 MINUTES 1 HOUR 31 MINUTES TO 1 HOUR 45 MINUTES 1 HOUR 46 MINUTES TO 2 HOURS 2 HOURS TO 2 HOURS 15 MINUTES 2 HOURS 16 MINUTES TO 2 HOURS 30 MINUTES 2 HOURS 31 MINUTES TO 2 HOURS 45 MINUTES 2 HOURS 46 MINUTES TO 3 HOURS 3 HOURS TO 3 HOURS 15 MINUTES 3 HOURS 16 MINUTES TO 3 HOURS 30 MINUTES 3 HOURS 31 MINUTES TO 3 HOURS 45 MINUTES 3 HOURS 46 MINUTES TO 4 HOURS 4 HOURS TO 4 HOURS 15 MINUTES 4 HOURS 16 MINUTES TO 4 HOURS 30 MINUTES 4 HOURS 31 MINUTES TO 4 HOURS 45 MINUTES 4 HOURS 46 MINUTES TO 5 HOURS 5 HOURS TO 5 HOURS 30 MINUTES 5 HOURS 31 MINUTES TO 6 HOURS OVER 6 HOURS WILL NOT EVACUATE DECLINE TO STATE
| |
| : 57. If Over 6 Hours for Question 11, Specify Here leave blank if your answer for Question 11, is under 6 hours.
| |
| : 58. 12. If there are 6-8 inches of snow on your driveway or curb, would you need to shovel out to evacuate? If yes, how much time, on average, would it take you to clear the 6-8 inches of snow to move the car from the driveway or curb to begin the evacuation trip? Assume the roads are passable.
| |
| Mark only one oval.
| |
| LESS THAN 15 MINUTES 15-30 MINUTES 31-45 MINUTES 46 MINUTES - 1 HOUR 1 HOUR TO 1 HOUR 15 MINUTES 1 HOUR 16 MINUTES TO 1 HOUR 30 MINUTES 1 HOUR 31 MINUTES TO 1 HOUR 45 MINUTES 1 HOUR 46 MINUTES TO 2 HOURS 2 HOURS TO 2 HOURS 15 MINUTES 2 HOURS 16 MINUTES TO 2 HOURS 30 MINUTES 2 HOURS 31 MINUTES TO 2 HOURS 45 MINUTES 2 HOURS 46 MINUTES TO 3 HOURS NO, WILL NOT SHOVEL OUT OVER 3 HOURS DECLINE TO STATE
| |
| : 59. If Over 3 Hours for Question 12, Specify Here leave blank if your answer for Question 12, is under 3 hours.
| |
| : 60. 13. Please specify the number of people in your household who require Functional or Transportation needs in an evacuation:
| |
| Mark only one oval per row.
| |
| More 0 1 2 3 4 than 4 Bus Medical Bus/Van Wheelchair Accessible Vehicle Ambulance Other
| |
| : 61. Specify "Other" Transportation Need Below
| |
| : 62. 14. Please choose one of the following:
| |
| Mark only one oval.
| |
| I would await the return of household members to evacuate together.
| |
| I would evacuate independently and meet other household members later.
| |
| Decline to State
| |
| : 63. 15A. Emergency officials advise you to shelter-in-place in an emergency because you are not in the area of risk. Would you:
| |
| Mark only one oval.
| |
| SHELTER-IN-PLACE EVACUATE DECLINE TO STATE
| |
| : 64. 15B. Emergency officials advise you to shelter-in-place now in an emergency and possibly evacuate later while people in other areas are advised to evacuate now. Would you:
| |
| Mark only one oval.
| |
| SHELTER-IN-PLACE EVACUATE DECLINE TO STATE
| |
| : 65. 15C. Emergency officials advise you to evacuate due to an emergency. Where would you evacuate to?
| |
| Mark only one oval.
| |
| A RELATIVES OR FRIENDS HOME EVACUATION ASSEMBLY CENTER A HOTEL, MOTEL OR CAMPGROUND A SECOND/SEASONAL HOME WOULD NOT EVACUATE DON'T KNOW OTHER (Specify Below)
| |
| DECLINE TO STATE
| |
| : 66. Fill in OTHER answers for question 15C Pet Questions
| |
| : 67. 16A. Do you have any pet(s) and/or animal(s)?
| |
| Mark only one oval.
| |
| YES NO Skip to question 72 DECLINE TO STATE Skip to question 72 Skip to question 72
| |
| | |
| Pet Questions
| |
| : 68. 16B. What type of pet(s) and/or animal(s) do you have?
| |
| Check all that apply.
| |
| DOG CAT BIRD REPTILE HORSE FISH CHICKEN GOAT PIG OTHER SMALL PETS/ANIMALS (Specify Below)
| |
| OTHER LARGE PETS/ANIMALS (Specify Below)
| |
| Other:
| |
| 69.
| |
| Mark only one oval.
| |
| DECLINE TO STATE Pet Questions
| |
| : 70. 16C. What would you do with your pet(s) and/or animal(s) if you had to evacuate?
| |
| Mark only one oval.
| |
| TAKE PET WITH ME TO A SHELTER TAKE PET WITH ME SOMEWHERE ELSE LEAVE PET AT HOME Skip to question 72 DECLINE TO STATE Pet Questions
| |
| : 71. 16D. Do you have sufficient room in your vehicle(s) to evacuate with your pet(s) and/or animal(s)?
| |
| Mark only one oval.
| |
| YES NO WILL USE A TRAILER DECLINE TO STATE Other:
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| Emergency Communications
| |
| : 72. 17A. At your place of residence, how reliable is your cell phone signal?
| |
| Mark only one oval.
| |
| VERY RELIABLE TO RECEIVE TEXTS AND PHONE CALLS RELIABLE FOR TEXT MESSAGES ONLY I DO NOT ALWAYS RECEIVE CELL COMMUNICATIONS AT MY RESIDENCE I DO NOT HAVE CELL SERVICE AT MY RESIDENCE
| |
| : 73. 17B. Emergency management officials in your state may send text messages, similar to AMBER Alerts, with emergency directions for the public during a radiological emergency at the North Anna Power Station. How likely would you be to take action on these directions, if you received the message?
| |
| Mark only one oval.
| |
| HIGHLY LIKELY LIKELY NEITHER LIKELY NOR UNLIKELY UNLIKELY HIGHLY UNLIKELY
| |
| : 74. 17C. Which of the following emergency communication methods do you think is most likely to alert you at your residence?
| |
| Check all that apply.
| |
| A SIREN SOUNDING NEAR YOUR HOME A TEXT MESSAGE FROM EMERGENCY OFFICIALS ALERT BROADCAST ON RADIO ALERT BROADCAST ON TV INFORMATION ON TWITTER OR FACEBOOK PHONE CALL/TEXT MESSAGE FROM FAMILY, FRIEND, OR NEIGHBOR OTHER
| |
| : 75. Fill in OTHER answers for question 17C This content is neither created nor endorsed by Google.
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| Forms
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| | |
| APPENDIX G Traffic Management Plan
| |
| | |
| G. TRAFFIC MANAGEMENT PLAN NUREG/CR7002, Rev. 1 indicates that the existing Traffic Control Points (TCPs) and Access Control Points (ACPs) identified by the offsite agencies should be used in the evacuation simulation modeling. The traffic and access control plans for the EPZ were provided by each county.
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| These plans were reviewed and the TCPs and ACPs were modeled accordingly. An analysis of the TCP and ACP locations was performed, and it was determined to model the ETE simulations with existing TCPs and ACPs that were provided in the approved county plans, with no additional TCPs or ACPs needed.
| |
| G.1 Manual Traffic Control The TCPs and ACPs are forms of manual traffic control (MTC). As discussed in Section 9, MTC at intersections (which are controlled) are modeled as actuated signals. If an intersection has a pretimed signal, stop, or yield control, and the intersection is identified as a TCP (or ACP), the control type was changed to an actuated signal in the DYNEV II system, in accordance with Section 3.3 of NUREG/CR7002, Rev. 1. MTC at existing actuated traffic signalized intersections were essentially left alone.
| |
| Table K1 provides the number of nodes with each control type. If the existing control was changed due to the point being a TCP or ACP, the control type is indicated as TACP in Table K
| |
| : 1. These MTC points, as shown in the county emergency plans, are mapped in Figure G1. No additional locations for MTC are suggested in this study.
| |
| It is assumed that ACPs will be established within 120 minutes of the ATE to discourage through travelers from using major through routes which traverse the EPZ. As discussed in Section 3.10, external traffic was considered on three routes which traverse the study area - US1, Interstate95 (I95) and I64 - in this analysis. The generation of the external trips on these routes ceased at 2 hours after the ATE in the simulation due to the activation of the ACPs.
| |
| G.2 Analysis of Key TCP/ACP Locations As discussed in Section 5.2 of NUREG/CR7002, Rev. 1, MTC at intersections could benefit from the ETE analysis. The MTC locations contained within the traffic management plans (TMP) were analyzed to determine key locations where MTC would be most useful and can be readily implemented. As previously mentioned, signalized intersections that were actuated based on field data collection were essentially left as actuated traffic signals in the model, with modifications to green time allocation as needed. Other controlled intersections (pretimed signals, stop signs and yield signs) were changed to actuated traffic signals to represent the MTC that would be implemented according to the TMP.
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| The majority of the TCPs/ACPs identified in the TMP were located at intersections with stop control. Table G1 shows a list of the controlled intersections that were identified as MTC points in the TMPs that were not previously actuated signals, including the type of control that North Anna Power Station G1 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| currently exists at each location. To determine the impact of MTC at these locations, a summer, midweek, midday, with good weather (Scenario 1) evacuation of the 2Mile Region, 5Mile Region and the entire EPZ (Region R01, R02, R03) were simulated wherein these intersections were left as is (without MTC). The results were compared to the results presented in Section 7.
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| As shown in Table G2, the ETE did not change at the 90th and increased slightly (by at most 5 minutes) at the 100th percentile when the MTC was not present at these intersections. The remaining TCPs and ACPs at controlled intersections were left as actuated signals in the model and, therefore, had no impact on ETE.
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| Although there is no reduction in ETE when MTC is implemented, traffic and access control can be beneficial in the reduction of localized traffic congestion and driver confusion and can be extremely helpful for fixed point surveillance, amongst other things. Should there be a shortfall of personnel to staff the TCPs or ACPs, the list of locations provided in Table G1 could be considered as priority locations when implementing the TMP as the existing control at these intersections is not as efficient as an actuated signal or MTC.
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| North Anna Power Station G2 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table G1. List of Key Manual Traffic Control Locations Node Previous Control TCP/ACP Name Number (Prior to being a TCP/ACP) 522/208 3 Stop 208/652 4 Stop 208/601 6 Stop 208/733 7 Stop 208/606 8 Stop 606/659 23 Stop 652/700 36 Stop 652/614 (eastern intersection) 37 Stop 652/723 38 Stop 522/751 46 Stop 522/700 49 Stop 33/522 (northwest intersection) 50 Stop 33/522 (southeast intersection) 51 Stop 614/618 59 Stop 618/609 62 Stop 601/7000 (entrance to Lake Anna State Park) 71 Stop 601/612 74 Stop 33/609 86 Stop 605/643 92 Stop 606/612 (western intersection) 103 Stop 606/612 (eastern intersection) 104 Stop 738/657 107 Stop Rt. 639 (Ladysmith Rd.) and Rt. 738 (Partlow Rd.) 111 Stop Rt. 669 (Trivette Rd.) and Rt. 738 (Partlow Rd) 118 Stop 652/650 120 Stop 208/1531 136 Stop 208/663 137 Stop 601/643 141 Stop 658 (Tyler Station Road)/680 (Woodsons Mill Road) 154 Stop 208/659 171 Stop 652/614 (western intersection) 184 Stop 652/685 199 Stop 208/655 203 Stop 652/739 275 Stop 652/790 (Mitchell Rd) 321 Stop 522/605 334 Stop 614/738 388 Stop 601/622 394 Stop 601/614 (southeast intersection) 399 Stop North Anna Power Station G3 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Node Previous Control TCP/ACP Name Number (Prior to being a TCP/ACP) 614/657 400 Stop 605/738 (southern intersection) 406 Stop 618/650 409 Stop 609/612 412 Stop 618 (Belsches Road)/680 (Woodsons Mill Road) 415 Stop 701/601 (northern intersection) 420 Stop 700/712 430 Stop 618/700 (eastern intersection) 434 Stop 678 (Union Church Road)/715 (Beaver Dam Road) 438 Stop 613/621 448 Stop 606/608 458 Stop 622/652 470 Stop 701/655 475 Stop 605/658 479 Stop 605/670 480 Stop 612/721 486 Stop 522/665 515 Stop 22(208)/778 517 Stop 33/657 541 Stop 719/Blue Water Blvd. 561 Stop 608/612 (western intersection) 574 Stop 738/647 582 Stop 650/680 595 Stop 618/684 597 Stop 618/703 603 Stop 652/1205 606 Stop 605/678 618 Stop 601/655 622 Stop 33/648 641 Stop Rt. 669 (Trivette Rd.) and Rt. 679 (Country Rd.) 644 Stop 658 (Green Bay Road)/ 715 (Beaver Dam Road) 646 Stop 669/731 698 Stop 658 (Green Bay Road)/681 (Ancient Acres Road) 722 Stop ACP 1 (653/65 1) 801 Stop Rt. 669 (Trivette Rd.) and Rt. 698 (Shockey Lane) 837 Stop Rt. 671 (Chilesburg Rd) and Rt. 738 (Partlow Rd.)
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| 840 Stop (northern intersection)
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| Rt. 671 (Chilesburg Rd.) and 738 (Partlow Rd.)
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| 846 Stop (southern intersection) 680 (Woodsons Mill Road)/729 (Hollowing Creek 851 Stop Road)
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| North Anna Power Station G4 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Node Previous Control TCP/ACP Name Number (Prior to being a TCP/ACP) 678 (Union Church Road/738 (Teman Road) 866 Stop 729 (Hollowing Creek Road)/658 (Tyler Station Road) 868 Stop 22(208)/645 870 Stop 522/779 873 Stop 522/770 878 Stop 522/720 881 Stop 618/700 (western intersection) 885 Stop 618/722 887 Stop 614/Seclusion Shores 889 Stop 614/1207 891 Stop 33/601 897 Stop 605/738 899 Stop 605/704 905 Stop 605/622 910 Stop 601/614 914 Stop 601/757 918 Stop 713/601 920 Stop 655/761 921 Stop 655/643 934 Stop 621/785 958 Stop 609/648 968 Stop 701/608 971 Stop 608/654 982 Stop 609/655 988 Stop 652/701 999 Stop 652/728 1004 Stop 33/644 1011 Stop 208/752 1014 Stop 208/602 1020 Stop 650/728 1025 Stop 208/691 1028 Stop 208/656 1030 Stop 606/649 1036 Stop 738/641 1069 Stop ACP 2 (522/651) 1078 Stop 605/644 1090 Stop 601/651 1113 Stop 22(208)/767 1117 Stop 522(208)/ Mineral Town line north 1121 Stop 208/1530 1148 Stop North Anna Power Station G5 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table G2. ETE with No MTC Scenario 1 th Region 90 Percentile ETE 100th Percentile ETE Base No MTC Difference Base No MTC Difference R01 (2Mile) 2:45 2:45 0:00 5:15 5:20 0:05 R02 (5Mile) 2:55 2:55 0:00 5:20 5:20 0:00 R03 (Full EPZ) 3:10 3:10 0:00 5:25 5:25 0:00 North Anna Power Station G6 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure G1. Access and Traffic Control Points for the North Anna Power Station North Anna Power Station G7 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| APPENDIX H Evacuation Regions
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| H EVACUATION REGIONS This appendix presents the evacuation percentages for each Evacuation Region (Table H1) and maps of all Evacuation Regions (Figure H1 through Figure H55). The percentages presented in Table H1 are based on the methodology discussed in assumption 7 of Section 2.2 and shown in Figure 21.
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| Note the baseline ETE study assumes 20% of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR7002, Rev. 1.
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| North Anna Power Station H1 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table H1. Percent of PAZ Population Evacuating for Each Region Radial Regions Protection Action Zone (PAZ)
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| Region Description Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R01 2Mile Region N/A 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R02 5Mile Region N/A 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R03 Full EPZ N/A 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
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| Evacuate 2Mile Region and Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R04 NNW, N 327 11 20% 20% 20% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R05 NNE 12 33 20% 20% 20% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R06 NE 34 56 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R07 ENE 57 78 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R08 E 79 101 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R09 ESE, SE 102 146 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R10 SSE 147 168 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R11 S, SSW 169 213 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R12 SW 214 236 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R13 WSW, W 237 281 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R14 WNW 282 303 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R15 NW 304 326 20% 20% 20% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R16 NNW, N 327 11 20% 20% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100%
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| R17 NNE 12 33 20% 100% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100%
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| R18 NE 34 56 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R19 ENE 57 78 100% 100% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R20 E 79 101 100% 100% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20%
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| R21 ESE, SE 102 146 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20%
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| R22 SSE 147 168 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 20% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20%
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| R23 S 169 191 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20%
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| R24 SSW 192 213 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 100% 100% 100% 100% 20% 20% 20% 20% 20%
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| R25 SW 214 236 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 100% 100% 100% 20% 20% 20% 20% 20%
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| R26 WSW 237 258 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100% 20% 20% 20% 20%
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| R27 W 259 281 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100% 20% 20% 20%
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| R28 WNW 282 303 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100% 100% 100% 100%
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| R29 NW 304 326 20% 20% 20% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100% 100% 100%
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| PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station H2 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Evacuate 5Mile Region and Downwind to the EPZ Boundary Wind Direction Protection Action Zone (PAZ)
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| Region Degrees From: 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R30 NNW, N 327 11 20% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100% 100%
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| R31 NNE 12 33 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 100%
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| R32 NE, ENE 34 78 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R33 E 79 101 100% 100% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 100% 20%
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| R34 ESE, SE 102 146 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 100% 20%
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| R35 SSE 147 168 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 100% 20%
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| R36 S 169 191 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 100% 100% 100% 20% 20% 20% 20% 100% 20%
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| R37 SSW 192 213 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 100% 100% 100% 100% 20% 20% 20% 100% 20%
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| R38 SW 214 236 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 100% 100% 100% 20% 20% 20% 100% 20%
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| R39 WSW 237 258 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 100% 100% 100% 20% 20% 100% 20%
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| R40 W 259 281 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 100% 100% 100% 20% 100% 20%
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| R41 WNW 282 303 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 100% 100% 100% 100% 100% 100%
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| R42 NW 304 326 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 100% 100% 100% 100% 100%
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| Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction Protection Action Zone (PAZ)
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| Region From: Degrees 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 R43 5Mile Region N/A 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R44 NNW, N 327 11 20% 20% 20% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R45 NNE 12 33 20% 20% 20% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R46 NE 34 56 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R47 ENE 57 78 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R48 E 79 101 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R49 ESE, SE 102 146 20% 20% 100% 20% 100% 20% 100% 100% 100% 20% 20% 20% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R50 SSE 147 168 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R51 S, SSW 169 213 20% 20% 20% 20% 100% 20% 100% 100% 100% 20% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R52 SW 214 236 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R53 WSW, W 237 281 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%
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| R54 WNW 282 303 20% 20% 20% 20% 100% 20% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| R55 NW 304 326 20% 20% 20% 20% 100% 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20% 100% 20%
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| PAZ(s) Evacuate PAZ is not in the plume, but it is surrounded by other PAZ(s) that are evacuating PAZ(s) ShelterinPlace until 90% ETE for R01, then Evacuate North Anna Power Station H3 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H1. Region R01 North Anna Power Station H4 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H2. Region R02 North Anna Power Station H5 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H3. Region R03 North Anna Power Station H6 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H4. Region R04 North Anna Power Station H7 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H5. Region R05 North Anna Power Station H8 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H6. Region R06 North Anna Power Station H9 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H7. Region R07 North Anna Power Station H10 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H8. Region R08 North Anna Power Station H11 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H9. Region R09 North Anna Power Station H12 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H10. Region R10 North Anna Power Station H13 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H11. Region R11 North Anna Power Station H14 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H12. Region R12 North Anna Power Station H15 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H13. Region R13 North Anna Power Station H16 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H14. Region R14 North Anna Power Station H17 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H15. Region R15 North Anna Power Station H18 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H16. Region R16 North Anna Power Station H19 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H17. Region R17 North Anna Power Station H20 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H18. Region R18 North Anna Power Station H21 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H19. Region R19 North Anna Power Station H22 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H20. Region R20 North Anna Power Station H23 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H21. Region R21 North Anna Power Station H24 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H22. Region R22 North Anna Power Station H25 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H23. Region R23 North Anna Power Station H26 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H24. Region R24 North Anna Power Station H27 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H25. Region R25 North Anna Power Station H28 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H26. Region R26 North Anna Power Station H29 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H27. Region R27 North Anna Power Station H30 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H28. Region R28 North Anna Power Station H31 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H29. Region R29 North Anna Power Station H32 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H30. Region R30 North Anna Power Station H33 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H31. Region R31 North Anna Power Station H34 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H32. Region R32 North Anna Power Station H35 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H33. Region R33 North Anna Power Station H36 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H34. Region R34 North Anna Power Station H37 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H35. Region R35 North Anna Power Station H38 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H36. Region R36 North Anna Power Station H39 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H37. Region R37 North Anna Power Station H40 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H38. Region R38 North Anna Power Station H41 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H39. Region R39 North Anna Power Station H42 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H40. Region R40 North Anna Power Station H43 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H41. Region R41 North Anna Power Station H44 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H42. Region R42 North Anna Power Station H45 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H43. Region R43 North Anna Power Station H46 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H44. Region R44 North Anna Power Station H47 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H45. Region R45 North Anna Power Station H48 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H46. Region R46 North Anna Power Station H49 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H47. Region R47 North Anna Power Station H50 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H48. Region R48 North Anna Power Station H51 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H49. Region R49 North Anna Power Station H52 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H50. Region R50 North Anna Power Station H53 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H51. Region R51 North Anna Power Station H54 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H52. Region R52 North Anna Power Station H55 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H53. Region R53 North Anna Power Station H56 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H54. Region R54 North Anna Power Station H57 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure H55. Region R55 North Anna Power Station H58 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| APPENDIX J Representative Inputs to and Outputs from the DYNEV II System
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| | |
| J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM This appendix presents data input to and output from the DYNEV II System.
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| Table J1 provides source (vehicle loading) and destination information for several roadway segments (links) in the analysis network. In total, there are 276 source links (origins) in the model. The source links are shown as centroid points in Figure J1. On average, vehicles travel a straightline distance of 5.00 miles to exit the EPZ.
| |
| Table J2 provides network-wide statistics (average travel time, average delay time1, average speed and number of vehicles) for an evacuation of the entire EPZ (Region R03) for each scenario. Rain/light snow scenarios (Scenarios 2, 4, 7, and 10) and heavy snow scenarios (Scenarios 8 and 11), exhibit slower average speeds and longer average travel times compared to good weather scenarios. As expected, when comparing Scenario 13 (special event) and Scenario 9, the additional vehicles introduced by the special event slightly lowers the network wide average speed. When comparing Scenario 14 (roadway closure) and Scenario 1, the one segment closure on US522 northbound decreases the average travel speed.
| |
| Table J3 provides statistics (average speed and travel time) for the major evacuation routes -
| |
| US 522, SR 208, SR 738 and US 33 - for an evacuation of the entire EPZ (Region R03) under Scenario 1 conditions. As shown in Figure 73 through Figure 78, there is minimal traffic congestion in the EPZ throughout the duration of the evacuation. As such, the average speeds on the major evacuation routes are only moderately affected. At the end of the evacuation (5:25) the roads are free flowing; the average speeds are only a few mph less than free flow during the first 5 hours of the evacuation.
| |
| Table J4 provides the number of vehicles discharged and the cumulative percent of total vehicles discharged for each link exiting the analysis network, for an evacuation of the entire EPZ (Region R03) under Scenario 1 conditions. Refer to the figures in Appendix K for a map showing the geographic location of each link. As expected, the high capacity roadways (I64, I 95, US1, and US33) in the network service the highest percentage of evacuating vehicles.
| |
| Figure J2 through Figure J15 plot the trip generation time versus the ETE for each of the 14 Scenarios considered. The distance between the trip generation and ETE curves is the travel time. Plots of trip generation time versus ETE are indicative of the level of traffic congestion during evacuation. For low population density sites, the curves are close together, indicating short travel times and minimal traffic congestion. For higher population density sites, the curves are farther apart indicating longer travel times and the presence of traffic congestion.
| |
| As seen in Figure J2 through Figure J15, the curves are somewhat separated due to the presence of moderate traffic congestion within the EPZ for the first 2 hours and 30 minutes.
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| After this congestion clears, the two curves are close together indicating ETE mimics trip generation time.
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| 1 Computed as the difference of the average travel time and the average ideal travel time under free flow conditions.
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| North Anna Power Station J1 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| | |
| Table J1. Sample Simulation Model Input Vehicles Upstream Downstream Entering Link Node Node Network Directional Destination Destination Number on this Link Preference Nodes Capacity 8070 1,700 84 56 48 29 SW 8073 1,700 8330 4,500 8330 4,500 1496 1249 1248 159 SW 8329 4,500 8187 1,700 8146 6,750 550 389 388 142 E 8143 1,700 8167 1,700 8070 1,700 493 343 46 33 W 8073 1,700 8330 4,500 8226 2,850 1170 948 104 33 N 8231 1,700 8306 1,700 8444 1,700 612 438 546 324 SE 8044 1,700 8235 1,700 37 24 306 19 NE 8306 1,700 8225 1,275 336 229 504 21 NE 8306 1,700 8238 3,800 8146 6,750 685 498 11 97 NE 8167 1,700 8257 1,275 8330 4,500 1324 1090 539 27 SW 8329 4,500 North Anna Power Station J2 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table J2. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03)
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| Scenario 1 2 3 4 5 6 7 NetworkWide Average 1.1 1.2 1.2 1.3 1.3 1.1 1.2 Travel Time (Min/VehMi)
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| NetworkWide Average 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Delay Time (Min/VehMi)
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| NetworkWide Average 54.1 49.1 50.0 45.7 47.6 56.7 51.5 Speed (mph)
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| Total Vehicles 42,461 42,695 42,593 42,835 30,141 40,197 40,411 Exiting Network Scenario 8 9 10 11 12 13 14 NetworkWide Average 1.3 1.1 1.2 1.3 1.2 1.1 1.1 Travel Time (Min/VehMi)
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| NetworkWide Average 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Delay Time (Min/VehMi)
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| NetworkWide Average 48.1 55.5 50.5 48.2 51.1 55.3 52.9 Speed (mph)
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| Total Vehicles 40,672 39,533 39,752 40,010 27,872 39,809 42,482 Exiting Network North Anna Power Station J3 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Table J3. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Scenario 1)
| |
| Elapsed Time (hours:minutes) 1:00 2:00 3:00 4:00 5:00 5:25 Travel Length Speed Time Travel Travel Travel Travel Travel (miles) (mph) (min) Speed Time Speed Time Speed Time Speed Time Speed Time Route#
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| US 522 NB from SR 208 7.2 55.1 7.9 59.4 7.3 58.5 7.4 58.4 7.4 58.8 7.4 60.0 7.2 US 522 SB from Mineral 7.3 50.7 8.7 50.7 8.7 50.6 8.7 50.7 8.7 51.2 8.6 54.2 8.1 SR 208/SR 22 WB from Mineral 4.2 49.8 5.0 47.3 5.3 45.9 5.5 46.2 5.4 46.6 5.4 53.7 4.7 SR 208/Courthouse Rd EB from CR 601 10.9 51.9 12.6 51.4 12.8 49.1 13.4 49.2 13.3 49.7 13.2 56.1 11.7 SR 738/Partlow Rd NB from CR 657 8.2 45.0 10.9 45.2 10.8 45.9 10.7 46.3 10.6 46.4 10.6 48.1 10.2 SR 738/Partlow Rd SB from CR 657 6.0 47.3 7.6 47.2 7.6 46.3 7.8 46.4 7.8 46.6 7.7 49.4 7.3 US 33 EB from SR 768 14.3 56.7 15.1 56.8 15.1 56.4 15.2 56.7 15.1 57.9 14.8 60.0 14.3 North Anna Power Station J4 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Table J4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 Elapsed Time (hours:minutes)
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| Roadway Network Upstream Downstream 1:00 2:00 3:00 4:00 5:00 5:25 Name Exit Link Node Node Cumulative Vehicles Discharged by the Indicated Time Cumulative Percent of Vehicles Discharged by the Indicated Time Interval 459 1,276 1,650 1,826 1,873 1,883 US 522 4 2 231 4.0% 4.4% 4.3% 4.4% 4.4% 4.4%
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| 348 972 1,250 1,375 1,418 1,424 SR 20 23 16 232 3.0% 3.3% 3.3% 3.3% 3.4% 3.4%
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| 205 712 979 1,103 1,135 1,140 SR 20 48 31 214 1.8% 2.4% 2.6% 2.7% 2.7% 2.7%
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| 63 240 357 410 423 425 SR 738 66 43 235 0.6% 0.8% 0.9% 1.0% 1.0% 1.0%
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| 75 280 430 496 509 512 US 522 82 55 187 0.7% 1.0% 1.1% 1.2% 1.2% 1.2%
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| 310 998 1,381 1,581 1,633 1,646 US 33 106 68 70 2.7% 3.4% 3.6% 3.8% 3.9% 3.9%
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| 82 422 649 744 768 770 SR 22 107 68 73 0.7% 1.4% 1.7% 1.8% 1.8% 1.8%
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| 89 415 635 712 725 728 CR 606 215 145 167 0.8% 1.4% 1.7% 1.7% 1.7% 1.7%
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| 2,385 4,846 5,565 5,594 5,599 5,601 I95 314 212 146 20.7% 16.6% 14.6% 13.5% 13.2% 13.2%
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| 108 370 537 622 643 648 SR 3 328 223 1,243 0.9% 1.3% 1.4% 1.5% 1.5% 1.5%
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| 20 111 193 224 230 231 CR 608 370 256 257 0.2% 0.4% 0.5% 0.5% 0.5% 0.5%
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| 692 1,673 2,362 2,626 2,702 2,717 US 1 382 264 265 6.0% 5.7% 6.2% 6.3% 6.4% 6.4%
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| 2,391 5,007 5,853 5,923 5,938 5,941 I95 387 267 152 20.8% 17.1% 15.3% 14.3% 14.0% 14.0%
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| 1,266 2,923 3,479 3,642 3,682 3,690 I64 420 290 330 11.0% 10.0% 9.1% 8.8% 8.7% 8.7%
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| 619 1,425 1,976 2,189 2,255 2,269 US 1 438 302 303 5.4% 4.9% 5.2% 5.3% 5.3% 5.3%
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| 79 388 624 737 772 777 CR 612 445 306 1,166 0.7% 1.3% 1.6% 1.8% 1.8% 1.8%
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| 1,231 2,783 3,294 3,441 3,476 3,484 I64 471 328 329 10.7% 9.5% 8.6% 8.3% 8.2% 8.2%
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| 501 1,883 3,035 3,673 3,796 3,820 US 33 618 444 1,171 4.4% 6.4% 8.0% 8.9% 9.0% 9.0%
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| North Anna Power Station J5 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| | |
| Elapsed Time (hours:minutes)
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| Roadway Network Upstream Downstream 1:00 2:00 3:00 4:00 5:00 5:25 Name Exit Link Node Node Cumulative Vehicles Discharged by the Indicated Time Cumulative Percent of Vehicles Discharged by the Indicated Time Interval 239 962 1,499 1,753 1,798 1,809 SR 208 760 562 226 2.1% 3.3% 3.9% 4.2% 4.3% 4.3%
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| 65 259 402 470 506 509 CR 627 978 777 225 0.6% 0.9% 1.1% 1.1% 1.2% 1.2%
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| 5 18 32 36 37 37 SR 207 1023 821 823 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%
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| 60 252 373 428 441 444 SR 605 1403 1,167 143 0.5% 0.9% 1.0% 1.0% 1.0% 1.0%
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| 177 719 1,057 1,212 1,255 1,263 SR 671 1425 1,188 44 1.5% 2.5% 2.8% 2.9% 3.0% 3.0%
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| 47 345 569 672 690 695 SR 3 1437 1,200 1,244 0.4% 1.2% 1.5% 1.6% 1.6% 1.6%
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| North Anna Power Station J6 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| | |
| Figure J1. Network Sources/Origins North Anna Power Station J7 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Summer, Midweek, Midday, Good (Scenario 1)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1)
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| ETE and Trip Generation Summer, Midweek, Midday, Rain (Scenario 2)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2)
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| North Anna Power Station J8 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Summer, Weekend, Midday, Good (Scenario 3)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3)
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| ETE and Trip Generation Summer, Weekend, Midday, Rain (Scenario 4)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4)
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| North Anna Power Station J9 KLD Engineering, P.C.
| |
| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Summer, Midweek, Weekend, Evening, Good (Scenario 5)
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| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)
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| ETE and Trip Generation Winter, Midweek, Midday, Good (Scenario 6)
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| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
| |
| 60%
| |
| 40%
| |
| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6)
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| North Anna Power Station J10 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Winter, Midweek, Midday, Rain/Light Snow (Scenario 7)
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| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J8. ETE and Trip Generation: Winter, Midweek, Midday, Rain/Light Snow (Scenario 7)
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| ETE and Trip Generation Winter, Midweek, Midday, Heavy Snow (Scenario 8)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 7:00 7:30 8:00 Elapsed Time (h:mm)
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| Figure J9. ETE and Trip Generation: Winter, Midweek, Midday, Heavy Snow (Scenario 8)
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| North Anna Power Station J11 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| | |
| ETE and Trip Generation Winter, Weekend, Midday, Good (Scenario 9)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
| |
| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J10. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 9)
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| ETE and Trip Generation Winter, Weekend, Midday, Rain/Light Snow (Scenario 10)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
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| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J11. ETE and Trip Generation: Winter, Weekend, Midday, Rain/Light Snow (Scenario 10)
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| North Anna Power Station J12 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Winter, Weekend, Midday, Heavy Snow (Scenario 11)
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| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
| |
| 60%
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| 40%
| |
| 20%
| |
| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 7:00 7:30 8:00 Elapsed Time (h:mm)
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| Figure J12. ETE and Trip Generation: Winter, Weekend, Midday, Heavy Snow (Scenario 11)
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| ETE and Trip Generation Winter, Midweek, Weekend, Evening, Good (Scenario 12)
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| Trip Generation ETE 100%
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| Percent of Total Vehicles 80%
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| 60%
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| 40%
| |
| 20%
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| 0%
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| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J13. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 12)
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| North Anna Power Station J13 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| ETE and Trip Generation Winter, Weekend, Midday, Good, Special Event (Scenario 13)
| |
| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
| |
| 60%
| |
| 40%
| |
| 20%
| |
| 0%
| |
| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J14. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather, Special Event (Scenario 13)
| |
| ETE and Trip Generation Summer, Midweek, Midday, Good, Roadway Impact (Scenario 14)
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| Trip Generation ETE 100%
| |
| Percent of Total Vehicles 80%
| |
| 60%
| |
| 40%
| |
| 20%
| |
| 0%
| |
| 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 Elapsed Time (h:mm)
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| Figure J15. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 14)
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| North Anna Power Station J14 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| APPENDIX K Evacuation Roadway Network
| |
| | |
| K. EVACUATION ROADWAY NETWORK As discussed in Section 1.3, a linknode analysis network was constructed to model the roadway network within the study area. Figure K1 provides an overview of the linknode analysis network. The figure has been divided up into 43 more detailed figures (Figure K2 through Figure K44) which show each of the links and nodes in the network.
| |
| The analysis network was calibrated using the observations made during the road survey conducted in February 2021.
| |
| Table K1 summarizes the number of nodes by the type of control (stop sign, yield sign, pre timed signal, actuated signal, traffic and/or access control points [TACP], uncontrolled).
| |
| Table K1. Summary of Nodes by the Type of Control Number of Control Type Nodes Uncontrolled 1,007 Pretimed 0 Actuated 26 Stop 73 TACP 142 Yield 4 Total: 1,252 North Anna Power Station K1 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K1. NAPS LinkNode Analysis Network North Anna Power Station K2 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K2. LinkNode Analysis Network - Grid 1 North Anna Power Station K3 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K3. LinkNode Analysis Network - Grid 2 North Anna Power Station K4 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K4. LinkNode Analysis Network - Grid 3 North Anna Power Station K5 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K5. LinkNode Analysis Network - Grid 4 North Anna Power Station K6 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K6. LinkNode Analysis Network - Grid 5 North Anna Power Station K7 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K7. LinkNode Analysis Network - Grid 6 North Anna Power Station K8 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K8. LinkNode Analysis Network - Grid 7 North Anna Power Station K9 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K9. LinkNode Analysis Network - Grid 8 North Anna Power Station K10 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K10. LinkNode Analysis Network - Grid 9 North Anna Power Station K11 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K11. LinkNode Analysis Network - Grid 10 North Anna Power Station K12 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K12. LinkNode Analysis Network - Grid 11 North Anna Power Station K13 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K13. LinkNode Analysis Network - Grid 12 North Anna Power Station K14 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K14. LinkNode Analysis Network - Grid 13 North Anna Power Station K15 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K15. LinkNode Analysis Network - Grid 14 North Anna Power Station K16 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
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| Figure K16. LinkNode Analysis Network - Grid 15 North Anna Power Station K17 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
| |
| | |
| Figure K17. LinkNode Analysis Network - Grid 16 North Anna Power Station K18 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K18. LinkNode Analysis Network - Grid 17 North Anna Power Station K19 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K19. LinkNode Analysis Network - Grid 18 North Anna Power Station K20 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K20. LinkNode Analysis Network - Grid 19 North Anna Power Station K21 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K21. LinkNode Analysis Network - Grid 20 North Anna Power Station K22 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K22. LinkNode Analysis Network - Grid 21 North Anna Power Station K23 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K23. LinkNode Analysis Network - Grid 22 North Anna Power Station K24 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K24. LinkNode Analysis Network - Grid 23 North Anna Power Station K25 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K25. LinkNode Analysis Network - Grid 24 North Anna Power Station K26 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K26. LinkNode Analysis Network - Grid 25 North Anna Power Station K27 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K27. LinkNode Analysis Network - Grid 26 North Anna Power Station K28 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K28. LinkNode Analysis Network - Grid 27 North Anna Power Station K29 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K29. LinkNode Analysis Network - Grid 28 North Anna Power Station K30 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K30. LinkNode Analysis Network - Grid 29 North Anna Power Station K31 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K31. LinkNode Analysis Network - Grid 30 North Anna Power Station K32 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K32. LinkNode Analysis Network - Grid 31 North Anna Power Station K33 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K33. LinkNode Analysis Network - Grid 32 North Anna Power Station K34 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K34. LinkNode Analysis Network - Grid 33 North Anna Power Station K35 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K35. LinkNode Analysis Network - Grid 34 North Anna Power Station K36 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K36. LinkNode Analysis Network - Grid 35 North Anna Power Station K37 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K37. LinkNode Analysis Network - Grid 36 North Anna Power Station K38 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K38. LinkNode Analysis Network - Grid 37 North Anna Power Station K39 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Figure K39. LinkNode Analysis Network - Grid 38 North Anna Power Station K40 KLD Engineering, P.C.
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| Figure K40. LinkNode Analysis Network - Grid 39 North Anna Power Station K41 KLD Engineering, P.C.
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| Figure K41. LinkNode Analysis Network - Grid 40 North Anna Power Station K42 KLD Engineering, P.C.
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| Figure K42. LinkNode Analysis Network - Grid 41 North Anna Power Station K43 KLD Engineering, P.C.
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| Figure K43. LinkNode Analysis Network - Grid 42 North Anna Power Station K44 KLD Engineering, P.C.
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| Figure K44. LinkNode Analysis Network - Grid 43 North Anna Power Station K45 KLD Engineering, P.C.
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| APPENDIX L Protective Action Zone (PAZ) Boundaries
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| L. PAZ BOUNDARIES PAZ 1 Not in use PAZ 2 County: Louisa Consists of the Town of Mineral PAZ 3 County: Louisa Consists of the area: Bounded on the north by Route 22/208 (Davis Highway),
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| bounded on the south by Route 605 (Shannon Hill Road) and Route 643 (Cuckoo Road), bounded on the east by Route 33 (Jefferson Highway), Route 522 (Pendleton Road) and the Mineral town line, bounded on the west by Route 644 (Mt. Airy Road), Route 33 (Jefferson Highway) and the Louisa town line PAZ 4 County: Louisa Consists of the area: Bounded on the north by Route 208 (New Bridge Road),
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| bounded on the south by Route 618 (Fredericks Hall Road) and Route 667 (Old Tolersville Road), bounded on the east by Lake Anna, Contrary Creek, Route 652 (Kentucky Springs Road) and Route 700 (Johnson Road), bounded on the west by Route 522/208 (Zachary Taylor Highway)
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| PAZ 5 County: Louisa Consists of the area: Bounded on the north by Route 618 (Fredericks Hall Road), bounded on the south by Route 33 (Jefferson Highway) and Route 657 (Apple Grove Road), bounded on the east by Route 609 (Buckner Road),
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| bounded on the west by Route 522 (Cross County Road) and Route 33 (Jefferson Highway)
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| PAZ 6 County: Louisa Consists of the area: Bounded on the north by Route 652 (Kentucky Springs Road), bounded on the south by Route 618 (Fredericks Hall Road), bounded on the east by Route 614 (Elk Creek Road), bounded on the west by Route 700 (Johnson Road)
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| PAZ 7 County: Louisa Consists of the area: Bounded on the northwest by Route 614 (Elk Creek Road),
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| bounded on the northeast by Route 652 (Kentucky Springs Road), bounded on the east by Route 650 (Pottiesville Road), bounded on the southwest by Route 618 (Fredericks Hall Road)
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| North Anna Power Station L1 KLD Engineering, P.C.
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| PAZ 8 County: Louisa Consists of the area: Bounded on the northeast by Lake Anna, bounded on the southeast by Route 614 (Carrs Bridge Road), bounded on the northwest by Contrary Creek, bounded on the southwest by Route 652 (Kentucky Springs Road)
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| PAZ 9 County: Spotsylvania Consists of the area: Bounded on the north by Route 713 (Boggs Drive) and the northeast by Route 601 (Lewiston Road), bounded on the south by Lake Anna, bounded on the east by Route 614 (Breaknock Road), bounded on the west by Route 208 (Courthouse Road) and Lake Anna PAZ 10 County: Louisa Consists of the area: Bounded on the north by Lake Anna, bounded on the south by Route 622 (Moody Town Road), bounded on the west by Route 652 (Kentucky Springs Road) and Route 614 (Elk Creek Road)
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| PAZ 11 County: Spotsylvania Consists of the area: Bounded on the north by Route 657 (Edenton Road),
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| bounded on the south by Route 622 (Fairview Road), bounded on the east by Route 738 (Partlow Road), bounded on the west by Lake Anna and Route 614 (Dickerson Road)
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| PAZ 12 County: Spotsylvania Consists of the area: Bounded on the north by Bluff Run and Glebe Run, bounded on the south by Route 657 (Edenton Road), Route 614 (Dickerson Road), Route 601 (Lewiston Road) and Route 713 (Boggs Drive), bounded on the east by Route 738 (Partlow Road), bounded on the west by Route 208 (Courthouse Road)
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| PAZ 13 County: Spotsylvania Consists of the area: Bounded on the north by Route 606 (Post Oak Road),
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| bounded on the south by Route 208 (Courthouse Road), bounded on the east by Route 208 (Courthouse Road), Route 650 (Margo Road) and Route 733 (Brokenburg Road), bounded on the west by Route 612 (Stubbs Bridge Road),
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| Route 601 (Lawyers Road) and Route 655 (Ridge Road)
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| PAZ 14 County: Spotsylvania Consists of the area: Bounded on the north by Route 601 (Lawyers Road),
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| bounded on the south by Lake Anna and Route 208 (Courthouse Road),
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| bounded on the east by Route 655 (Ridge Road), bounded on the west by Route 612 (Stubbs Bridge Road) and Route 719 (Belmont Road)
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| North Anna Power Station L2 KLD Engineering, P.C.
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| PAZ 15 County: Louisa Consists of the area: Bounded on the north by Lake Anna, bounded on the south by Route 208 (New Bridge Road), bounded on the east by Lake Anna, bounded on the west by Route 522 (Zachary Taylor Highway) and Route 719 (Days Bridge Road)
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| PAZ 16 County: Louisa Consists of the area: Bounded on the north by Lake Anna, bounded on the south by Route 22/208 (Davis Highway) and the Louisa town line, bounded on the east by Route 719 (Days Bridge Road), Route 522 (Zachary Taylor Highway) and Route 208 (New Bridge Road), bounded on the west by Colonial Pipeline PAZ 17 County: Orange Consists of the area: Bounded on the north by Route 653 (Orange Springs Road) and Route 629 (Orange Springs Road), bounded on the south by the Orange/Louisa County line (North Anna River), bounded on the east by Orange/Spotsylvania County line, bounded on the west by Colonial Pipeline PAZ 18 County: Spotsylvania Consists of the area: Bounded on the northeast by Route 608 (W. Catharpin Road) and Route 606 (Post Oak Road), bounded on the south by Spotsylvania/Louisa County line (North Anna River), bounded on the east by Route 612 (Stubbs Bridge Road) and Route 719 (Belmont Road), bounded on the west by Spotsylvania/Orange County line PAZ 19 County: Spotsylvania Consists of the area: Bounded on the north by Route 608 (W. Catharpin Road),
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| bounded on the south by Route 606 (Post Oak Road), bounded on the east by Route 612 (Pamunkey Road), bounded on the west by Route 606 (Post Oak Road)
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| PAZ 20 County: Spotsylvania Consists of the area: Bounded on the north by Route 608 (Robert E. Lee Drive),
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| bounded on the south by Route 208 (Courthouse Road), bounded on the east by Route 649 (Seays Road), bounded on the west by Route 612 (Pamunkey Road), Route 606 (Post Oak Road) and Route 650 (Margo Road)
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| PAZ 21 County: Spotsylvania Consists of the area: Bounded on the north by Route 208/606 (Courthouse Road), bounded on the south by Route 605 (Marye Road), bounded on the east by Route 647 (Blades Corner Road) and Route 738 (Partlow Road),
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| bounded on the west by Bluff Run, Glebe Run and Route 738 (Partlow Road)
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| PAZ 22 County: Spotsylvania Consists of the area: Bounded on the north by Route 604 (Blanton Road) and Route 605 (Marye Road), bounded on the south by the North Anna River, bounded on the east by the Spotsylvania/Caroline County line, bounded on the west by Route 622 (Fairview Road) and Route 738 (Partlow Road)
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| PAZ 23 County: Caroline Consists of the area: Bounded on the northeast by Route 738 (Partlow Road),
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| bounded on the south by the North Anna River, bounded on the east by Route 738 (Anderson Mill Road), bounded on the west by Caroline/Spotsylvania County line PAZ 24 County: Hanover Consists of the area: Bounded on the north by the North Anna River, bounded on the south by Route 608 (Parsons Road), Route 680 (Shiloh Church Road),
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| Route 729 (Hollowing Creek Road), Route 658 (Tyler Station Road), Route 715 (Beaver Dam Road), Route 739 (Beaver Dam School Road) and Route 800 (Flat Iron Road), bounded on the east by Route 738 (Teman Road) and the North Anna River, bounded on the west by Hanover/Louisa County line PAZ 25 County: Louisa Consists of the area: Bounded on the north by the North Anna River, bounded on the south by Route 652 (Kentucky Springs Road), Route 701 (Eastham Road) and Route 601 (Bumpass Road), bounded on the east by Route 601 (Green Corners Road), bounded on the west by Route 622 (Moody Town Road) and Route 652 (Kentucky Springs Road)
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| PAZ 26 County: Louisa Consists of the area: Bounded on the north by the North Anna River, bounded on the south by Route 33 (Jefferson Highway), Route 655 (Bethany Church Road), Route 701 (Belle Meade Road) and Route 608 (Signboard Road/Parsons Road), bounded on the east by Louisa/Hanover County line, bounded on the west by Route 609 (Buckner Road), Route 650 (Pottiesville Road), Route 652 (Kentucky Springs Road) and Route 601 (Bumpass Road/Greens Corner Road)
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| APPENDIX M Evacuation Sensitivity Studies
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| M. EVACUATION SENSITIVITY STUDIES This appendix presents the results of a series of sensitivity analyses. These analyses are designed to identify the sensitivity of the ETE to changes in some base evacuation conditions.
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| M.1 Effect of Changes in Trip Generation Time A sensitivity study was performed to determine whether changes in the estimated trip generation time have an effect on the ETE for the entire EPZ. Specifically, if the tail of the mobilization distribution were truncated (i.e., if those who responded most slowly to the ATE, could be persuaded to respond much more rapidly), or if the tail were elongated (i.e., spreading out the departure of evacuees to limit the demand during peak times) how would the ETE be affected? The case considered was Scenario 1, Region 3; a summer, midweek, midday, with good weather evacuation of the entire EPZ. Table M1 presents the results of this study.
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| If evacuees mobilize one hour quicker, the 90th percentile ETE is reduced by 10 minutes and the 100th percentile ETE is reduced by 1 hour. If evacuees mobilize one hour slower, the 90th and 100th percentile ETE are increased by 30 minutes and 1 hour, respectively - a significant change.
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| As discussed in Section 7.3, traffic congestion within the full EPZ clears (i.e., all highways within EPZ operate at Level of Service A) at just over 2 hours and 50 minutes after the ATE, well before the completion of trip generation time. As such, congestion dictates the 100th percentile ETE until 2 hours and 50 minutes after the ATE. After his time, trip generation (plus a 10minute travel time to the EPZ boundary), dictates the 100th percentile ETE. See Table M1.
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| M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate A sensitivity study was conducted to determine the effect on ETE of changes in the percentage of people who decide to relocate from the Shadow Region. The case considered was Scenario 1, Region 3; a summer, midweek, midday, with good weather evacuation of the entire EPZ. The movement of people in the Shadow Region has the potential to impede vehicles evacuating from an Evacuation Region within the EPZ. Refer to Sections 3.2 and 7.1 for additional information on population within the Shadow Region.
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| Table M2 presents the ETE for each of the cases considered. The results show that eliminating (0%) shadow evacuation does not impact 90th percentile ETE. While doubling (40%), tripling (60%),
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| and quadrupling (80%) the shadow percentage increases the 90th percentile ETE by 5 minutes, full evacuation (100%) of the Shadow Region increases the 90th percentile ETE by 10 minutes - not significant changes. The results show that shadow evacuation has no impact on the 100th percentile ETE.
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| Note the demographic survey results presented in Appendix F indicate that about 18% of households would elect to evacuate if advised to shelter, which is slightly lower than the base assumption of 20% noncompliance suggested in the NUREG/CR7002, Rev. 1. A sensitivity study was run using 18% shadow evacuation and the 90th and 100th percentile ETE remained the same.
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| There is minimal traffic congestion in the EPZ during an evacuation. The Shadow Region is sparsely populated with Louisa being the only major population center. While shadow evacuation in Louisa does reduce travel speeds on State Route 208 westbound, there is no impact on ETE.
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| M.3 Effect of Changes in EPZ Resident Population A sensitivity study was conducted to determine the effect on ETE of changes in the resident population within the study area (EPZ plus Shadow Region). As population in the study area changes over time, the time required to evacuate the public may increase, decrease, or remain the same. Since the ETE is related to the demand to capacity ratio present within the study area, changes in population will cause the demand side of the equation to change and could impact ETE.
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| As per the NRCs response to the Emergency Planning Frequently Asked Question (EPFAQ) 2013001, the ETE population sensitivity study must be conducted to determine what percentage increase in permanent resident population causes an increase in the 90th percentile ETE of 25% or 30 minutes, whichever is less. The sensitivity study must use the scenario with the longest 90th percentile ETE (excluding the roadway impact scenario and the special event scenario if it is a one day per year special event).
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| Thus, the sensitivity study was conducted using the following planning assumptions:
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| : 1. The percent change in the permanent resident population within the study area was increased by up to 192%. Changes in population were applied to permanent residents only (as per federal guidance), in both the EPZ and in the Shadow Region.
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| : 2. The transportation infrastructure (as presented in Appendix K) remained fixed; the presence of future proposed roadway changes and/or highway capacity improvements was not considered.
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| : 3. The study was performed for the 2Mile Region (R01), 5Mile Region (R02), and the entire EPZ (R03).
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| : 4. The scenario (excluding roadway impact and special event) with yielded the longest 90th percentile ETE values was selected as the case to be considered in this sensitivity study (Scenario 8 - winter, midweek, midday, with heavy snow).
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| Table M3 presents the results of the sensitivity study. Section IV of Appendix E to 10 CFR Part 50, and NUREG/CR7002, Rev. 1, Section 5.4, require licensees to provide an updated ETE analysis to the NRC when a population increase within the EPZ causes the longest 90th percentile ETE values (for the 2Mile Region, 5Mile Region or entire EPZ) to increase by 25% or 30 minutes, whichever is less. All base ETE values are at least 4 hours; thus, 25% of these base ETE is always greater than 30 minutes. Therefore, 30 minutes is the lesser and is the criterion for updating.
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| Those percent population changes which result in 90th percentile ETE changes greater than or equal to 30 minutes are highlighted in red in Table M3 - a 192% or greater increase in the EPZ permanent resident population (includes 20% of the Shadow Region permanent resident North Anna Power Station M2 KLD Engineering, P.C.
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| population). Dominion Energy will have to estimate the EPZ population on an annual basis. If the EPZ population increases by 192% or more, an updated ETE analysis will be needed.
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| M.4 Effect of Changes in Average Household Size As discussed in Appendix F, the average household size obtained from the survey results was 2.90 people per household. The difference between the Census data (2.67 people per household) and survey data is 8.6%, which exceeds the sampling error of 6.0%. Dominion Energy and the OROs agreed to use the results from the demographic survey (2.90) for the ETE study. A sensitivity study was performed to determine how sensitive the ETE is to changes in the average household size. It should be noted that only resident and shadow vehicles were changed for this sensitivity study. The case considered was Scenario 1, a summer, midweek, midday, with good weather evacuation of the 2Mile Region, 5Mile Region, and entire EPZ.
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| Table M4 presents the results of this study.
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| Decreasing the average household size (increasing the total number of evacuating vehicles) by 8.6% has no impact on the 90th and 100th percentile ETE.
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| M.5 Enhancements in Evacuation Time This appendix documents sensitivity studies on critical variables that could impact ETE. Possible improvements to ETE are further discussed below:
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| Prolonging the trip generation time by an hour increases the 90th percentile ETE by 30 minutes. The 100th percentile ETE increased by 1 hour since trip generation within the EPZ dictates ETE (Section M.1). Thus, public outreach encouraging evacuees to mobilize more quickly could significantly decrease ETE.
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| Increasing the percent shadow evacuation has minimal impact (5 to 10 minutes increase) on the 90th percentile and no impact on the 100th percentile ETE (Section M.2).
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| Nonetheless, public outreach could be considered to inform those people within the EPZ (and potentially beyond the EPZ) that if they are not advised to evacuate, they should not.
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| Population growth results in more evacuating vehicles which could significantly increase ETE (Section M.3). Public outreach to inform those people within the EPZ to evacuate as a family in a single vehicle would reduce the number of evacuating vehicles and could reduce ETE or offset the impact of population growth.
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| Table M1. Evacuation Time Estimates for Trip Generation Sensitivity Study Trip Evacuation Time Estimate for Entire EPZ Generation Period 90th Percentile 100th Percentile 4:15 3:00 4:25 5:15 (Base) 3:10 5:25 6:15 3:40 6:25 Table M2. Evacuation Time Estimates for Shadow Sensitivity Study Evacuating Evacuation Time Estimate for Entire EPZ Percent Shadow Shadow Evacuation Vehicles1 90th Percentile 100th Percentile 0 0 3:10 5:25 18 (Demographic 3,811 3:10 5:25 Survey) 20 (Base) 4,234 3:10 5:25 40 8,468 3:15 5:25 60 12,702 3:15 5:25 80 16,936 3:15 5:25 100 21,170 3:20 5:25 1
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| The Evacuating Shadow Vehicles, in Table M-2, represent the residents and employees who will spontaneously decide to relocate during the evacuation. The basis, for the base values shown, is a 20% relocation of shadow residents along with a proportional percentage of shadow employees. See Section 6 for further discussion.
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| Table M3. ETE Variation with Population Change Resident Population Population Change Base
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| + 20% Shadow Population 190% 191% 192%
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| 34,762 100,810 101,158 101,505 th ETE for 90 Percentile Population Change Region Base 190% 191% 192%
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| 2MILE 4:00 4:15 4:15 4:15 5MILE 4:15 4:25 4:25 4:25 FULL EPZ 4:25 4:50 4:50 4:55 ETE for 100th Percentile Population Change Region Base 190% 191% 192%
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| 2MILE 7:00 7:00 7:00 7:00 5MILE 7:05 7:05 7:05 7:05 FULL EPZ 7:10 7:40 7:30 7:45 Table M4. ETE Results for the Change in Average Household Size Base Case Sensitivity Case EPZ and 20% Shadow (Average HH Size of 2.90 people (Average HH Size of 2.67 Permanent Resident per household) people per household)
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| Population 19,648 Vehicles 21,341 Vehicles th ETE for 90 Percentile Region Base Case Sensitivity Case 2MILE 2:45 2:45 5MILE 2:55 2:55 FULL EPZ 3:10 3:10 th ETE for 100 Percentile Region Base Case Sensitivity Case 2MILE 5:15 5:15 5MILE 5:20 5:20 FULL EPZ 5:25 5:25 North Anna Power Station M5 KLD Engineering, P.C.
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| APPENDIX N ETE Criteria Checklist
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| N. ETE CRITERIA CHECKLIST Table N1. ETE Review Criteria Checklist Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA) 1.0 Introduction
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| : a. The emergency planning zone (EPZ) and surrounding area is Yes Section 1.2 described.
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| : b. A map is included that identifies primary features of the site Yes Figures 11, 31, 61 including major roadways, significant topographical features, boundaries of counties, and population centers within the EPZ.
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| : c. A comparison of the current and previous ETE is provided Yes Section 1.4, Table 13 including information similar to that identified in Table 11, ETE Comparison.
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| 1.1 Approach
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| : a. The general approach is described in the report as outlined in Yes Section 1.1, Section 1.3, Appendix D Section 1.1, Approach.
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| 1.2 Assumptions
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| : a. Assumptions consistent with Table 12, General Yes Section 2 Assumptions, of NUREG/CR7002 are provided and include the basis to support use.
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| 1.3 Scenario Development
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| : a. The scenarios in Table 13, Evacuation Scenarios, are Yes Table 21, Section 6, Table 62 developed for the ETE analysis. A reason is provided for use of other scenarios or for not evaluating specific scenarios.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA) 1.4 Evacuation Planning Areas
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| : a. A map of the EPZ with emergency response planning areas Yes Figure 31, Figure 61 (ERPAs) is included.
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| 1.4.1 Keyhole Evacuation
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| : a. A table similar to Table 14 Evacuation Areas for a Keyhole Yes Table 61, Table 75, Table H1 Evacuation, is provided identifying the ERPAs considered for each ETE calculation by downwind direction.
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| 1.4.2 Staged Evacuation
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| : a. The approach used in development of a staged evacuation is Yes Section 7.2, Section 5.4.2 discussed.
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| : b. A table similar to Table 15, Evacuation Areas for a Staged Yes Table 61, Table 75, Table H1, Table 7 Evacuation, is provided for staged evacuations identifying 3, Table 74 the ERPAs considered for each ETE calculation by downwind direction.
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| 2.0 Demand Estimation
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| : a. Demand estimation is developed for the four population Yes Section 3 groups (permanent residents of the EPZ, transients, special facilities, and schools).
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| 2.1 Permanent Residents and Transient Population
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| : a. The U.S. Census is the source of the population values, or Yes Section 3.1 another credible source is provided.
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| : b. The availability date of the census data is provided. Yes Section 3.1 North Anna Power Station N2 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : c. Population values are adjusted as necessary for growth to NA 2020 Census used as the base year of reflect population estimates to the year of the ETE. the analysis
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| : d. A sector diagram, similar to Figure 21, Population by Yes Figure 32 Sector, is included showing the population distribution for permanent residents.
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| 2.1.1 Permanent Residents with Vehicles
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| : a. The persons per vehicle value is between 1 and 3 or Yes Section 3.1, Appendix F justification is provided for other values.
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| 2.1.2 Transient Population
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| : a. A list of facilities that attract transient populations is included, Yes Section 3.3, Table E5 and peak and average attendance for these facilities is listed.
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| The source of information used to develop attendance values is provided.
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| : b. Major employers are listed. Yes Section 3.4, Table E4
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| : c. The average population during the season is used, itemized Yes Table 34, Table 35, and Appendix E and totaled for each scenario. itemize the peak transient population and employee estimates. These estimates are multiplied by the scenario specific percentages provided in Table 63 to estimate average transient population and employee by scenario -
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| see Table 64.
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| : d. The percentage of permanent residents assumed to be at Yes Section 3.3 and Section 3.4 facilities is estimated.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : e. The number of people per vehicle is provided. Numbers may Yes Section 3.3 and Section 3.4 vary by scenario, and if so, reasons for the variation are discussed.
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| : f. A sector diagram is included, similar to Figure 21, Population Yes Figure 36 (transients) and Figure 38 by Sector, is included showing the population distribution for (employees) the transient population.
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| 2.2 Transit Dependent Permanent Residents
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| : a. The methodology (e.g., surveys, registration programs) used Yes Section 3.6 to determine the number of transit dependent residents is discussed.
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| : b. The State and local evacuation plans for transit dependent Yes Section 8.1 residents are used in the analysis.
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| : c. The methodology used to determine the number of people Yes Section 3.9 with disabilities and those with access and functional needs who may need assistance and do not reside in special facilities is provided. Data from local/county registration programs are used in the estimate.
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| : d. Capacities are provided for all types of transportation Yes Item 3 of Section 2.4 resources. Bus seating capacity of 50 percent is used or justification is provided for higher values.
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| : e. An estimate of the transit dependent population is provided. Yes Section 3.6, Table 37, Table 311 North Anna Power Station N4 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : f. A summary table showing the total number of buses, Yes Table 38, Table 312, Table 81 ambulances, or other transport assumed available to support evacuation is provided. The quantification of resources is detailed enough to ensure that double counting has not occurred.
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| 2.3 Special Facility Residents
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| : a. Special facilities, including the type of facility, location, and Yes Table E3 lists all medical facilities by average population, are listed. Special facility staff is included facility name, location, and average in the total special facility population. population. Staff estimates were not provided.
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| : b. The method of obtaining special facility data is discussed. Yes Section 3.5
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| : c. An estimate of the number and capacity of vehicles assumed Yes Section 3.5 available to support the evacuation of the facility is provided.
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| : d. The logistics for mobilizing specially trained staff (e.g., medical Yes Section 8.1 - under Evacuation of support or security support for prisons, jails, and other Medical Facilities correctional facilities) are discussed when appropriate.
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| 2.4 Schools
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| : a. A list of schools including name, location, student population, Yes Table 38, Table E1, Section 3.7 and transportation resources required to support the evacuation, is provided. The source of this information should be identified.
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| : b. Transportation resources for elementary and middle schools Yes Section 3.7 are based on 100 percent of the school capacity.
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| North Anna Power Station N5 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : c. The estimate of high school students who will use personal Yes Section 3.7 vehicle to evacuate is provided and a basis for the values used is given.
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| : d. The need for return trips is identified. Yes Section 8.1 no return trips are needed.
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| 2.5 Other Demand Estimate Considerations 2.5.1 Special Events
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| : a. A complete list of special events is provided including Yes Section 3.8 information on the population, estimated duration, and season of the event.
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| : b. The special event that encompasses the peak transient Yes Section 3.8 population is analyzed in the ETE.
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| : c. The percentage of permanent residents attending the event is Yes Section 3.8 estimated.
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| 2.5.2 Shadow Evacuation
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| : a. A shadow evacuation of 20 percent is included consistent Yes Item 7 of Section 2.2, Figure 21 and with the approach outlined in Section 2.5.2, Shadow Figure 71, Section 3.2 Evacuation.
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| : b. Population estimates for the shadow evacuation in the Yes Section 3.2, Table 33, Figure 34 shadow region beyond the EPZ are provided by sector.
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| : c. The loading of the shadow evacuation onto the roadway Yes Section 5 - Table 59 (footnote) network is consistent with the trip generation time generated for the permanent resident population.
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| 2.5.3 Background and Pass Through Traffic North Anna Power Station N6 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : a. The volume of background traffic and passthrough traffic is Yes Section 3.10, Section 3.11 based on the average daytime traffic. Values may be reduced for nighttime scenarios.
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| : b. The method of reducing background and passthrough traffic Yes Section 2.2 - Item 11 and 12 is described. Section 2.5 Section 3.10 and Section 3.11 Table 63 - External Through Traffic footnote
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| : c. Passthrough traffic is assumed to have stopped entering the Yes Section 2.5, Section 3.10 EPZ about two (2) hours after the initial notification.
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| 2.6 Summary of Demand Estimation
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| : a. A summary table is provided that identifies the total Yes Table 311, Table 312, and Table 64 populations and total vehicles used in the analysis for permanent residents, transients, transit dependent residents, special facilities, schools, shadow population, and pass through demand in each scenario.
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| 3.0 Roadway Capacity
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| : a. The method(s) used to assess roadway capacity is discussed. Yes Section 4 North Anna Power Station N7 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA) 3.1 Roadway Characteristics
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| : a. The process for gathering roadway characteristic data is Yes Section 1.3, Appendix D described including the types of information gathered and how it is used in the analysis.
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| : b. Legible maps are provided that identify nodes and links of the Yes Appendix K modeled roadway network similar to Figure A1, Roadway Network Identifying Nodes and Links, and Figure A2, Grid Map Showing Detailed Nodes and Links.
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| 3.2 Model Approach
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| : a. The approach used to calculate the roadway capacity for the Yes Section 4 transportation network is described in detail, and the description identifies factors that are expressly used in the modeling.
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| : b. Route assignment follows expected evacuation routes and Yes Appendix B and Appendix C traffic volumes.
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| : c. A basis is provided for static route choices if used to assign N/A Static route choices are not used to evacuation routes. assign evacuation routes. Dynamic traffic assignment is used.
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| : d. Dynamic traffic assignment models are described including Yes Appendix B and Appendix C calibration of the route assignment.
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| 3.3 Intersection Control
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| : a. A list that includes the total numbers of intersections Yes Table K1 modeled that are unsignalized, signalized, or manned by response personnel is provided.
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| North Anna Power Station N8 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : b. The use of signal cycle timing, including adjustments for Yes Section 4, Appendix G manned traffic control, is discussed.
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| 3.4 Adverse Weather
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| : a. The adverse weather conditions are identified. Yes Item 2 and 3 of Section 2.6
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| : b. The speed and capacity reduction factors identified in Table 3 Yes Table 22 1, Weather Capacity Factors, are used or a basis is provided for other values, as applicable to the model.
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| : c. The calibration and adjustment of driver behavior models for N/A Driver behavior is not adjusted for adverse weather conditions are described, if applicable. adverse weather conditions.
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| : d. The effect of adverse weather on mobilization is considered Yes Item 6 of Section 2.6, Table 22 and assumptions for snow removal on streets and driveways are identified, when applicable.
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| 4.0 Development of Evacuation Times 4.1 Traffic Simulation Models
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| : a. General information about the traffic simulation model used Yes Section 1.3, Table 13, Appendix B, in the analysis is provided. Appendix C
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| : b. If a traffic simulation model is not used to perform the ETE N/A Not applicable since a traffic simulation calculation, sufficient detail is provided to validate the model was used.
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| analytical approach used.
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| 4.2 Traffic Simulation Model Input
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| : a. Traffic simulation model assumptions and a representative set Yes Section 2, Appendix J of model inputs are provided.
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| North Anna Power Station N9 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : b. The number of origin nodes and method for distributing Yes Appendix J, Appendix C vehicles among the origin nodes are described.
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| : c. A glossary of terms is provided for the key performance Yes Appendix A, Table C1, and Table C3 measures and parameters used in the analysis.
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| 4.3 Trip Generation Time
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| : a. The process used to develop trip generation times is Yes Section 5 identified.
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| : b. When surveys are used, the scope of the survey, area of the Yes Appendix F survey, number of participants, and statistical relevance are provided.
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| : c. Data used to develop trip generation times are summarized. Yes Appendix F, Section 5
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| : d. The trip generation time for each population group is Yes Section 5 developed from sitespecific information.
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| : e. The methods used to reduce uncertainty when developing N/A There was no uncertainty when trip generation times are discussed, if applicable. developing trip generation times.
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| 4.3.1 Permanent Residents and Transient Population North Anna Power Station N10 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : a. Permanent residents are assumed to evacuate from their Yes Section 5 discusses trip generation for homes but are not assumed to be at home at all times. Trip households with and without returning generation time includes the assumption that a percentage of commuters.
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| residents will need to return home before evacuating. Table 63 presents the percentage of households with returning commuters and the percentage of households either without returning commuters or with no commuters.
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| Appendix F presents the percent households who will await the return of commuters.
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| Item 3 of Section 2.3
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| : b. The trip generation time accounts for the time and method to Yes Section 5 notify transients at various locations.
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| : c. The trip generation time accounts for transients potentially Yes Section 5, Figure 51 returning to hotels before evacuating.
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| : d. The effect of public transportation resources used during Yes Section 3.8 special events where a large number of transients are Public Transportation is not provided expected is considered. for the special event and was therefore not considered.
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| North Anna Power Station N11 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA) 4.3.2 Transit Dependent Permanent Residents
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| : a. If available, existing and approved plans and bus routes are Yes Section 8.1 under Evacuation of Transit used in the ETE analysis. Dependent People (Residents without access to a vehicle)
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| : b. The means of evacuating ambulatory and nonambulatory Yes Section 8.1 under Evacuation of Transit residents are discussed. Dependent People (Residents without access to a vehicle)
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| Section 8.2
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| : c. Logistical details, such as the time to obtain buses, brief Yes Section 8.1, Figure 81 drivers and initiate the bus route are used in the analysis.
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| : d. The estimated time for transit dependent residents to Yes Section 8.1 under Evacuation of Transit prepare and then travel to a bus pickup point, including the Dependent People (Residents without expected means of travel to the pickup point, is described. access to a vehicle)
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| : e. The number of bus stops and time needed to load passengers Yes Section 8.1, Table 85 though Table 87 are discussed.
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| : f. A map of bus routes is included. Yes Figure 102, Figure 103, Figure 104
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| : g. The trip generation time for nonambulatory persons Yes Section 8.2 including the time to mobilize ambulances or special vehicles, time to drive to the home of residents, time to load, and time to drive out of the EPZ, is provided.
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| : h. Information is provided to support analysis of return trips, if Yes Sections 8.1 and 8.2 no return trips are necessary. needed.
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| 4.3.3 Special Facilities North Anna Power Station N12 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : a. Information on evacuation logistics and mobilization times is Yes Section 2.4, Section 8.1, Table 88 provided.
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| : b. The logistics of evacuating wheelchair and bed bound Yes Section 8.1, Table 88 residents are discussed.
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| : c. Time for loading of residents is provided. Yes Section 2.4, Section 8.1, Table 88
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| : d. Information is provided that indicates whether the evacuation Yes Section 8.1 can be completed in a single trip or if additional trips are needed.
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| : e. Discussion is provided on whether special facility residents Yes Section 8.1 are expected to pass through the reception center before being evacuated to their final destination.
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| : f. Supporting information is provided to quantify the time Yes Section 8.1 elements for each trip, including destinations if return trips are needed.
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| 4.3.4 Schools
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| : a. Information on evacuation logistics and mobilization times is Yes Section 2.4, Section 8.1, Table 82 provided. through Table 84
| |
| : b. Time for loading of students is provided. Yes Section 2.4, Section 8.1, Table 82 through Table 84
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| : c. Information is provided that indicates whether the evacuation Yes Section 8.1 can be completed in a single trip or if additional trips are needed.
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| North Anna Power Station N13 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : d. If used, reception centers should be identified. A discussion is Yes Section 8.1, Table 103 provided on whether students are expected to pass through the reception center before being evacuated to their final destination.
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| : e. Supporting information is provided to quantify the time Yes Section 8.1, Table 82 through Table 84 elements for each trip, including destinations if return trips are needed.
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| 4.4 Stochastic Model Runs
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| : a. The number of simulation runs needed to produce average N/A DYNEV does not rely on simulation results is discussed. averages or random seeds for statistical
| |
| : b. If one run of a single random seed is used to produce each N/A confidence. For DYNEV/DTRAD, it is a ETE result, the report includes a sensitivity study on the 90 mesoscopic simulation and uses percent and 100 percent ETE using 10 different random seeds dynamic traffic assignment model to for evacuation of the full EPZ under Summer, Midweek, obtain the "average" (stable) network Daytime, Normal Weather conditions. work flow distribution. This is different from microscopic simulation, which is montecarlo random sampling by nature relying on different seeds to establish statistical confidence. Refer to Appendix B for more details.
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| North Anna Power Station N14 KLD Engineering, P.C.
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA) 4.5 Model Boundaries
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| : a. The method used to establish the simulation model Yes Section 4.5 boundaries is discussed.
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| : b. Significant capacity reductions or population centers that may Yes Section 4.5 influence the ETE and that are located beyond the evacuation area or shadow region are identified and included in the model, if needed.
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| 4.6 Traffic Simulation Model Output
| |
| : a. A discussion of whether the traffic simulation model used Yes Appendix B must be in equilibration prior to calculating the ETE is provided.
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| : b. The minimum following model outputs for evacuation of the Yes 1. Appendix J, Table J2 entire EPZ are provided to support review: 2. Table J2
| |
| : 1. Evacuee average travel distance and time. 3. Table J4
| |
| : 2. Evacuee average delay time. 4. None and 0%. 100 percent ETE is
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| : 3. Number of vehicles arriving at each destination node. based on the time the last
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| : 4. Total number and percentage of evacuee vehicles not vehicle exits the evacuation exiting the EPZ. zone
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| : 5. A plot that provides both the mobilization curve and 5. Figures J2 through J15 (one evacuation curve identifying the cumulative percentage of plot for each scenario evacuees who have mobilized and exited the EPZ. considered)
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| : 6. Average speed for each major evacuation route that exits 6. Table J3 the EPZ.
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| North Anna Power Station N15 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : c. Color coded roadway maps are provided for various times Yes Figure 73 through Figure 78 (e.g., at 2, 4, 6 hrs.) during a full EPZ evacuation scenario, identifying areas where congestion exists.
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| 4.7 Evacuation Time Estimates for the General Public
| |
| : a. The ETE includes the time to evacuate 90 percent and 100 Yes Table 71 and Table 72 percent of the total permanent resident and transient population.
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| : b. Termination criteria for the 100 percent ETE are discussed, if N/A 100 percent ETE is based on the time not based on the time the last vehicle exits the evacuation the last vehicle exits the evacuation zone. zone.
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| : c. The ETE for 100 percent of the general public includes all Yes Section 5.4.1 - truncating survey data members of the general public. Any reductions or truncated to eliminate statistical outliers data is explained. Table 72 - 100th percentile ETE for general population
| |
| : d. Tables are provided for the 90 and 100 percent ETEs similar to Yes Table 73 and Table 74 Table 43, ETEs for a Staged Evacuation, and Table 44, ETEs for a Keyhole Evacuation.
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| : e. ETEs are provided for the 100 percent evacuation of special Yes Section 8 facilities, transit dependent, and school populations.
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| 5.0 Other Considerations 5.1 Development of Traffic Control Plans
| |
| : a. Information that responsible authorities have approved the Yes Section 9, Appendix G traffic control plan used in the analysis are discussed.
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| North Anna Power Station N16 KLD Engineering, P.C.
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| Evacuation Time Estimate Rev. 0
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| Addressed in ETE NRC Review Criteria Analysis Comments (Yes/No/NA)
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| : b. Adjustments or additions to the traffic control plan that affect Yes Section 9, Appendix G the ETE is provided.
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| 5.2 Enhancements in Evacuation Time
| |
| : a. The results of assessments for enhancing evacuations are Yes Appendix M provided.
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| 5.3 State and Local Review
| |
| : a. A list of agencies contacted is provided and the extent of Yes Table 11 interaction with these agencies is discussed.
| |
| : b. Information is provided on any unresolved issues that may Yes Results of the ETE study were formally affect the ETE. presented to state and local authorities at the final project meeting. There are no unresolved issues.
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| 5.4 Reviews and Updates
| |
| : a. The criteria for when an updated ETE analysis is required to Yes Appendix M, Section M.3 be performed and submitted to the NRC is discussed.
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| 5.4.1 Extreme Conditions
| |
| : a. The updated ETE analysis reflects the impact of EPZ conditions N/A This ETE is being updated as a result of not adequately reflected in the scenario variations. the availability of US Census Bureau decennial census data.
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| 5.5 Reception Centers and Congregate Care Center
| |
| : a. A map of congregate care centers and reception centers is Yes Figure 105 provided.
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| North Anna Power Station N17 KLD Engineering, P.C.
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