ML22257A279

Revised Evacuation Time Estimate Analysis

ML22257A279
Person / Time
Site:	South Texas
Issue date:	09/14/2022
From:	Cramer G South Texas
To:	Document Control Desk, Office of Nuclear Reactor Regulation
References
NOC-AE-22003915, STI: 35364239
Download: ML22257A279 (1)

Text

3Jr N Operqting Compony Soulh Tens Proiect Electric GenratinE Station PO Eox 289 Wadsworth, Texas 77483 September 14,2022 NOC-AE-22003915 STI: 35364239 10 CFR 50, Appendix E Attention: Document Control Desk U.S. Nuclear Regulatory Commission Washington, DC 20555-0001 South Texas Project Units 1 and2 Docket Nos. STN 50-498 and STN 50-499 Revised Evacuation Time Estimate Analvsis Pursuant to '10 CFR 50, Appendix E, Section lV, STP Nuclear Operating Company is submitting the enclosed revised Evacuation Time Estimate (ETE) analysis based on the most recent decennial census data. The ETE analysis was revised based on guidance provided in NUREG/CR-7002, Revision 1, "Criteria for Development of Evacuation Time Estimate Studies." Appendix N of the enclosed revised ETE analysis provides a cross-reference between the evaluation criteria in Appendix B of NUREG/CR-7002, Revision 1, and the sections of the revised ETE analysis.

There are no commitments in this correspondence.

lf you have any questions concerning this submittal, please contact Stephanie Rodgers at (361) 972-4527 or myself at (361) 972-4283.

crbg er Emergency Response Manager scr Enclosure south Texas Project Electric Generating station Development of Evacuation Time Estimates

NOC-AE-22003915 Page2 of 2 cc:

Regional Administrator, Region lV U.S. Nuclear Regulatory Commission 1600 E. Lamar Boulevard Arlington, TX 7601 1-4511 Dennis Galvin Project Manager U.S. Nuclear Regulatory Commission Office of Nuclear Reactor Regulation Division of Operating Reactor Licensing Licensing Project Branch 4 Gregory Kolcum Senior Resident lnspector, South Texas Project U.S. Nuclear Regulatory Commission Chad Stott Resident lnspector, South Texas Project U.S. Nuclear Regulatory Commission

South Texas Project Electric Generating Station Development of Evacuation Time Estimates Work performed for South Texas Project Nuclear Operating Company by:

KLD Engineering, P.C.

1601 Veterans Memorial Highway, Suite 340 Islandia, NY 11749 Email: kweinisch@kldcompanies.com July 29, 2022 Final Report, Rev. 0 KLD TR - 1244

Table of Contents ACRONYM LIST ......................................................................................................................................... AL1 EXECUTIVE

SUMMARY

............................................................................................................................. ES1 1 INTRODUCTION .................................................................................................................................. 11 1.1 Overview of the ETE Process...................................................................................................... 11 1.2 The South Texas Project Electric Generating 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 Estimate Assumptions ....................................................................................................... 21 2.2 Methodological Assumptions .................................................................................................... 22 2.3 Assumptions on Mobilization Times .......................................................................................... 23 2.4 Transit Dependent Assumptions ................................................................................................ 24 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 3.4 Employees .................................................................................................................................. 34 3.5 School Population Demand........................................................................................................ 34 3.6 Transit Dependent Population ................................................................................................... 35 3.7 Special Event .............................................................................................................................. 37 3.8 External Traffic ........................................................................................................................... 37 3.9 Background Traffic ..................................................................................................................... 38 3.10 Summary of Demand ................................................................................................................. 38 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 South Texas Project Nuclear Generating Station Study Area ...................... 46 4.3.1 TwoLane Roads ................................................................................................................. 46 4.3.2 Multilane Highway ............................................................................................................. 47 4.3.3 Intersections ...................................................................................................................... 47 4.4 Simulation and Capacity Estimation .......................................................................................... 47 4.5 Boundary Conditions .................................................................................................................. 48 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 5.4 Calculation of Trip Generation Time Distribution ...................................................................... 55 5.4.1 Statistical Outliers .............................................................................................................. 55 5.4.2 Application to the South Texas Project Electric Generating Station.................................. 57 5.4.3 Staged Evacuation Trip Generation ................................................................................... 58 5.4.4 Trip Generation for Waterways and Recreational Areas ................................................. 510 6 EVACUATION CASES ........................................................................................................................... 61 7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE) .......................................................... 71 South Texas Project Electric Generating Station i KLD Engineering, P.C.

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7.1 Voluntary Evacuation and Shadow Evacuation ......................................................................... 71 7.2 Staged Evacuation ...................................................................................................................... 71 7.3 Patterns of Traffic Congestion during Evacuation ..................................................................... 72 7.4 Evacuation Rates ........................................................................................................................ 73 7.5 Evacuation Time Estimate (ETE) Results .................................................................................... 74 7.6 Staged Evacuation Results ......................................................................................................... 75 7.7 Guidance on Using ETE Tables ................................................................................................... 76 8 TRANSITDEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES ................................. 81 8.1 ETEs for Schools and Transit Dependent People ....................................................................... 82 9 TRAFFIC MANAGEMENT STRATEGY ................................................................................................... 91 9.1 Assumptions ............................................................................................................................... 92 9.2 Additional Considerations .......................................................................................................... 92 10 EVACUATION ROUTES AND RECEPTION CENTERS ........................................................................... 101 10.1 Evacuation Routes.................................................................................................................... 101 10.2 Reception Centers/Host Schools.............................................................................................. 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 D. DETAILED DESCRIPTION OF STUDY PROCEDURE .................................................................................. 1 E. 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 TACP Locations ................................................................................................. G1 H EVACUATION REGIONS ..................................................................................................................... H1 J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM ..................................... J1 South Texas Project Electric Generating Station ii KLD Engineering, P.C.

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K. EVACUATION ROADWAY NETWORK .................................................................................................. K1 APPENDIX L ................................................................................................................................................ L0 L. protective response zone (PRZ) boundaries ...................................................................................... L1 M. EVACUATION SENSITIVITY STUDIES ................................................................................................. M1 M.1 Effect of Changes in Trip Generation Times ............................................................................ M1 M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate ................. M1 M.3 Effect of Changes in the Permanent Resident Population ....................................................... M2 M.4 Effect of Changes in Average Household Size .......................................................................... M3 M.5 Enhancements in Evacuation Time .......................................................................................... M4 N. ETE CRITERIA CHECKLIST ................................................................................................................... N1 Note: Appendix I intentionally skipped List of Figures Figure 11. STP Location ........................................................................................................................... 112 Figure 12. STP LinkNode Analysis Network ........................................................................................... 113 Figure 21. Voluntary Evacuation Methodology ........................................................................................ 28 Figure 31. PRZs Comprising the STP EPZ ................................................................................................. 315 Figure 32. Permanent Resident Population by Sector ............................................................................ 316 Figure 33. Permanent Resident Vehicles by Sector ................................................................................ 317 Figure 34. Shadow Resident Population by Sector ................................................................................. 318 Figure 35. Shadow Vehicles by Sector .................................................................................................... 319 Figure 36. Transient Population by Sector.............................................................................................. 320 Figure 37. Transient Vehicles by Sector .................................................................................................. 321 Figure 38. Employee Population by Sector ............................................................................................. 322 Figure 39. Employee Vehicles by Sector ................................................................................................. 323 Figure 41. Fundamental Diagrams ............................................................................................................ 49 Figure 51. Events and Activities Preceding the Evacuation Trip ............................................................. 518 Figure 52. Time Distributions for Evacuation Mobilization Activities .................................................... 519 Figure 53. Comparison of Data Distribution and Normal Distribution ...................................................... 520 Figure 54. Comparison of Trip Generation Distributions ....................................................................... 521 Figure 55. Comparison of the Time to Prepare Home for Evacuation of STP vs. CPNPP ....................... 522 Figure 56. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region .................................................................................................... 523 Figure 61. PRZs Comprising the STP EPZ ................................................................................................... 68 Figure 71. Voluntary Evacuation Methodology ...................................................................................... 716 Figure 72. STP Shadow Region................................................................................................................ 717 Figure 73. Congestion Patterns at 45 Minutes after the Advisory to Evacuate ..................................... 718 Figure 74. Congestion Patterns at 1 Hours and 5 Minutes after the Advisory to Evacuate ................... 719 Figure 75. Congestion Patterns at 1 Hour and 45 minutes after the Advisory to Evacuate ................... 720 Figure 76. Congestion Patterns at 2 Hours and 35 Minutes after the Advisory to Evacuate ................. 721 Figure 77. Evacuation Time Estimates Scenario 1 for Region R03 ....................................................... 722 Figure 78. Evacuation Time Estimates Scenario 2 for Region R03 ....................................................... 722 Figure 79. Evacuation Time Estimates Scenario 3 for Region R03 ....................................................... 723 Figure 710. Evacuation Time Estimates Scenario 4 for Region R03 ..................................................... 723 Figure 711. Evacuation Time Estimates Scenario 5 for Region R03 ..................................................... 724 South Texas Project Electric Generating Station iii KLD Engineering, P.C.

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Figure 712. Evacuation Time Estimates Scenario 6 for Region R03 ..................................................... 724 Figure 713. Evacuation Time Estimates Scenario 7 for Region R03 ..................................................... 725 Figure 714. Evacuation Time Estimates Scenario 8 for Region R03 ..................................................... 725 Figure 715. Evacuation Time Estimates Scenario 9 for Region R03 ..................................................... 726 Figure 716. Evacuation Time Estimates Scenario 10 for Region R03 ................................................... 726 Figure 717. Evacuation Time Estimates Scenario 11 for Region R03 ................................................... 727 Figure 718. Evacuation Time Estimates Scenario 12 for Region R03 ................................................... 727 Figure 81. Chronology of Transit Evacuation Operations ......................................................................... 88 Figure 101. Evacuation Routes ............................................................................................................... 104 Figure 102. TransitDependent Bus Routes ............................................................................................ 105 Figure 103. Reception Centers and Host Schools .................................................................................. 106 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 .......................................................................................................... 5 Figure E1. Schools within the EPZ ............................................................................................................. E4 Figure E2. Major Employers within the EPZ.............................................................................................. E5 Figure E3. Recreational Areas within the EPZ ........................................................................................... E6 Figure E4. Lodging Facilities within the EPZ .............................................................................................. E7 Figure F1. Household Size in the EPZ ........................................................................................................ F7 Figure F2. Household Vehicle Availability ................................................................................................. F7 Figure F3. Vehicle Availability 1 to 4 Person Households ....................................................................... F8 Figure F4. Vehicle Availability 5 to 8 Person Households ....................................................................... F8 Figure F5. Household Ridesharing Preference ......................................................................................... F9 Figure F6. Commuters per Households in the EPZ ................................................................................... F9 Figure F7. Modes of Travel in the EPZ .................................................................................................... F10 Figure F8. Impact to Commuters due to the COVID19 Pandemic ......................................................... F10 Figure F9. Households with Functional or Transportation Needs .......................................................... F11 Figure F10. Number of Vehicles Used for Evacuation ............................................................................ F11 Figure F11. Percent of Households that Await Returning Commuter Before Leaving ....................................................................................................................... F12 Figure F12. Shelter in Place Characteristics ............................................................................................ F12 Figure F13. Shelter Then Evacuate Characteristics ................................................................................. F13 Figure F14. Study Area Evacuation Destinations .................................................................................... F13 Figure F15. Households Evacuating with Pets/Animals .......................................................................... F14 Figure F16. Time Required to Prepare to Leave Work/College .............................................................. F14 Figure F17. Time to Commute Home from Work/College...................................................................... F15 Figure F18. Time to Prepare Home for Evacuation ................................................................................ F15 Figure F19. Cell Phone Signal Reliability ................................................................................................. F16 Figure F20. Likelihood to Take Action Based off Emergency Management Officials Guidelines ............................................................................................................ F16 Figure F21. Emergency Communication Alert ........................................................................................ F17 Figure G1. Traffic and Access Control Points for the STP EPZ ................................................................. G4 Figure H1. Region R01 ............................................................................................................................. H3 Figure H2. Region R02 ............................................................................................................................. H4 South Texas Project Electric Generating Station iv KLD Engineering, P.C.

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Figure H3. Region R03 ............................................................................................................................. H5 Figure H4. Region R04 ............................................................................................................................. H6 Figure H5. Region R05 ............................................................................................................................. H7 Figure H6. Region R06 ............................................................................................................................. H8 Figure H7. Region R07 ............................................................................................................................. H9 Figure H8. Region R08 ........................................................................................................................... H10 Figure H9. Region R09 ........................................................................................................................... H11 Figure H10. Region R10 ......................................................................................................................... H12 Figure H11. Region R11 ......................................................................................................................... H13 Figure H12. Region R12 ......................................................................................................................... H14 Figure H13. Region R13 ......................................................................................................................... H15 Figure H14. Region R14 ......................................................................................................................... H16 Figure H15. Region R15 ......................................................................................................................... H17 Figure H16. Region R16 ......................................................................................................................... H18 Figure H17. Region R17 ......................................................................................................................... H19 Figure H18. Region R18.......................................................................................................................... H20 Figure H19. Region R19 ......................................................................................................................... H21 Figure H20. Region R20 ......................................................................................................................... H22 Figure H21. Region R21.......................................................................................................................... H23 Figure H22. Region R22.......................................................................................................................... H24 Figure H23. Region R23.......................................................................................................................... H25 Figure H24. Region R24.......................................................................................................................... H26 Figure H25. Region R25 ......................................................................................................................... H27 Figure H26. Region R26 ......................................................................................................................... H28 Figure H27. Region R27.......................................................................................................................... H29 Figure H28. Region R28 ......................................................................................................................... H30 Figure H29. Region R29 ......................................................................................................................... H31 Figure H30. Region R30 ......................................................................................................................... H32 Figure H31. Region R31 ......................................................................................................................... H33 Figure H32. Region R32 ......................................................................................................................... H34 Figure J1. Network Sources/Origins.......................................................................................................... J4 Figure J2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1) ...................................................................................................................... J5 Figure J3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2) ....................................................................................................................................... J5 Figure J4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3) ....................................................................................................................... J6 Figure J5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4) ....................................................................................................................................... J6 Figure J6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5) ......................................................................................................... J7 Figure J7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6) ...................................................................................................................... J7 Figure J8. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7) ........................................................................................................................................ J8 Figure J9. ETE and Trip Generation: Winter, Weekend, Midday, Good (Scenario 8) ...................................................................................................................................... J8 South Texas Project Electric Generating Station v KLD Engineering, P.C.

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Figure J10. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 9) ........................................................................................................................................ J9 Figure J11. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 10) ....................................................................................................... J9 Figure J12. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather, Special Event (Scenario 11) ............................................................................................ J10 Figure J13. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 12) ...................................................................................... J10 Figure K1. STP 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 South Texas Project Electric Generating Station vi 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 ........................................................................................ 39 Table 32. Permanent Resident Population and Vehicles by PRZ .............................................................. 39 Table 33. Shadow Population and Vehicles by Sector ............................................................................ 310 Table 34. Summary of Transients and Transient Vehicles ...................................................................... 310 Table 35. Summary of Employees and Employee Vehicles Commuting into the EPZ ............................ 311 Table 36. School Population Demand Estimates .................................................................................... 311 Table 37. TransitDependent Population Estimates ............................................................................... 312 Table 38. STP EPZ External Traffic........................................................................................................... 312 Table 39. Summary of Population Demand ............................................................................................ 313 Table 310. Summary of Vehicle Demand................................................................................................ 314 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 .................................................. 512 Table 54. Time Distribution for Commuters to Travel Home ................................................................. 513 Table 55. Time Distribution for Population to Prepare to Evacuate ...................................................... 514 Table 56. Time Distribution for Population to Prepare to Evacuate - from CPNPP survey ................... 514 Table 57. Mapping Distributions to Events............................................................................................. 515 Table 58. Description of the Distributions .............................................................................................. 515 Table 59. Trip Generation Histograms for the EPZ Population for Unstaged Evacuation ..................... 516 Table 510. Trip Generation Histograms for the EPZ Population for Staged Evacuation ........................ 517 Table 61. Description of Evacuation Regions ........................................................................................... 64 Table 62. Evacuation Scenario Definitions ............................................................................................... 65 Table 63. Percent of Population Groups Evacuating for Various Scenarios ............................................. 66 Table 64. Vehicle Estimates by Scenario .................................................................................................. 67 Table 71. Time to Clear the Indicated Area of 90 Percent of the Affected Population ............................ 79 Table 72. Time to Clear the Indicated Area of 100 Percent of the Affected Population ........................ 711 Table 73. Time to Clear 90 Percent of the 2Mile Region within the Indicated Region ......................... 713 Table 74. Time to Clear 100 Percent of the 2Mile Region within the Indicated Region ....................... 714 Table 75. Description of Evacuation Regions ......................................................................................... 715 Table 81. Summary of Transportation Resources .................................................................................... 86 Table 82. School Evacuation Time Estimates Good Weather................................................................. 86 Table 83. School Evacuation Time Estimates - Rain ................................................................................. 87 Table 84. TransitDependent Evacuation Time Estimates Good Weather ............................................. 87 Table 85. TransitDependent Evacuation Time Estimates Rain .............................................................. 87 Table 101. Summary of TransitDependent Bus Routes ......................................................................... 103 Table 102. Bus Route Descriptions ......................................................................................................... 103 Table 103. Host Schools for School Evacuation ...................................................................................... 103 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 South Texas Project Electric Generating Station vii KLD Engineering, P.C.

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Table C3. Glossary ..................................................................................................................................C10 Table E1. Schools within the EPZ .............................................................................................................. E2 Table E2. Major Employers within the EPZ ............................................................................................... E2 Table E3. Recreational Areas within the EPZ ............................................................................................ E3 Table E4. Lodging Facilities within the EPZ ............................................................................................... E3 Table F1. STP Demographic Survey Sampling Plan ................................................................................... F6 Table G1. List of Key Manual Traffic Control Locations ........................................................................... G3 Table G2. ETE with No Manual Traffic Control ....................................................................................... G3 Table H1. Percent of PRZ 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)................................................................................... J3 Table J4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 .............................................................................................................................. J3 Table K1. Summary of Nodes by the Type of Control ............................................................................... K1 Table M1. Evacuation Time Estimates for Trip Generation Sensitivity Study ........................................ M5 Table M2. Evacuation Time Estimates for Shadow Sensitivity Study ..................................................... M5 Table M3. ETE Variation with Population Change .................................................................................. M5 Table M4. ETE Results for Change in Average Household Size............................................................... M6 Table N1. ETE Review Criteria Checklist ................................................................................................. N1 South Texas Project Electric Generating Station viii KLD Engineering, P.C.

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ACRONYM LIST Table 1. Acronym List ACRONYM DEFINITION AADT Average Annual Daily Traffic ACP Access Control Point ANS Alert and Notification System ASLB Atomic Safety and Licensing Board ATE Advisory to Evacuate ATIS Automated Traveler Information Systems BFFS Base Free Flow Speed CR County Road COVID19 Coronavirus Disease 2019 D Destination DDHV Directional Design Hourly Volume DHV Design Hour Volume DMS Dynamic Message Sign DTA Dynamic Traffic Assignment DTRAD Dynamic Traffic Assignment and Distribution DYNEV Dynamic Network Evacuation EAS Emergency Alert System EOC Emergency Operations Center EPZ Emergency Planning Zone EPFAQ Emergency Planning Frequently Asked Question ETE Evacuation Time Estimate EVAN Evacuation Animator EMA Emergency Management Agency FEMA Federal Emergency Management Agency FFS Free Flow Speed FHWA Federal Highway Administration FM Farm to Market GIS Geographic Information System HAR Highway Advisory Radio HCM Highway Capacity Manual HH Household HPMS Highway Performance Monitoring System HS Host School ITS Intelligent Transportation Systems LOS Level of Service MOE Measures of Effectiveness South Texas Project Electric Generating Station AL1 KLD Engineering, P.C.

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ACRONYM DEFINITION mph Miles Per Hour MUTCD Manual of Uniform Traffic Control Devices MTC Manual Traffic Control NB Northbound NOAA The National Oceanic and Atmospheric Administration NRC United States Nuclear Regulatory Commission O Origin OD OriginDestination ORO Offsite Response Organization PAR Protective Action Recommendation pce Passenger Car Equivalent pcphpl passenger car per hour per lane PRZ Protective Response Zone PSL PathSizeLogit QDF Queue Discharge Flow RC Reception Center SH State Highway STP South Texas Project Electric Generating Station STPNOC South Texas Project Nuclear Operating Company SV Service Volume TA Traffic Assignment TCP Traffic Control Point TD Trip Distribution TI Time Interval TMP Traffic Management Plan TxDOT Texas Department of Transportation UNITES Unified Transportation Engineering System USDOT United States Department of Transportation vph Vehicles Per Hour vpm Vehicles Per Minute South Texas Project Electric Generating Station AL2 KLD Engineering, P.C.

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EXECUTIVE

SUMMARY

This report describes the analyses undertaken and the results obtained by a study to develop Evacuation Time Estimates (ETE) for the South Texas Project Electric Generating Station (STP) located in Matagorda County, Texas. ETE are part of the required planning basis and provide South Texas Project Nuclear Operating Company (STPNOC) and state and local governments with sitespecific information needed for Protective Action decisionmaking.

In the performance of this effort, guidance is provided by documents published by Federal Governmental agencies. Most important of these are:

• Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.

• Revision 1 of the Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR7002, February 2021.

• 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.

Project Activities This project began in April 2021 and extended over a period of about 15 months. The major activities performed are briefly described in chronological sequence:

Conducted a virtual kickoff meeting with STPNOC personnel and emergency management personnel representing state and county agencies.

Accessed the U.S. Census Bureau data files for the year 2020.

Estimated the number of employees who reside outside the Emergency Planning Zone (EPZ1) and commute to work within the EPZ based upon data provided by Matagorda County. The plant employee data was provided by STPNOC.

Studied Geographic Information Systems (GIS) maps of the area in the vicinity of the STP, then conducted a detailed field survey of the highway network to observe any roadway changes relative to the previous ETE study done in 2012. Obtained construction plans for roadway improvements that were scheduled for completion prior to the finalization of this report, as per NUREG/CR7002, Rev. 1.

Updated the analysis network representing the highway system topology and capacities within the EPZ, plus a Shadow Region covering the region between the EPZ boundary and approximately 15 miles radially from the plant.

Used the existing Protective Response Zones (PRZ) to identify regions.

1 All references to EPZ refer to the plume exposure pathway EPZ.

South Texas Project Electric Generating Station ES1 KLD Engineering, P.C.

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Designed and conducted an 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 offsite response organization (ORO) personnel prior to the survey. In addition, results from the Comanche Peak Nuclear Power Plant (CPNPP) in Glen Rose, Texas was used to determine the Time Distribution for Population to Prepare to Evacuate. Refer to Section 5.4.2 and Appendix F for more information.

A data needs matrix (requesting data) was provided to STPNOC and the OROs at the kickoff meeting. Available data was provided by Matagorda County emergency management officials for transient attractions and schools. Internet searches were also utilized, where data was missing. If updated information was not provided or available, the data gathered for the 2012 ETE study was utilized (reviewed and confirmed accurate by OROs).

The traffic demand and tripgeneration rates of evacuating vehicles were estimated from the gathered data. The trip generation rates reflect the estimated mobilization 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 and the use of the Time Distribution for Population to Prepare to Evacuate from the CPNPP survey.

Following federal guidelines, the existing 11 PRZs2, within the EPZ, are grouped within circular areas or keyhole configurations (circles plus radial sectors) that define a total of 32 Evacuation Regions (numbered R01 through R32).

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).

One special event scenario for a holiday weekend with beachgoers at Matagorda Beach was considered. One roadway impact scenario was considered wherein a full closure of FM 521 Eastbound (from FM 2668 to SH 60) and Westbound (FM 1468 to CR 392) for the duration of the evacuation.

Staged evacuation was considered for those regions wherein the 2Mile Region and sectors downwind to 5 miles are evacuated.

As per NUREG/CR7002, Rev. 1, the Planning Basis for the calculation of ETE is:

A rapidly escalating accident at the STP that quickly assumes the status of a general emergency wherein evacuation is ordered promptly, and no early protective actions have been implemented such that the Advisory to Evacuate (ATE) is virtually coincident with the Integrated Public Alert and Warning System (IPAWS) notification.

2 PRZ 1 also includes the South Texas Project Reservoir.

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While an unlikely accident 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.

If the emergency occurs while schools are in session, the ETE study assumes that the children will be evacuated by bus directly to host schools located outside the EPZ. Parents, relatives, and neighbors are advised to not pick up their children at school prior to the arrival of the buses dispatched for that purpose. The ETE for schoolchildren are calculated separately.

Evacuees who do not have access to a private vehicle will either rideshare with relatives, friends, or neighbors, or be evacuated by buses, provided by the County of Matagorda.

Separate ETE are calculated for the transitdependent evacuees.

Attended final meeting with STPNOC personnel and emergency management personnel representing state and county agencies to present results from the study..

Computation of ETE A total of 384 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 32 Evacuation Regions to evacuate from that Region, under the circumstances defined for one of the 12 Evacuation Scenarios (32 x 12 = 384). Separate ETE are calculated for transitdependent evacuees, including schoolchildren for applicable scenarios.

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 percent of the people within the impacted region will evacuate in response to this Advisory. The people occupying the remainder of the EPZ outside the impacted region may be advised to take shelter.

The computation of ETE assumes that 20 percent of the population within the EPZ, but outside the impacted region, will elect to voluntarily evacuate. In addition, 20 percent 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.

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 percent of the 2Mile Region is evacuated, those people beyond 2 miles begin to evacuate. As per federal guidance, 20 percent 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:

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.

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.

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.

The ETE statistics provide the elapsed times for 90 percent and 100 percent, 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.

Traffic Management This study reviewed, modeled and analyzed the existing comprehensive traffic management plans provided by Matagorda County. Due to the limited traffic congestion within the EPZ, no additional Traffic and Access Control Points (TACPs) have been identified as a result of this study.

Refer to Section 9 and Appendix G.

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.

Table 31 presents the estimates of permanent resident population in each PRZ based on the 2020 Census data.

Table 61 defines each of the 32 Evacuation Regions in terms of their respective groups of PRZs.

Table 62 defines the 12 Evacuation Scenarios.

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 percent 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 the ETE for the 2Mile Region, when evacuating additional PRZ downwind to 5miles for unstaged and staged evacuations for the 90th and 100th percentile ETE, respectively.

Table 82 presents the ETE for the schools in good weather.

Table 84 presents the ETE for the transitdependent population in good weather.

Table M3 compares the results of the sensitivity study conducted to determine the effect on ETE due to changes in the permanent resident population within the study area (EPZ plus Shadow Region).

Figure 61 displays a map of the STP EPZ showing the layout of the 11 PRZs that comprise, in aggregate, the EPZ.

Figure H8 presents an example of an Evacuation Region (Region R08) to be evacuated under the circumstances defined in Table 61. Maps of all Regions are provided in Appendix H.

Conclusions General population ETE were computed for 384 unique cases - a combination of 32 unique Evacuation Regions and 12 Evacuation Scenarios. Table 71 and Table 72 document these ETE for the 90th and 100th percentiles. The 90th percentile ETE range from 1:15 (hr:min) to 2:50. The 100th percentile ETE for the 2 Mile Region (R01) is 1:45 for all scenarios, which it the trip mobilization time for employees, since R01 consists only of the plant employees. The 100th percentile ETE for the rest of the regions range from 4:50 to 4:55 and are dictated by trip mobilization of the permanent residents (i.e., the time it takes to prepare to evacuate plus the time to travel to the EPZ boundary).

There is minimal congestion in the EPZ throughout the evacuation. The most congestion is observed near the plant, in the town of Wadsworth, and in Bay City. Both SH 60 northbound and SH 35 eastbound experience moderate congestion in Bay City. All congestion within the EPZ clears by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE for Scenario 6 (winter, midweek, midway with good weather conditions). See Section 7.3 and Figures 7 3 through 76.

The comparisons of Table 71 and Table 72 indicate that the 100th percentile ETE are significantly longer than those for the 90th percentile. This is the result of the long trip generation tail of the evacuation curve caused by those evacuees who take longer to mobilize and not congestion within the EPZ. See Sections 7.3 through 7.5, and Figures 7 7 through 718.

Inspection of Table 73 and Table 74 indicate that a staged evacuation provides no benefits to evacuees from within the 2Mile Region (compare Region R01 with Regions R04 trough R10 and R25 through R32, in Table 73) and adversely impacts some evacuees beyond the 2Mile Region (compare Regions R02 and R04 through R05 with Regions R25 through R32, respectively, in Table 71). See Section 7.6 for additional discussion.

Comparison of Scenarios 3 (summer, weekend, midday with good weather) and 11 (summer, weekend, midday with good weather, special event) in Table 71 and Table 72 indicate that the special event, a holiday weekend with beachgoers at Matagorda Beach, increases the 90th percentile ETE by up to 45 minutes for Regions that include PRZ 3 and South Texas Project Electric Generating Station ES5 KLD Engineering, P.C.

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PRZ 7 and has no impact on the 100th percentile ETE. See Section 7.5 for additional discussion.

Comparison of Scenarios 1 and 14 in Table 71 and in Table 72 indicate that the roadway closure - full closure of FM 521 Eastbound (from FM 2668 to SH 60) and Westbound (FM 1468 to CR 392) - has no impact on the 90th percentile ETE or the 100th percentile ETE.

See Section 7.5 for additional discussion.

Separate ETE were computed for schools and transitdependent persons. The average singlewave ETE for schools is 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes less than the 90th percentile ETE for the general population; average singlewave ETE for transit dependent persons is 15 minutes longer than the 90th percentile for the general population. See Section 8.

Table 81 indicates that there are sufficient buses available to evacuate everyone in a single wave. There are also the following transportation resources available, wheelchair vehicles and ambulances, but based on the type of transitdependent resources needed, was not considered in the study. See Section 8.

A reduction in the base trip generation time by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> reduces the general population ETE at the 90th percentile by 5 minutes and the 100th percentile ETE is reduced by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />. An increase in mobilization time by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> increases the 90th percentile ETE by 55 minutes and the 100th percentile ETE by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> - a significant change. See Appendix M and Table M1.

An increase in voluntary evacuation of vehicles in the Shadow Region has minimal impact (at most 15 minutes) on the general population ETE. See Appendix M and Table M2.

An increase in permanent resident population (EPZ plus Shadow Region) of 150% or greater result in an increase in the longest 90th percentile ETE by 30 minutes, which meets the federal criterion for performing a fully updated ETE study between decennial Censuses. See Appendix M and Section M.3.

An increase in the average household size from 2.40 people per household to 2.62 people per household will result in 4% less evacuating vehicles and minimally impacts ETE with a reduction of 5 minutes in the 5Mile Region (R02) and a full EPZ evacuation (Region R03) at the 90th percentile ETE. See Section M.4.

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Table 31. EPZ Permanent Resident Population PRZ 2010 Population 2020 Population 1 0 0 2 49 42 3 356 333 4 74 61 5 102 65 6 707 593 7 624 426 8 0 18 9 224 308 10 823 865 11 173 191 EPZ TOTAL 3,132 2,902 EPZ Population Growth (20102020): 7.34%

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Table 61. Description of Evacuation Regions Radial Regions Protective Response Zone Region Description 13 2 3 4 5 6 7 8 9 10 11 R01 2Mile Region X R02 5Mile Region X X X X X R03 Full EPZ X X X X X X X X X X X Evacuate 2Mile Region and Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R04 34450 X X R05 51106 X X X R06 107140 X X R07 141174 X X X R08 175230 X X R09 231286 X X X R10 287331 X X N/A 332343 Refer to Region R01 Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R11 34450 X X X X R12 5161 X X X X X X R13 6295 X X X X X R14 96106 X X X X X X R15 107129 X X X X X R16 130140 X X X X R17 141163 X X X X X R18 164174 X X X X X X R19 175219 X X X X R20 220230 X X X R21 231286 X X X X X R22 287298 X X X R23 299331 X X X X R24 332343 X X Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R25 5Mile Region X X X X X R26 34450 X X R27 51106 X X X R28 107140 X X R29 141174 X X X R30 175230 X X R31 231286 X X X R32 287331 X X N/A 332343 Refer to Region R01 PRZ(s) ShelterinPlace until 90% ETE for R01, then PRZ(s) Evacuate PRZ(s) ShelterinPlace Evacuate 3

PRZ 1 also includes the South Texas Project Reservoir.

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Table 62. 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 None 8 Winter Weekend Midday Good None 9 Winter Weekend Midday Rain None Midweek, 10 Winter Evening Good None Weekend Special Event:

Holiday weekend 11 Winter Midweek Midday Good with Beachgoers at Matagorda Beach Roadway Impact 12 Summer Midweek Midday Good Road Closure on FM 5215 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 Scenario 12 will consider a roadway closure of FM 521 eastbound (from FM 2668 to SH 60) and westbound (FM 1468 to CR 392).

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R02 1:55 1:55 2:10 2:10 2:15 1:55 1:55 2:10 2:10 2:20 2:45 1:55 R03 2:35 2:35 2:20 2:25 2:30 2:35 2:35 2:20 2:25 2:30 2:45 2:35 2Mile Region and Keyhole to 5 Miles R04 1:25 1:25 1:40 1:45 1:40 1:25 1:25 1:40 1:45 1:40 1:40 1:25 R05 1:30 1:30 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:00 1:30 R06 1:25 1:25 1:45 1:45 1:45 1:25 1:25 1:45 1:45 1:45 1:45 1:25 R07 1:30 1:30 1:45 1:50 1:50 1:30 1:30 1:50 1:50 1:50 1:45 1:30 R08 1:20 1:25 1:30 1:30 1:30 1:20 1:25 1:30 1:30 1:30 1:30 1:20 R09 1:45 1:45 2:00 2:05 2:10 1:45 1:45 2:05 2:05 2:15 2:45 1:45 R10 1:45 1:45 2:00 2:05 2:15 1:45 1:45 2:05 2:05 2:15 2:45 1:45 2Mile Region and Keyhole to EPZ Boundary R11 2:15 2:15 2:15 2:15 2:25 2:15 2:15 2:15 2:15 2:25 2:15 2:15 R12 2:20 2:25 2:15 2:20 2:25 2:20 2:25 2:15 2:20 2:25 2:15 2:20 R13 2:20 2:25 2:15 2:20 2:25 2:20 2:25 2:15 2:20 2:25 2:15 2:20 R14 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:20 2:25 R15 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:20 2:25 R16 2:25 2:25 2:20 2:20 2:30 2:20 2:25 2:20 2:20 2:30 2:20 2:25 R17 2:20 2:25 2:20 2:20 2:30 2:20 2:25 2:20 2:20 2:30 2:20 2:20 R18 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:45 2:25 R19 2:15 2:15 2:15 2:15 2:20 2:15 2:15 2:15 2:15 2:25 2:45 2:15 R20 2:10 2:10 2:15 2:15 2:20 2:05 2:10 2:15 2:15 2:20 2:50 2:10 R21 2:25 2:25 2:20 2:20 2:25 2:25 2:25 2:20 2:25 2:25 2:50 2:25 R22 2:10 2:10 2:10 2:10 2:20 2:10 2:10 2:15 2:15 2:20 2:45 2:10 R23 2:10 2:10 2:10 2:10 2:20 2:10 2:10 2:15 2:15 2:20 2:45 2:10 R24 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 South Texas Project Electric Generating Station ES10 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Staged Evacuation 2Mile Region and Keyhole to 5 Miles R25 1:55 1:55 2:10 2:10 2:15 1:55 1:55 2:10 2:15 2:20 2:45 1:55 R26 1:25 1:25 1:45 1:45 1:45 1:25 1:25 1:45 1:45 1:45 1:45 1:25 R27 1:30 1:30 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:00 1:30 R28 1:30 1:30 1:45 1:45 1:45 1:25 1:30 1:45 1:45 1:45 1:45 1:30 R29 1:30 1:30 1:45 1:50 1:50 1:30 1:30 1:50 1:50 1:50 1:45 1:30 R30 1:25 1:25 1:30 1:30 1:30 1:20 1:25 1:30 1:30 1:30 1:30 1:25 R31 1:45 1:45 2:00 2:05 2:10 1:45 1:45 2:05 2:05 2:15 2:45 1:45 R32 1:45 1:45 2:00 2:05 2:15 1:45 1:50 2:05 2:05 2:15 2:45 1:45 South Texas Project Electric Generating Station ES11 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R02 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R03 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 2Mile Region and Keyhole to 5 Miles R04 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R05 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R06 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R07 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R08 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R09 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R10 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 2Mile Region and Keyhole to EPZ Boundary R11 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R12 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R13 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R14 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R15 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R16 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R17 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R18 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R19 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R20 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R21 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R22 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R23 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R24 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 South Texas Project Electric Generating Station ES12 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Staged Evacuation 2Mile Region and Keyhole to 5 Miles R25 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R26 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R27 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R28 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R29 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R30 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R31 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R32 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 South Texas Project Electric Generating Station ES13 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region and 5Mile Region R01 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R02 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R05 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R06 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R07 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R08 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R09 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R10 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 Staged Evacuation 2Mile Region and Keyhole to 5Miles R25 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R26 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R27 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R28 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R29 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R30 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R31 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R32 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 South Texas Project Electric Generating Station ES14 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region and 5Mile Region R01 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R02 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R05 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R06 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R07 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R08 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R09 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R10 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 Staged Evacuation 2Mile Region and Keyhole to 5Miles R25 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R26 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R27 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R28 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R29 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R30 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R31 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R32 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 South Texas Project Electric Generating Station ES15 KLD Engineering, P.C.

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Table 82. School Evacuation Time Estimates Good Weather Travel Dist. Travel Driver Dist. Time EPZ Time from Mobilization Loading To EPZ Average to EPZ Bdry to EPZ Bdry ETA to Time Time Bdry Speed Bdry ETE H.S. to H.S. H.S.

School (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

Matagorda 60 15 16.7 50.0 20 1:35 3.6 4 1:40 Elementary School Tidehaven Junior and 60 15 6.4 50.0 8 1:25 0.2 1 1:30 High School Maximum for EPZ: 1:35 Maximum: 1:40 Average for EPZ: 1:30 Average: 1:35 Table 85. TransitDependent Evacuation Time Estimates Good Weather Route Travel UNITES Route Travel Pickup Distance Time to ETA to Route PRZ(s) Mobilization Length Speed Time Time ETE to R. C. R. C. R.C.

Route # Serviced (min) (miles) (mph) (min) (min) (hr:min) (miles) (min) (hr:min) 1 3 3, 6, & 7 120 15.9 50.0 19 30 2:50 5.5 7 3:00 2 7 3, 6, & 7 120 17.0 50.0 20 30 2:50 5.5 7 3:00 3 4 10 120 7.0 50.0 8 30 2:40 12.3 15 2:55 Maximum ETE: 2:50 Maximum ETE: 3:00 Average ETE: 2:50 Average ETE: 3:00 Table M3. ETE Variation with Population Change EPZ and 20% Population Change Shadow Permanent Base 148% 149% 150%

Resident Population 8,023 19,897 19,977 20,058 ETE (hrs:min) for the 90th Percentile Population Change Region Base 148% 149% 150%

2MILE 1:15 1:15 1:15 1:15 5MILE 2:45 2:45 2:45 2:45 FULL EPZ 2:45 3:10 3:10 3:15 th ETE for the 100 Percentile Population Change Region Base 148% 149% 150%

2MILE 1:45 1:45 1:45 1:45 5MILE 4:50 4:50 4:50 4:50 FULL EPZ 4:55 4:55 4:55 4:55 South Texas Project Electric Generating Station ES16 KLD Engineering, P.C.

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Figure 61. PRZs Comprising the STP EPZ South Texas Project Electric Generating Station ES17 KLD Engineering, P.C.

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Figure H8. Region R08 South Texas Project Electric Generating Station ES18 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 South Texas Project Electric Generating Station (STP),

located in Matagorda County, Texas. This ETE study provides South Texas Project Nuclear Operating Company (STPNOC) and state and local governments with sitespecific information needed for Protective Action decisionmaking.

In the performance of this effort, guidance is provided by documents published by Federal governmental agencies. Most important of these are:

• Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.

• Revision 1 of the Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR7002, February 2021.

• 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.

The work effort reported herein was supported and guided by STPNOC and the local stakeholders who contributed suggestions, critiques, and the local knowledge base required.

Table 11 presents a summary of stakeholders and interactions.

1.1 Overview of the ETE Process The following outline presents a brief description of the work effort in chronological sequence:

1. Information Gathering:

a. Defined the scope of work in discussions with representatives from STPNOC.

b. Attended a project kickoff meeting with STPNOC, emergency planners from Matagorda County Emergency Management and the Texas Department of State Health Services to discuss methodology, identify issues to be addressed, resources available and project assumptions.

c. Conducted a detailed field survey of the highway system and of the area traffic conditions within the Emergency Planning Zone (EPZ) and Shadow Region.

d. Reviewed STPNOC and existing county and state emergency plans.

e. Obtained demographic data from the 2020 census (see Section 3.1).

f. Conducted an online demographic survey of EPZ residents.

g. Conducted a data collection effort to update the database of schools, special facilities, major employers, transportation providers/resources, and other important information and to identify new facilities.

2. Estimated distributions of trip generation times representing the time required by various population groups (permanent residents, employees, and transients) to prepare South Texas Project Electric Generating Station 11 KLD Engineering, P.C.

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(mobilize) for the evacuation trip. These estimates are primarily based upon the online demographic survey and the Comanche Peak Nuclear Power Plan (CPNPP), in Glen Rose, Texas. A meeting with STPNOC personnel was conducted to discuss the use of the Time Distribution for Population to Prepare to Evacuate from the CPNPP demographic survey.

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.

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 control is applied at specified Traffic and Access Control Points (TACP) located within the study area.

5. Used existing Protective Response Zones (PRZ) to define Evacuation Areas or Regions.

The EPZ is partitioned into 11 PRZ along jurisdictional and geographic boundaries.

Regions are groups of contiguous PRZs 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.

6. Estimated demand for transit services for persons at schools and for transitdependent persons at home.

7. Prepared the input streams for DYNEV II, which computes ETE (see Appendices B and C).

a. Estimated the evacuation traffic demand, based on the available information derived from Census data, and from data provided by county and state agencies, STPNOC, online sources, and from the demographic survey.

b. Updated the linknode representation of the evacuation network, using the field survey and aerial imagery, which is used as the basis for the computer analysis that calculates the ETE.

c. Applied the procedures specified in the 2016 Highway Capacity Manual (HCM1 2016) to the data acquired during the field survey, to estimate the capacity of all highway segments comprising the evacuation routes.

d. Calculated the evacuating traffic demand for each Region and for each Scenario.

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 location of the plant.

1 Highway Capacity Manual (HCM 2016), Transportation Research Board, National Research Council, 2016.

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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.

9. Documented ETE in formats in accordance with NUREG/CR7002, Rev 1.

10. Calculated the ETE for all transit activities including those for schools and for the transit dependent population.

1.2 The South Texas Project Electric Generating Station Location The STP is located in Wadsworth, Matagorda County, Texas, approximately 13 miles south southwest of Bay City, and 75 miles southsouthwest of Houston. A portion of the EPZ is on the Gulf Coast (E/W Matagorda Bay) and Tres Palacios Bay. The area has many lakes, rivers, creeks, and a barrier island that attracts many transients. Figure 11 shows the location of the STP site relative to Houston and Bay City, as well as major population centers and roadways in the area.

1.3 Preliminary Activities These activities are described below.

Field Surveys of the Highway Network In April 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. These characteristics are shown in Table 12.

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.

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:

Minor arterial: 2 or more lanes in each direction Collector: single lane in each direction Local Roadway: single lane in each direction, local road with low free flow speeds South Texas Project Electric Generating Station 13 KLD Engineering, P.C.

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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. 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.

Further discussion of roadway capacity is provided in Section 4 of this report.

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.

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. TACPs at locations which have control devices are represented as actuated signals in the DYNEV II model.

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 model used to compute ETE, as per NUREG/CR7002, Rev. 1 guidance.

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, aerial imagery and construction plans from the TxDOT, were used to calibrate the analysis network.

Demographic Survey An online demographic survey was performed in 2021 to gather information needed for the ETE study. Appendix F presents the survey instrument, the procedures used, and tabulations of data compiled from the survey returns along with discussion validating the use of the survey results in this study.

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.

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 system 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).

DYNEV II consists of four submodels:

A macroscopic traffic simulation model (for details, see Appendix C).

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.

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.

A Myopic Traffic Diversion model which diverts traffic to avoid intense, local congestion, if possible.

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.

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.

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.

For the reader interested in an evaluation of the original model, IDYNEV, the following references are suggested:

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 The evacuation analysis procedures are based upon the need to:

Route traffic along paths of travel that will expedite their travel from their respective points of origin to points outside the EPZ.

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.

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.

1.4 Comparison with Prior ETE Study The 90th percentile ETE for the full EPZ increases by 20 minutes for a winter, midweek, midday, good weather scenario and by 5 minutes for a summer, weekend, midday, good weather scenario when compared with the 2012 study (KLD TR491, dated December 2012). The 100th percentile ETE for the 2Mile Region (R01) has increased by at most 40 minutes for all scenarios, which is dictated by the mobilization of the plant employees. The 100th percentile ETE for an evacuation of the 5Mile Region and Full EPZ (dictated by the trip generation plus 10minute travel time to the EPZ boundary) decreases by at most 45 minutes for the same scenarios.

Table 13. ETE Study Comparisons presents a comparison of the present ETE study with the previous ETE study. The major factors contributing to the differences/similarities between the ETE values obtained in this study and those of the previous study are:

The permanent resident population decreased by approximately 7%. This decrease should result in less evacuating vehicles which can decrease ETE, but the persons per vehicles decreased by 7.6%, which resulted in a very minor increase (0.2%) in the number of permanent resident vehicles, which can increase ETE.

The permanent resident population in the Shadow Region has decreased by 2.5%, but due to the decrease in permanent resident occupancy per vehicle, this results in an increase (4.3%) in the number of Shadow Region permanent resident vehicles. The increase in the number of evacuating vehicles in the Shadow Region, which reduces the available roadway capacity for EPZ evacuees, can increase ETE.

The number of employees commuting into the EPZ significantly decreased by 18.7%,

due to the updated NRCs criteria for major employers from 50 or more employees per shift to 200 or more employees per shift2. A decrease in this quickly mobilizing population group can increase the 90th percentile ETE to increase as it will take longer to reach an evacuation of 90% of all vehicles. A decrease in the number of employee vehicles can decrease the 100th percentile ETEs.

There are decreases in the number of transit dependent population (4.9%) and school children (38.5%) and transients (0.2%) which results in less evacuating vehicles within the EPZ, which can decrease the ETE.

The roadway network was updated based on the current construction of the roundabout at State Highway (SH) 60 and Farm to Market Road (FM) 2668 near Bay City which began in April 2022 and is estimated to be completed late July 2023. The 2

OG corporation even though is slightly less than 200 employees, it was considered for this study.

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signalized intersection at SH 60 and FM 2668 is now a stop control. This study also includes the roadway closure on FM 2668 from SH 60 to Hamman Road, which could increase congestion and increase ETE.

External traffic on SH 35 and FM 616 has increased by 13.1%, which could reduce the capacity for evacuee vehicles within the EPZ, prolonging ETE.

This study considers only one special event. The construction of White Stallion no longer is considered. The beachgoers at Matagorda Beach on a holiday weekend, has decreased by, potentially reducing the ETE for Scenario 11.

Trip mobilization (also known as trip generation), based on the data collected from the demographic survey and the "Time Distribution for Population to Prepare to Evacuate from the CPNPP demographic survey, for the following population groups have changed:

o The employees have increased by 45 minutes while the transients decreased by 15 minutes.

o The permanent residents with commuters decreased by 45 minutes.

o The permanent residents without commuters increased by 15 minutes.

As the mobilization time (plus travel time to the 2Mile Region and EPZ boundary) dictates the ETE, as discussed in Section 7.3, the increases in mobilization can increase ETE, while the decreases in mobilization can decrease the ETE, especially in the 100th percentile.

The various factors, discussed above, that can increase ETE, outweigh those that can decrease ETE, thereby explaining why the 90th percentile ETE have increased while the 100th percentile ETE decreased in this study relative to the previous study.

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Table 11. Stakeholder Interaction Stakeholder Nature of Stakeholder Interaction Attended kickoff meeting to define project methodology and data requirements. Set up contacts with local government agencies. Provided recent plant employee data. Attended meeting to discuss discrepancies with the time distribution for South Texas Project Nuclear Operating Company population to prepare to evacuate. Reviewed and (STPNOC) approved all project assumptions. Engaged in the ETE development and was informed of the study results and coordinated with the OROs. Attended final meeting where the ETE study results were presented.

Attended kickoff meeting to discuss the project methodology, key project assumptions and to define data needs. Provided county emergency plans, special facility data and existing traffic Matagorda County Emergency Management management plans. Reviewed and approved all project assumptions. Engaged in the ETE development and was informed of the study results. Attended final meeting where the ETE study results were presented.

Met to discuss project methodology, key project assumptions and to define data needs. Provided Texas Department of State Health Services state emergency plans. Reviewed and approved all project assumptions. Attended final meeting where the ETE study results were presented.

Provided construction plans and roadway closures Texas Department of Transportation and roadway changes for the construction of the future roundabout at SH 60 and FM 2668.

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)

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 Previous ETE Study Current ETE Study ArcGIS Software using 2010 US Census ArcGIS Software using 2020 US Census Resident blocks; area ratio method used; blocks; area ratio method used.

Population Basis Population = 3,132 Population = 2,902 Vehicles = 1,889 Vehicles = 1,903 Resident 2.38 persons/household, 1.43 2.40 persons/household, 1.56 Population Vehicle evacuating vehicles/household evacuating vehicles/household yielding:

Occupancy yielding: 1.66 persons/vehicle 1.54 persons/vehicle.

Employee estimates based on Employee estimates based on information provided by Matagorda information provided about major County about major employers in the employers in EPZ. 1.09 employees per Employee EPZ. 1.01 employees/vehicle based on vehicle based on demographic survey Population phone survey results. results.

Employees = 1,976 Employees = 1,435 Vehicles = 1,764 Vehicles = 1,475 Estimates based upon 2010 U.S.

Estimates based upon 2020 U.S. Census Census data and the results of the data and the results of the 2020 STP telephone survey. A total of 91 people demographic survey. A total of 13 who do not have access to a vehicle, people who do not have access to a Transit Dependent requiring 3 buses to evacuate. An vehicle, requiring 1 bus to evacuate. No Population additional 5 access and/or functional access and/or functional needs needs persons require special population were provided by the transportation to evacuate (4 buses County. As such, was not considered in and 1 wheelchair van - are required to this study.

evacuate this population).

Transient estimates based upon Transient estimates based upon information provided by Matagorda information provided about transient County, internet searches, and satellite attractions in EPZ, supplemented by imagery, telephone calls to the facilities and supplemented by data from the Transient from aerial photography.

previous ETE study.

Population Transients in EPZ = 555 Transients = 553 Transients in Shadow Region = 350 Seasonal Residents = 350 Total = 905 Total = 903 Total Vehicles = 463 Total Vehicles = 458 School population based on School population based on information information provided by Matagorda from the previous ETE study, confirmed School Population County. to valid by Matagorda County.

School enrollment = 561 School enrollment = 345 Buses Required = 12 Buses Required = 7 South Texas Project Electric Generating Station 19 KLD Engineering, P.C.

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Topic Previous 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.

Shadow Total Population = 26,268 Population = 25,607 Evacuation and Shadow Population Total Vehicles = 15,756 Vehicles = 16,433 20% of people outside of the EPZ 20% of people outside of the EPZ within within the Shadow Region the Shadow Region Voluntary evacuation from 20 percent of the population within 20 percent of the population within the within EPZ in areas the EPZ, but not within the Evacuation EPZ, but not within the Evacuation outside region to Region Region be evacuated Network Size 497 Links; 370 Nodes. 573 Links; 424 Nodes Field surveys conducted in August 2011. Major intersections were video Field surveys conducted in April 2021.

Roadway archived. GIS shapefiles of signal Roads and intersections were video Geometric Data locations and roadway characteristics archived.

created during road survey. Road capacities based on HCM 2016.

Road capacities based on 2010 HCM.

Direct evacuation to designated Host Direct evacuation to designated Host School Evacuation School. School.

50 percent of transitdependent 74.7 percent of transitdependent Ridesharing persons will ride out with a neighbor persons will evacuate with a neighbor or or friend. friend.

Based on residential telephone survey of specific pretrip mobilization activities: Based on residential demographic survey of specific pretrip mobilization Residents with commuters returning activities:

leave between 45 and 330 minutes.

Residents with commuters returning Residents without commuters leave between 60 and 285 minutes.

Trip Generation for returning leave between 15 and 210 minutes. Residents without commuters returning Evacuation leave between 30 and 225 minutes.

Employees leave between 15 and 60 minutes. Employees and transients leave between 15 and 105 minutes.

Transients leave between 15 and 120 minutes. All times measured from the Advisory to Evacuate.

All times measured from the Advisory to Evacuate.

Normal, or Rain. The capacity and Normal, or Rain. The capacity and free free flow speed of all links in the Weather flow speed of all links in the network are network are reduced by 10% in the reduced by 10% in the event of rain.

event of rain.

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Topic Previous ETE Study Current ETE Study Modeling DYNEV II System - Version 4.0.0.0 DYNEV II System - Version 4.0.21.0 Peak Holiday and White Stallion Peak Holiday at Matagorda Beach -

Special Events Construction - 8,500 additional 5,400 additional transients in 2,250 transients in 4,692 vehicles vehicles.

44 Regions (central sector wind 32 Regions (central sector wind direction and each adjacent sector direction and each adjacent sector Evacuation Cases technique used) and 13 Scenarios technique used) and 12 Scenarios producing 572 unique cases producing 384 unique cases.

Evacuation Time ETE reported for 90th and 100th ETE reported for 90th and 100th Estimates percentile population. Results percentile population. Results Reporting presented by Region and Scenario. presented by Region and Scenario.

Winter Weekday, Midday, Winter Weekday, Midday, Evacuation Time Good Weather and Rain: 2:35 Estimates for the Good Weather and Rain: 2:15 entire EPZ, 90th Summer Weekend, Midday, Summer Weekend, Midday, percentile Good Weather: 2:20 Good Weather and Rain = 2:15 Rain: 2:25 Winter Weekday, Midday, Winter Weekday, Midday, Evacuation Time Estimates for the Good Weather and Rain: 5:40 Good Weather and Rain: 4:55 entire EPZ, 100th Summer Weekend, Midday, Summer Weekend, Midday, percentile Good Weather and Rain: 4:55 Good weather and Rain = 5:40 South Texas Project Electric Generating Station 111 KLD Engineering, P.C.

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Figure 11. STP Location South Texas Project Electric Generating Station 112 KLD Engineering, P.C.

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Figure 12. STP LinkNode Analysis Network South Texas Project Electric Generating Station 113 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.

2.1 Data Estimate Assumptions

1. The permanent resident population are based on the 2020 U.S. Census population from the Census Bureau website1 (See Section 3.1). A methodology, referred to as the area ratio method, is employed to estimate the population within portions of census blocks that are divided by Protective Response Zones (PRZ) 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.)

2. Estimates of employees who reside outside the Emergency Planning Zone (EPZ) and commute to work within the EPZ is based on data provided by Matagorda County. The plant employee data was provided by STPNOC (see Section 3.4).

3. Population estimates at transient and schools are based on the data received from Matagorda County, data from the previous ETE study which was reviewed, revised (where applicable) and confirmed accurate by Matagorda County and supplemented by internet searches where data was missing (See Sections 3.3, 3.6, and 3.7).

4. The relationship between permanent resident population and evacuating vehicles is based on Census data and the results of the demographic survey (see Appendix F). The values of 2.40 persons per household and 1.56 evacuating vehicles per household will be used for the permanent resident population. See Section F.3.1 for more information.

5. On average, the relationship between persons and vehicles for transients and special event is as follows:

a. Campgrounds - 1.44 people per vehicle

b. Golf Courses - 1.43 people per vehicle

c. Marinas - 2.38 person per vehicle

d. Parks - 2.20 people per vehicle

e. Lodging Facilities - 2.03 people per vehicle

f. Special Event (Beachgoers at Matagorda Beach) - 2.40 people per vehicle (the average household size; families will travel in one vehicle)

g. Where data was not provided, the average household size was assumed to be the vehicle occupancy rate for transient facilities.

6. Employee vehicle occupancies are based on the results of the demographic survey. 1.09 employees per vehicle. In addition, it is assumed there are two people per carpool, on average (see Figure F6).

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7. The maximum bus speed assumed within the EPZ is 50 mph based on Texas State laws for school buses and average posted speed limits on roadways within the study area.

8. Roadway capacity estimates are based on field surveys performed in 2021 (verified by aerial imagery), roadway construction (provided by Texas Department of Transportation), and the application of the Highway Capacity Manual 2016.

a. In accordance with NUREG/CR7002, Rev. 1, only those roadway construction projects that will be completed prior to the finalization of this report will be considered in this study. Based on discussions with STPNOC and the OROs, a roundabout is proposed at the intersection of State Highway (SH) 60 and Farm to Market Road (FM) 2668 near Bay City which began in April 2022 and is estimated to be completed late July 2023. As such, the proposed roundabout was not included in the base simulations, but any changes to the roadway due to the construction of the roundabout was incorporated. A separate sensitivity study was already performed using the data from the previous study to determine the impacts of the fully constructed roundabout to the ETE. (See STPEGS ETE Sensitivity Study Construction of the Roundabout at SH 60 and FM 2668, KLD TR 1223, dated November 19, 2021.)

2.2 Methodological Assumptions

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):

a. Advisory to Evacuate (ATE) is announced coincident with the Integrated Public Alert and Warning System (IPAWS) notification.

b. Mobilization of the general population will commence within 15 minutes after the IPAWS notification.

c. The ETE are measured relative to the ATE.

2. The centerpoint of the plant is located at 28.794957° N, 96.049014° W.

3. The DYNEV II3 system is used to compute ETE in this study.

4. Evacuees will drive safely, travel radially away from the plant to the extent practicable given the highway network, and obey all control devices and traffic guides. All major evacuation routes are used in the analysis.

5. The existing EPZ and Protective Response Zones (PRZ) boundaries were used. See Figure 31.

2 It is emphasized 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:

1. Establish a temporal framework for estimating the Trip Generation distribution in the format recommended in Section 2.13 of NUREG/CR-6863.

2. Identify temporal points of reference that uniquely define "Clear Time" and ETE.

It is likely that a longer time will elapse between the various stages of an emergency. See Section 5.1 for more detail.

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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6. The Shadow Region extends to 15 miles radially from the plant or approximately 5 miles radially from the EPZ boundary, as per NRC guidance. See Figure 72.

7. One hundred percent (100%) of the people within the impacted keyhole will evacuate.

Twenty percent (20%) of the population within the Shadow Region and within PRZs of the EPZ 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).

8. Shadow population characteristics (household size, evacuating vehicles per household, and mobilization time) was assumed to be the same as that of the permanent resident population within the EPZ.

9. The ETE are presented for the 90th and 100th percentiles, as well as 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.

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. See Section 3.8

11. This study does not assume that roadways are empty at the start of the first time period.

Rather, there is a 30minute initialization period (often referred to as fill time in traffic simulation) wherein the traffic volumes from the first time period 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 first time period depends on the scenario and the region being evacuated. See Section 3.9

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 fact that the evacuating traffic volume (main street) 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.

2.3 Assumptions on Mobilization Times

1. Trip generation time (also known as mobilization time, or the time required by evacuees to prepare for the evacuation) is based upon the results of the demographic survey and the use of the Comanche Peak Nuclear Power Plant (CPNPP) Prepare to Leave Home time distribution, which was discussed and approved by STPNOC. (See Section 5 and Appendix F for detailed discussions.)

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2. It is assumed that stated events take place in sequence such that all preceding events must be completed before the current event can occur.

3. 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.

4. Commuter percentages (and the percentage of residents awaiting the return of a commuter) are based on the results of the demographic survey. According to the survey results, 75.7% of the households in the EPZ have at least 1 commuter (see Section F.3.1.);

approximately 73% of those households with commuters will await the return of a commuter before beginning their evacuation trip (see Figure F.3.2). Therefore, 55%

(75.7% x 73% = 55.3% rounded to 55%) of EPZ households will await the return of a commuter, prior to beginning their evacuation trip.

2.4 Transit Dependent Assumptions

1. The percentage of transitdependent people who will rideshare with a neighbor or friend is based on the results of the demographic survey. According to the survey results, approximately 75% of the transitdependent population will rideshare.

2. Buses are used to transport those without access to private vehicles:

a. Schools

i. If schools are in session, transport (buses) will evacuate students directly to the host schools.

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. Transitdependent permanent residents:

i. Transitdependent permanent resident population is evacuated to reception centers.

ii. No access and/or functional needs population are registered within the EPZ, as per Matagorda County. As such, no access and/or functional needs population was considered in this analysis.

iii. Households with 3 or more vehicles were assumed to have no need for transit vehicles.

c. Analysis of the number of required roundtrips (waves) of evacuating transit vehicles are presented. Sufficient transportation resources exist for transit dependent population, so roundtrips are not considered. (See Section 8.)

d. Transport of transitdependent evacuees from reception centers to congregate care centers is not considered in this study.

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3. Transit vehicle capacities:

a. School buses = 70 students per bus for elementary schools and 50 students per bus for middle/high schools.

b. Transit Dependent buses = 30 persons per bus

4. Transit vehicles mobilization times, which will be considered in ETE calculations:

a. School and transit buses will arrive at schools and facilities to be evacuated within 60 minutes of the ATE.

b. Transit dependent buses are mobilized when approximately 82% of residents with no commuters have completed their mobilization at 120 minutes of the ATE. If necessary, multiple waves of buses will be utilized to gather transit dependent people who mobilize more slowly.

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.

6. Drivers for all transit vehicles, identified in Table 81, are available.

2.5 Traffic and Access Control Assumptions

1. Traffic Access Control Points (TACP) as defined in the approved emergency plans are considered in the ETE analysis, as per NRC guidance. See Appendix G.

2. TACPs are assumed to be staffed approximately 120 minutes after the ATE, as per NRC guidance. It is assumed that no through traffic will enter the EPZ after this 120minute time period.

3. It is assumed that all transit vehicles and other responders entering the EPZ to support the evacuation are unhindered by personnel manning TACPs.

2.6 Scenarios and Regions

1. A total of 12 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 county and state emergency management agencies were polled regarding potential special events in the EPZ. The only potential special event identified by the county and state agencies that attracts transients from outside the EPZ is a holiday with beachgoers at Matagorda Beach, located in the Shadow Region southeast of STP. This event is considered in Scenario 11.

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 will consider the closure of FM 521 Eastbound (from FM 2668 to SH 60) and Westbound (FM 1468 to CR 392) -

Scenario 12.

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2. One type of adverse weather scenarios was considered. Rain may occur for either winter or summer scenarios. It is assumed that the rain begins earlier or at about the same time the evacuation advisory is issued. No weatherrelated reduction in the number of transients who may be present in the EPZ is assumed. It is assumed that roads are passable in rain.

3. Adverse weather affects roadway capacity and free flow roadway speeds. The capacity and free flow speed are reduced by 10% for rain, based on Transportation research. This study assumes a 10% reduction in speed and capacity for rain. The factors are shown in Table 22.

4. The mobilization and loading times for transit vehicles are slightly longer in adverse weather. It is assumed that mobilization times are 10 minutes longer in rain. It is assumed that loading times are 5 minutes longer and 10 minutes longer for school buses and transit buses, respectively in rain conditions. Refer to Table 22.

5. It is assumed that employment is reduced slightly (4% reduction) in the summer for vacations.

6. 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 PRZs 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 PRZs forming a Region that is issued an ATE will, in fact, respond and evacuate in general accord with the planned routes.

7. 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 R25 through R32 in Table 61.

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Table 21. Evacuation Scenario Definitions Time of Scenario Season4 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 7 Winter Midweek Midday Rain None 8 Winter Weekend Midday Good None 9 Winter Weekend Midday Rain None Midweek, 10 Winter Evening Good None Weekend Special Event:

Holiday with 11 Summer Weekend Midday Good Beachgoers at Matagorda Beach Roadway Impact:

12 Summer Midweek Midday Good Road Closure on FM 5215 Table 22. Model Adjustment for Adverse Weather Mobilization Mobilization Time Time for School Loading Time Loading Time Highway Free Flow for General Buses/Transit for School for Transit Scenario Capacity* Speed* Population Vehicles Buses Vehicles 10minute 5minute 10minute Rain 90% 90% No Effect increase increase increase

• 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 Scenario 12 will consider a roadway closure of FM 521 eastbound (from FM 2668 to SH 60) and westbound (FM 1468 to CR 392).

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Figure 21. Voluntary Evacuation Methodology South Texas Project Electric Generating 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 shops within the EPZ could be counted as a resident, again as an employee and once again as a shopper.

A visitor who stays at a hotel and spends time at a park, then goes shopping 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 will tend to overestimate the number of transients and can lead to ETE that are too conservative.

Analysis of the population characteristics of the STP 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.

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 PRZ and by polar coordinate representation (population rose).

The STP EPZ is subdivided into 11 PRZs. The PRZs comprising the EPZ are shown in Figure 31.

Note the central PRZ is the STP site. The 2Mile Region is comprised of the STP site and PRZ 1 which always evacuate together.

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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 (2.40 persons/household was estimated based on the 2020 Census - See Appendix F, SubSection F.3.1). The number of evacuating vehicles per household (1.56 vehicles/household - See Appendix F, SubSection F.3.2) was adapted from the demographic survey results.

The permanent resident population is estimated by cutting the census block polygons by the PRZ 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. This methodology (referred to as the area ratio method) assumes that the population is evenly distributed across a census block. Table 31 provides permanent resident population within the EPZ, by PRZ, for 2010 and for 2020 (based on the methodology above). As indicated, the permanent resident population within the EPZ has decreased by 7.34% since the 2010 Census.

To estimate the number of vehicles, the 2020 Census permanent resident population is divided by the average household size (2.40 persons/household) and multiplied by the average number of evacuating vehicles per household (1.56 vehicles/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 STP. This population 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 STP 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 percent 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 permanent resident shadow population and vehicles, by sector. Note, the 2020 Census indicates there are group quarters population in the Shadow Region. They are residents living in group quarters, such as skilled nursing facilities, group homes, etc. These people are transit dependent (will not evacuate in personal vehicles) and are included in the special facility evacuation demand estimates. Since special facility evacuation in the Shadow Region is not considered in the study, the vehicle estimates for these people have been removed. The resident vehicles in Table 33 and Figure 35 have been adjusted accordingly.

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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 (shopping, recreation).

Transients may spend less than one day or stay overnight at camping facilities, hotels and motels.

Data collected for the previous ETE study was reviewed by Matagorda County and confirmed it was still accurate. A new lodging facility was identified within the EPZ by Matagorda County.

The number of rooms was obtained from the facility website. It assumed that transients stay at the lodging facility as a family/household. As such, the average household size (2.40 persons/household - see Section 3.1) was used to estimate the number of transients for at this new facility. The transient facilities within the STP EPZ are summarized as follows:

Campgrounds - 170 transients and 118 vehicles; an average of 1.44 transients per vehicle Golf Courses - 30 transients and 21 vehicles; an average of 1.43 transients per vehicle Marinas/Boat Ramps - 157 transients and 66 vehicles; an average of 2.38 transients per vehicle Parks - 426 transients and 194 vehicles; an average of 2.20 transients per vehicle Lodging Facilities - 120 transients and 59 vehicles; an average of 2.03 transients per vehicle Transient facilities at Matagorda beach were included even though they exist outside of the EPZ because they will be evacuated in all scenarios, according to Matagorda County Emergency Management personnel. Also, evacuees at Matagorda Beach must travel through the EPZ; thus, they are treated the same as evacuees from within the EPZ. The beach population is highly seasonal and varies by day of week and on holidays. The special event, Scenario 11, with maximum visitors at the beach is not shown in Table 33. Table 34, Figure 36, or Figure 37; only the average daily number of visitors is shown.

Transients in West Matagorda Bay are included in the analysis at their launch point; they are counted at the marina and boat ramps within the EPZ. Transients in West Matagorda Bay who launch from a point outside of the EPZ are not counted, as they are expected to return to their launch site safely outside of the EPZ in the event of an evacuation.

Appendix E summarizes the transient data that was estimated for the EPZ. Table E3 presents the number of transients visiting recreational areas, while Table E4 presents the number of transients at lodging facilities within the EPZ. Table 34 presents transient population and transient vehicle estimates by PRZ. Figure 36 and Figure 37 present these data by sector and distance from the plant.

Even though Matagorda Beach lies outside the EPZ, its population is included within Figure 36 and Figure 37 (in the 10 to EPZ boundary ring) because this population must enter the EPZ while evacuating. Thus, the ETE statistics reflect this population.

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3.4 Employees The estimate of employees commuting into the EPZ is based on the data provided by South Texas Project Nuclear Operating Company and by Matagorda County. The data includes maximum shift employment and percentage of employees living outside of the EPZ.

As per the NUREG/CR7002, Rev. 1 guidance, employers with 200 or more employees working in a single shift are considered as major employers. As such, the employees with less than 200 employees (during the maximum shift) are not considered in this study, except for OQ Corporation. Although OQ Corporation does not meet this criterion, it is included as a major employer for this study considering its relatively large scale of employment for a sparsely population area like the STP EPZ.

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. As discussed above, the percentage of employees living outside of the EPZ is included for each major employer.

To estimate the evacuating employee vehicles, a vehicle occupancy rate of 1.09 employees per vehicle obtained from the demographic survey (see Appendix F, Subsection F.3.1) was used for all the major employers. Appendix E, Table E2 includes the detailed information of each major employer. Table 35 presents nonEPZ Resident employee and vehicle estimates by PRZ. Figure 38 and Figure 39 present these data by sector.

3.5 School Population Demand Table 36 presents the school population and transportation requirements for the direct evacuation of all schools within the EPZ, as confirmed by Matagorda County for the current school year. The column in Table 36 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 and 50 for middle and 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 percent daily.

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Implementation of a process to confirm individual school transportation needs prior to bus dispatch may improve bus utilization. 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, 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.

Table 103 presents a list of the host schools for each school in the EPZ. Students will be transported to these schools where they will be subsequently retrieved by their respective families.

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 transit dependent 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 percent 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 percent of transit dependent persons were evacuated via ride sharing.

Based on the results of the demographic survey, approximately 75 percent of the transitdependent population will rideshare.

The estimated number of bus trips needed to service transitdependent persons is based on an estimated 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 1

Institute for Environmental Studies, University of Toronto, THE MISSISSAUGA EVACUATION FINAL REPORT, June 1981. The report indicates that 6,600 people of a transit-dependent population of 8,600 people shared rides with other residents; a ride share rate of 77% (Page 5-10).

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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 x 10) = 27. On this basis, the average load factor anticipated is (27/40) x 100 = 68 percent. Thus, if the actual demand for service exceeds the estimates of Table 37 by 50 percent, 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 13 people. Therefore, a total of one (1) bus run is 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 PRZs to pick up transit dependent people, 3 buses are used in the ETE calculations, see Section 8.1 for further discussion. 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 STP EPZ:

Where, A = Percent of households with commuters C = Percent of households who will not await the return of a commuter 1,209 0.0036 1.00 0 0.757 0.27 0.179 1.80 1 0.757 0.27 0.485 2.53 2 0.757 0.27 53 1 0.747 30 0.253 53 30 1 These calculations, based on the demographic survey results, are explained as follows:

• 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.

• The number of households (HH) is computed by dividing the EPZ population by the average household size (2,902 2.4) and is 1,209.

• All members (1.00 avg.) of households (HH) with no vehicles (0.36%) will evacuate by public transit or rideshare. The term 1,209 (number of households) x 0.0036 x 1.00, accounts for these people.

• The members of HH with 1 vehicle away (17.9%), who are at home, equal (1.80 1).

The number of HH where the commuter will not return home is equal to (1,209 x 0.179 x 0.8 x 0.757 x 0.27), as 75.7% of EPZ households have a commuter, 27% 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.

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• The members of HH with 2 vehicles that are away (48.5%), who are at home, equal (2.53 - 2). The number of HH where neither commuter will return home is equal to 1,209 x 0.485 x 0.53 x (0.757 x 0.27)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 estimate of transitdependent population in Table 37 exceeds the number of registered transitdependent persons (access and/or functional needs population) in the EPZ. Currently, there are zero access and/or functional needs population registered, as per Matagorda County.

This is consistent with the findings of NUREG/CR6953, Volume 2, in that a large majority of the transitdependent population within the EPZs of U.S. nuclear plants does not register with their local emergency response agency.

3.7 Special Event Matagorda County emergency management agency was polled regarding potential special events in the EPZ. The only potential special event (Scenario 11) identified by Matagorda County (that attracts transients from outside the EPZ) is a holiday with beachgoers at Matagorda Beach which occurs during summer weekends.

Data for the event was provided by Matagorda County. On a holiday, attendance at the beach is approximately 6,000 people, where 90% were considered transients, resulting in an additional 5,400 transients present for the special event. (It should be noted that the remaining 600 people are assumed to be permanent residents within the EPZ and is already counted within the EPZ permanent resident population.) Using an average household size of 2.40, from the Census data (see Section 3.1), the additional 5,400 transients would be evacuating in 2,250 vehicles. This is based on the assumptions that families travel as a household unit in a single car to Matagorda Beach when visiting and they would evacuate as a family.

Vehicles are loaded on local streets near Matagorda Beach for this scenario. The special event vehicle trips were generated utilizing the same mobilization distributions for transients. Public transportation is not provided for this event and was not considered in the special event analysis.

3.8 External Traffic Vehicles will be traveling through the EPZ (externalexternal trips) at the time of an accident.

After the Advisory to Evacuate (ATE) is announced, these throughtravelers will also evacuate.

These through vehicles are assumed to travel on the major routes traversing the study area -

SH 35 and FM 616. It is assumed that this traffic will continue to enter the EPZ during the first 120 minutes following the ATE.

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Average Annual Daily Traffic (AADT) data was obtained from the Texas Department of Transportation (TxDOT) website2 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). 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 resulting values are the directional design hourly volumes (DDHV) and are presented in Table 38 for each of the routes considered. The DDHV is then multiplied by 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> since Traffic and Access Control Points (TACP) are assumed to be activated at 120 minutes after the ATE, to estimate the total number of external vehicles loaded on the analysis network. As indicated, there are 1,416 vehicles entering the EPZ as externalexternal trips prior to the activation of the ACP and the diversion of this traffic. This number is reduced by 60% for evening scenarios (Scenarios 5 and 10) as discussed in Section 6.

3.9 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 58, there are 14 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.

This study does not assume that roadways are empty at the start of Time Period 1. Rather, there is a 30minute initialization time period (often referred to as fill time in traffic simulation) wherein the traffic volumes from Time Period 1 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 Time Period 1 depends on the scenario and the region being evacuated (see Section 6). There are 427 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 6 (winter, midweek, midday, with good weather) conditions.

3.10 Summary of Demand A summary of population and vehicle demand is provided in Table 39 and Table 310, respectively. This summary includes all population groups described in this section. A total of 16,291 people and 10,811 vehicles are considered in this study.

2 https://www.dot.state.tx.us/apps/statewide_mapping/StatewidePlanningMap.html South Texas Project Electric Generating Station 38 KLD Engineering, P.C.

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Table 31. EPZ Permanent Resident Population PRZ 2010 Population 2020 Population 1 0 0 2 49 42 3 356 333 4 74 61 5 102 65 6 707 593 7 624 426 8 0 18 9 224 308 10 823 865 11 173 191 EPZ TOTAL 3,132 2,902 EPZ Population Growth (20102020): 7.34%

Table 32. Permanent Resident Population and Vehicles by PRZ 2020 PRZ 2020 Population Resident Vehicles 1 0 0 2 42 28 3 333 217 4 61 40 5 65 42 6 593 388 7 426 285 8 18 12 9 308 200 10 865 565 11 191 126 EPZ TOTAL 2,902 1,903 South Texas Project Electric Generating Station 39 KLD Engineering, P.C.

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Table 33. Shadow Population and Vehicles by Sector Sector 2020 Population Evacuating Vehicles N 1,196 780 NNE 17,358 11,058 NE 131 84 ENE 34 24 E 3 2 ESE 0 0 SE 0 0 SSE 49 32 S 0 0 SSW 0 0 SW 332 218 WSW 4,615 3,009 W 69 46 WNW 1,105 720 NW 513 337 NNW 202 133 TOTAL 25,607 16,443 Table 34. Summary of Transients and Transient Vehicles PRZ Transients Transient Vehicles 1 0 0 2 6 3 3 71 60 4 0 0 5 0 0 6 74 41 7 397 220 8 0 0 9 5 2 10 0 0 11 0 0 EPZ TOTAL 553 326 Shadow Region 350 132 STUDY AREA TOTAL 903 458 South Texas Project Electric Generating Station 310 KLD Engineering, P.C.

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Table 35. Summary of Employees and Employee Vehicles Commuting into the EPZ PRZ Employees Employee Vehicles 1 1,200 1,101 2 172 158 3 235 216 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0 9 0 0 10 0 0 11 0 0 EPZ TOTAL 1,607 1,475 Table 36. School Population Demand Estimates Buses PRZ School Name Enrollment Required 7 Matagorda Elementary School 135 2 10 Tidehaven Junior and High School 210 5 TOTAL: 345 7 South Texas Project Electric Generating Station 311 KLD Engineering, P.C.

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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 2,902 1.00 1.80 2.53 1,209 0.36% 17.9% 48.5% 75.7% 27.0% 53 74.7% 13 0.4%

Table 38. STP EPZ External Traffic Upstream Downstream Hourly External Node Node Road Name Direction TxDOT AADT3 KFactor4 DFactor4 Volume Traffic 8481 481 SH 35 WB 6,002 0.118 0.5 354 708 8844 1477 SH 35 EB 6,002 0.118 0.25 177 354 8982 982 FM 616 EB 6,002 0.118 0.25 177 354 TOTAL: 1,416 3

TxDOT 2020 Annual Average Daily Traffic (AADT) Statewide Planning Map 4

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Table 39. Summary of Population Demand Transit Special Shadow External PRZ Residents Dependent Transients Employees Schools Event Population5 Traffic Total 1 0 0 0 1,200 0 0 0 0 1,200 2 42 0 6 172 0 0 0 0 220 3 333 2 71 235 0 0 0 0 641 4 61 0 0 0 0 0 0 0 61 5 65 0 0 0 0 0 0 0 65 6 593 3 74 0 0 0 0 0 670 7 426 2 397 0 135 0 0 0 960 8 18 0 0 0 0 0 0 0 18 9 308 1 5 0 0 0 0 0 314 10 865 4 0 0 210 0 0 0 1,079 11 191 1 0 0 0 0 0 0 192 Shadow Region 0 0 350 0 0 5,400 5,121 0 10,871 Total 2,902 13 903 1,607 345 5,400 5,121 0 16,291 5

Shadow population has been reduced to 20%. Refer to Figure 2-1 for additional information.

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Table 310. Summary of Vehicle Demand Transit Special Shadow External PRZ Residents Dependent6 Transients Employees Schools 6 Event Population7 Traffic Total 1 0 0 0 1,101 0 0 0 0 1,101 2 28 0 3 158 0 0 0 0 189 3 217 2 60 216 0 0 0 0 495 4 40 0 0 0 0 0 0 0 40 5 42 0 0 0 0 0 0 0 42 6 388 0 41 0 0 0 0 0 429 7 285 2 220 0 4 0 0 0 511 8 12 0 0 0 0 0 0 0 12 9 200 0 2 0 0 0 0 0 202 10 565 2 0 0 10 0 0 0 577 11 126 0 0 0 0 0 0 0 126 Shadow Region 0 0 132 0 0 2,250 3,289 1,416 7,087 Total 1,903 6 458 1,475 14 2,250 3,289 1,416 10,811 6

Buses for transit-dependent population and schools are represented as two passenger vehicles. Refer to Sections 3.5, 3.6 and 8 for additional information.

7 Shadow population has been reduced to 20%. Refer to Figure 2-1 for additional information.

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Figure 31. PRZs Comprising the STP EPZ South Texas Project Electric Generating Station 315 KLD Engineering, P.C.

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Figure 32. Permanent Resident Population by Sector South Texas Project Electric Generating Station 316 KLD Engineering, P.C.

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Figure 33. Permanent Resident Vehicles by Sector South Texas Project Electric Generating Station 317 KLD Engineering, P.C.

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Figure 34. Shadow Resident Population by Sector South Texas Project Electric Generating Station 318 KLD Engineering, P.C.

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Figure 35. Shadow Vehicles by Sector South Texas Project Electric Generating Station 319 KLD Engineering, P.C.

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Figure 36. Transient Population by Sector South Texas Project Electric Generating Station 320 KLD Engineering, P.C.

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Figure 37. Transient Vehicles by Sector South Texas Project Electric Generating Station 321 KLD Engineering, P.C.

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Figure 38. Employee Population by Sector South Texas Project Electric Generating Station 322 KLD Engineering, P.C.

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Figure 39. Employee Vehicles by Sector South Texas Project Electric Generating Station 323 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.

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.

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.

Thus, in simple terms, a 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.

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.

Other factors also influence capacity. These include, but are not limited to:

Lane width Shoulder width Pavement condition Horizontal and vertical alignment (curvature and grade)

Percent truck traffic Control device (and timing, if it is a signal)

Weather conditions (good, rain, fog, wind speed)

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

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 mph to 75 mph in the study area. Capacity is estimated from the procedures of the HCM 2016. For example, HCM 2016 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).

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.

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 percent. 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 20 percent 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 percent for rain.

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.

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.

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:

3600 3600 where:

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.

m = The movement executed by vehicles after they enter the intersection:

through, leftturn, rightturn, and diagonal.

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.

Formally, we can write, where:

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, South Texas Project Electric Generating 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:

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.

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.

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.

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.

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.

2 Lieberman, E., "Determining Lateral Deployment of Traffic on an Approach to an Intersection", McShane, W. & Lieberman, E.,

"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:

where:

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 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.

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.

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.

Therefore, the application of a factor of 0.90 is appropriate on rural roads, but rarely, if ever, activated.

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.

3 Lei Zhang and David Levinson, Some Properties of Flows at Freeway Bottlenecks, Transportation Research Record 1883, 2004.

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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 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.

4.3 Application to the South Texas Project Nuclear Generating Station 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:

2016 Highway Capacity Manual (HCM 2016)

Transportation Research Board National Research Council Washington, D.C.

The highway system in the study area consists primarily of two categories of roads and, of course, intersections:

TwoLane roads: Local, State Multilane Highways (atgrade)

Each of these classifications will be discussed.

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.

Based on the field survey and on expected traffic operations associated with evacuation scenarios:

Most sections of twolane roads within the study area is classified as Class I, with "level terrain"; some are rolling terrain.

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 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.

4.3.3 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.

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.

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.

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:

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. 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 observation during the road survey; the second is estimated using the concepts of the HCM 2016, as described earlier.

It is important to note that simulation is 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 - many of which will differ from these test cases - and many others cannot be taken into account with the tools available.

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%

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.

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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 South Texas Project Electric Generating Station 49 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 distribution 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. 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.

5.1 Background

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):

1. Unusual Event

2. Alert

3. Site Area Emergency

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:

1. The Advisory to Evacuate (ATE) will be announced coincident with the Integrated Public Alert and Warning System (IPAWS) notification.

2. Mobilization of the general population will commence within 15 minutes after the IPAWS notification.

3. The ETE are measured relative to the ATE.

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:

1. Establish a temporal framework for estimating the Trip Generation distribution in the format recommended in Section 2.13 of NUREG/CR6863.

2. Identify temporal points of reference that uniquely define "Clear Time" and ETE.

It is likely that a longer time will elapse between the various classes of an emergency.

For example, suppose onehour elapses from the IPAWS alert to the ATE. In this case, it is reasonable to expect some degree of spontaneous evacuation by the public during this one hour period. As a result, the population within the EPZ will be lower when the ATE is announced, than at the time of the IPAWS 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 South Texas Project Electric Generating Station 51 KLD Engineering, P.C.

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evacuate the EPZ after the ATE, will both be somewhat less than the estimates presented in this report. 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.

The notification process consists of two events:

1. Transmitting information using the alert and notification systems (ANS) available within the EPZ (IPAWS, Wireless Emergency Alerts (WEAs), Emergency Alert System (EAS) radio and television alerts, national weather service radio, autodial calling).

2. Receiving and correctly interpreting the information that is transmitted.

The population within the EPZ is dispersed over an area of approximately 333 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.

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.

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.

For example, people at home or at work within the EPZ will be notified by IPAWS, 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.

As indicated in Section 4.3 of NUREG/CR7002, Rev. 1, the information required to compute trip generation times is typically obtained from a demographic survey of the EPZ permanent residents. Such a survey was conducted in support of this ETE study. Appendix F presents the survey sampling plan, the number of completed surveys obtained (including statistical confidence bounds), 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 ETE to extend well beyond the trip generation period. The remaining discussion will focus on the application of the trip generation data obtained from the online 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.

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:

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.

These relationships are shown graphically in Figure 51.

An Event is a state that exists at a point in time (e.g., depart work, arrive home)

An Activity is a process that takes place over some elapsed time (e.g., prepare to leave work, travel home)

As such, a completed Activity changes the state of an individual (e.g., 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.

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.

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.

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.

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 South Texas Project Electric Generating Station 53 KLD Engineering, P.C.

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estimates of the time distributions of all preceding events. For this study, we adopt the conservative posture that all activities will occur in sequence.

In some cases, assuming certain events occur strictly sequential (for instance, commuter returning home before beginning 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.

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).

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, the 2019 Federal Emergency Management Agency (FEMA) Radiological Emergency Preparedness Program Manual Part V Section B.1 Bullet 3 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 IPAWS it is assumed that 100 percent of those within the EPZ will be aware of the accident within 45 minutes. The assumed notification distribution for notifying the EPZ population is provided in Table 52 and plotted in Figure 54.

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 for employees working inside or outside of the EPZ who returns home prior to evacuating. 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.

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 STP demographic survey. This distribution is plotted in Figure 52 and listed in Table 55. The data from the Comanche Peak Nuclear Power Plant (CPNPP) is listed in Table 56. (See Section 5.4.2 for further information.)

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.

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 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. Table 58 presents a description of each of the final trip generation distributions achieved after the summing process is completed.

5.4.1 Statistical Outliers As already mentioned, 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 3 say four hours and 4 say six or more hours.

These outliers must be considered: are they valid responses, or so atypical that they should be dropped from the sample?

In assessing outliers, there are three alternatives to consider:

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 access and/or functional needs;

2) Other responses may be unrealistic (6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> to return home from commuting distance, or 2 days to prepare the home for departure);

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.

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.

In establishing the overall mobilization time/trip generation distributions, the following principles are used:

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;

2) The individual mobilization activities (prepare to leave work, travel home, prepare home) are reviewed for outliers, and then the overall trip generation distributions are created (see Figure 51, Table 59, Table 510);

3) Outliers can be eliminated either because the response reflects a special population (e.g.,

access and/or functional needs, transit dependent) or lack of realism, because the purpose is to estimate trip generation patterns for personal vehicles;

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 3.5 standard deviations are flagged for attention, taking special note of whether there are gaps (categories with zero entries) in the histogram display.

In general, only flagged values more than 4 standard deviations from the mean are allowed to be considered outliers, with gaps in the histogram expected.

When flagged values are classified as outliers and dropped, steps a to d are repeated.

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 below in Figure 53.

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:

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; South Texas Project Electric Generating Station 56 KLD Engineering, P.C.

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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.

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;

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.

This is done by using the data sets and distributions under different scenarios (e.g., commuter returning, no commuter returning 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 for each population group considered. 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 - travel home from work follows preparation to leave work, preparation for departure follows the return of the commuter, 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.)

The mobilization distributions results are used in their tabular/graphical form as direct inputs to later computations that lead to the ETE.

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, and D, properly displaced with respect to one another, are tabulated in Table 59 (Distribution B, Arrive Home, omitted for clarity).

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.

5.4.2 Application to the South Texas Project Electric Generating Station Analysis of outliers for the Time Distribution for Population to Prepare to Evacuate (Table 55) yields a distribution with a tail that extends to 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> (360 minutes). When compared with the demographic surveys results used in the previous study and those obtained from recent surveys of EPZ residents at other nuclear sites, it is clear that the distribution for this activity is significantly longer within the STP EPZ. In the last few years, there has been a large increase in tropical storms, severe hurricanes and extreme weather within the study area. As the demographic survey is not specific to what incident is occurring to prepare for, the EPZ residents may have responded to this survey question with these storms in mind.

Consequently, responses to this question are indicative of a level of hurricane preparation that is not relevant to a nonotice nuclear power plant evacuation scenario. To mitigate this situation, the distribution (Table 56) obtained from the demographic survey of Comanche Peak South Texas Project Electric Generating Station 57 KLD Engineering, P.C.

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Nuclear Power Plant (CPNPP) in Glen Rose, Texas was substituted (see Section 5.4.2.1 below for information on how this was determined.) This demographic survey data for CPNPP was collected in 2021 and was discussed with the licensee. The use of the CPNPP distribution was deemed acceptable. This method of using the Time Distribution for Population to Prepare to Evacuate from a different site was also used in the previous study (see KLD TR491, Rev. 1, dated December 2012) to minimize any uncertainty. It should be noted that all other time distributions from the STP demographic survey is used in the trip generation times, as discussed in Section 5.3.

5.4.2.1 Methodology to Determine the use of CPNPP data Tableau (an interactive data visualization tool) was used to identify patterns and similarities between the trip mobilization distributions across the various plant sites within the United States. Each distribution was plotted on the same graph and the various demographic data and EPZ characteristics were toggled on and off until curves could be grouped into categories. Each category contained distributions that followed the same patterns on the graph. An average of the distributions for each site within a given category could then be used for any anomalies that were identified in the 2020 demographic survey results for any site. This analysis could be used to determine the most appropriate replacement or supplemental distribution for that site.

Based on our analysis, we have noted that plants located in specific regions shared similar distributions when it came to the demographic survey. As such, we chose a different plant within the southwest region, CPNPP. Based on the results to the same question, the CPNPP distribution tail extended to 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and 15 minutes (195 minutes). It should be noted that this is the same amount of time used in the previous STP ETE Study, which was also taken from results at a different plant location, Oconee Nuclear Station (ONS). Figure 55 presents a comparison of the Time Distribution for Population to Prepare to Evacuate mobilization distribution drawn from the STP previous study (from ONS), STP current study and the CPNPP demographic survey data.

5.4.3 Staged Evacuation Trip Generation As defined in NUREG/CR7002, Rev. 1, staged evacuation consists of the following:

1. PRZs comprising the 2Mile Region are advised to evacuate immediately

2. PRZs comprising regions extending from 2 to 5 miles downwind are advised to shelter inplace while the 2Mile Region is cleared

3. As vehicles evacuate the 2Mile Region, sheltered people from 2 to 5 miles downwind continue to prepare for evacuation

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

5. Noncompliance with the shelter recommendation is the same as the shadow evacuation percentage of 20%.

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Assumptions

1. The EPZ population in PRZs beyond 5 miles will shelterinplace. A noncompliance voluntary evacuation percentage of 20% is assumed for this population.

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.

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.

4. Employees will also be assumed to evacuate without first sheltering.

Procedure

1. Trip generation for population groups in the 2Mile Region will be as computed based upon the results of the demographic survey and analysis.

2. Trip generation for the population subject to staged evacuation will be formulated as follows:

a. Identify the 90th percentile evacuation time for the PRZ comprising the 2Mile Region. This value, TScen*, is obtained from the simulation results is scenario specific. It will become the time at which the region being sheltered will be told to evacuate for each scenario.

b. The resultant trip generation curves for staging are then formed as follows:

i. The nonshelter trip generation curve is followed until a maximum of 20%

of the total trips are generated (to account for shelter noncompliance).

ii. No additional trips are generated until time TScen*

iii. Following time TScen*, the balance of trips is generated:

1. by stepping up and then following the nonshelter trip generation curve (if TScen* is < max trip generation time) or

2. by stepping up to 100% (if TScen* is > max trip generation time)

c. Note: This procedure implies that there may be different staged trip generation distributions for different scenarios, however that was not the case for this site.

NUREG/CR7002, Rev. 1 uses the statement approximately 90th percentile as the time to end staging and begin evacuating. The value of TScen* is 1:15 for all scenarios (see Regin R01 in Table 71).

3. Staged trip generation distributions are created for the following population groups:

a. Residents with returning commuters

b. Residents without returning commuters Figure 56 and Table 510 present the staged trip generation distributions for both residents with and without returning commuters and employees/transients; the 90th percentile 2Mile South Texas Project Electric Generating Station 59 KLD Engineering, P.C.

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Region evacuation time is about 75 minutes for all scenarios. At TScen*, approximately 1% of the permanent resident population with commuters (who normally would have completed their mobilization activities for an unstaged evacuation) 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.

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.

Table 510 provides the trip generation histograms for staged evacuation.

5.4.4 Trip Generation for Waterways and Recreational Areas Annex W, Tab 5 of the Matagorda County RERP, dated June 1, 2017, Rev. 14, indicates protective actions for the public are broadcast over the National Weather Service and local EAS radio services (KKHAFM). In addition, the Matagorda County Emergency Management Plan, dated August 29, 2019, indicates that the law enforcement agencies of the Matagorda County Sheriffs Department, Bay City Police Department, Palacios Police Department, and the Texas Park and Wildlife Department are responsible for coordinating evacuation movements and establishing traffic access and/or crowd control for roadways, waterways, rail and airspace.

As discussed in Section 2.3, this study assumes a rapidly escalating general emergency. As indicated in Table 52, this study assumes 100% notification in 45 minutes. Table 59 indicates that all transients will have mobilized within 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes. It is assumed that this timeframe is sufficient time for boaters, campers and other transients to return to their vehicles, pack their belongings and begin their evacuation trip.

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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 Table 52. Time Distribution for Notifying the Public Elapsed Time Percent of (Minutes) Population Notified 0 0%

5 7%

10 13%

15 27%

20 47%

25 66%

30 87%

35 92%

40 97%

45 100%

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Table 53. Time Distribution for Employees to Prepare to Leave Work Cumulative Percent Employees Elapsed Time (Minutes) Leaving Work 0 0.0%

5 20.3%

10 39.7%

15 54.8%

20 63.4%

25 66.8%

30 78.8%

35 81.2%

40 85.5%

45 88.0%

50 88.9%

55 89.5%

60 98.2%

65 98.6%

70 99.0%

75 99.4%

80 99.6%

85 99.8%

90 100.0%

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 Percent Elapsed Time (Minutes) Returning Home 0 0.0%

5 9.3%

10 21.3%

15 35.3%

20 53.6%

25 65.9%

30 75.1%

35 82.3%

40 85.0%

45 88.6%

50 93.4%

55 93.7%

60 96.4%

65 96.8%

70 97.2%

75 97.6%

80 98.4%

85 99.2%

90 100.0%

NOTE: The survey data was normalized to distribute the "Decline to State" response South Texas Project Electric Generating Station 513 KLD Engineering, P.C.

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Table 55. Time Distribution for Population to Prepare to Evacuate Cumulative Elapsed Time Cumulative Elapsed Time Percent Ready to (Minutes) Percent Ready to (Minutes) Evacuate Evacuate 0 0% 180 81.5%

15 1.6% 195 87.0%

30 14.6% 210 88.6%

45 23.2% 225 88.6%

60 38.2% 240 90.9%

75 50.4% 255 92.9%

90 56.3% 270 93.7%

105 59.8% 285 93.7%

120 68.1% 300 94.5%

135 77.6% 330 96.5%

150 79.9% 360 100.0%

165 80.3%

NOTE: The survey data was normalized to distribute the "Decline to State" response Table 56. Time Distribution for Population to Prepare to Evacuate - from CPNPP survey Cumulative Percent Ready to Elapsed Time (Minutes) Evacuate 0 0.0%

15 2.5%

30 19.1%

45 36.6%

60 61.1%

75 76.3%

90 80.4%

105 83.6%

120 91.5%

135 96.3%

150 97.2%

165 97.7%

180 98.2%

195 100%

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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 Table 58. Description of the Distributions Distribution Description Time distribution of commuters departing place of work (Event 3). Also applies A to employees who work within the EPZ who live outside, and to Transients within the EPZ.

B Time distribution of commuters arriving home (Event 4).

Time distribution of residents with commuters who return home, leaving home C

to begin the evacuation trip (Event 5).

Time distribution of residents without commuters returning home, leaving home D

to begin the evacuation trip (Event 5).

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Table 59. Trip Generation Histograms for the EPZ Population for Unstaged Evacuation1 Percent of Total Trips Generated Within Indicated Time Period Residents with Residents Without Time Duration Employees Transients Commuters Commuters Period (Min) (Distribution A) (Distribution A) (Distribution C) (Distribution D) 1 15 4% 4% 0% 0%

2 15 24% 24% 0% 2%

3 15 34% 34% 0% 9%

4 15 19% 19% 2% 17%

5 15 10% 10% 5% 20%

6 15 7% 7% 10% 18%

7 15 2% 2% 13% 11%

8 15 0% 0% 15% 5%

9 15 0% 0% 14% 5%

10 30 0% 0% 19% 9%

11 30 0% 0% 12% 2%

12 30 0% 0% 6% 2%

13 30 0% 0% 3% 0%

14 30 0% 0% 1% 0%

15 600 0% 0% 0% 0%

1 Shadow vehicles are loaded onto the analysis network (Appendix K) using Distribution C. Special event vehicles are loaded using Distribution A.

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Table 510. Trip Generation Histograms for the EPZ Population for Staged Evacuation Percent of Total Trips Generated Within Indicated Time Period2 Residents Residents with Without Time Duration Commuters Commuters Period (Min) (Distribution C) (Distribution D) 1 15 0% 0%

2 15 0% 0%

3 15 0% 2%

4 15 0% 4%

5 15 1% 4%

6 15 16% 56%

7 15 13% 11%

8 15 15% 5%

9 15 14% 5%

10 30 19% 9%

11 30 12% 2%

12 30 6% 2%

13 30 3% 0%

14 30 1% 0%

15 600 0% 0%

2 Trip Generation for Employees and Transients (see Table 5 8) is the same for Un-staged and Staged Evacuation South Texas Project Electric Generating Station 517 KLD Engineering, P.C.

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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.

2 Applies throughout the year for transients.

Figure 51. Events and Activities Preceding the Evacuation Trip South Texas Project Electric Generating Station 518 KLD Engineering, P.C.

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Mobilization Activities 100%

Percent of Population Completing Mobilization Activity 80%

60%

Notification Prepare to Leave 40% Work Travel Home Prepare Home 20%

0%

0 30 60 90 120 150 180 210 Elapsed Time from Start of Mobilization Activity (min)

Figure 52. Time Distributions for Evacuation Mobilization Activities South Texas Project Electric Generating Station 519 KLD Engineering, P.C.

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100.0%

90.0%

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)

Cumulative Data Cumulative Normal Figure 53. Comparison of Data Distribution and Normal Distribution South Texas Project Electric Generating Station 520 KLD Engineering, P.C.

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Trip Generation Distributions Employees/Transients Residents with Commuters Residents with no Commuters 100 80 Percent of Population Beginning Evacuation Trip 60 40 20 0

0 60 120 180 240 300 Elapsed Time from Evacuation Advisory (min)

Figure 54. Comparison of Trip Generation Distributions South Texas Project Electric Generating Station 521 KLD Engineering, P.C.

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Comparison of Prepare to Leave Home Distributions STP Current Results from Demographic Survey CPNPP 2020 Demographic Survey Results STP 2012 Results using Oconee Nuclear Station 100%

80%

Percent of Households 60%

40%

20%

0%

0 40 80 120 160 200 240 280 320 360 400 Preparation Time (min)

Figure 55. Comparison of the Time to Prepare Home for Evacuation of STP vs. CPNPP South Texas Project Electric Generating Station 522 KLD Engineering, P.C.

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Staged and Unstaged Evacuation Trip Generation Employees / Transients Residents with Commuters Residents with no Commuters Staged Residents with Commuters Staged Residents with no Commuters 100 80

% of Population Evacuating 60 40 20 0

0 30 60 90 120 150 180 210 240 270 300 Elapsed Time from Evacuation Advisory (min)

Figure 56. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region South Texas Project Electric Generating Station 523 KLD Engineering, P.C.

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6 EVACUATION CASES An evacuation case defines a combination of an Evacuation Region and an Evacuation Scenario.

The definitions of Region and Scenario are as follows:

Region A grouping of contiguous evacuating PRZs that form either a keyhole sector based area, or a circular area within the Emergency Planning Zone (EPZ), that must be evacuated in response to a radiological emergency.

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.

A total of 32 Regions were identified which encompass all the groupings of PRZs considered.

These Regions are defined in Table 61. The PRZ 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, Rev. 1 guidance. The central sector coincides with the wind direction. These sectors extend to 5 miles from the plant (Regions R04 through R10) or to the EPZ boundary (Regions R11 through R24).

Regions R011, R02 and R03 represent evacuations of circular areas with radii of 2, 5 and 10 miles (full EPZ), respectively. Region R25 and Regions R26 through R32 are geographically identical to Region R02 and Regions R04 through R10, respectively; however, those PRZs between 2 miles and 5 miles are staged until 90% of the 2Mile Region (Region R01) has evacuated.

A total of 12 Scenarios were evaluated for all Regions. Thus, there are a total of 32 x 12 = 384 evacuation cases. Table 62 provides is a description of all Scenarios.

Each combination of Region and Scenario implies a specific population to be evacuated. The population and vehicle estimates presented in Section 3 and in Appendix E are peak values. These peak values are adjusted depending on the Scenario and Region being considered, using Scenario and Regionspecific percentages, such that the population is considered for each evacuation case.

The Scenario percentages are presented in Table 63, while the Region percentages are provided in Table H1.

Table 64 presents the vehicle counts for each Scenario for an evacuation of Region R03 - the entire EPZ, based on the Scenario percentages in Table 63. 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 55%, which is the product of 75.7% (the number of households with at least one commuter -

see Figure F6) and approximately 73% (the number of households with a commuter that would await the return of the commuter prior to evacuating - see Figure F11). See assumption 4 in 1

The South Texas Project Reservoir is also included in PRZ 1 as per page 5 of the Offiste Protective Action Recommendation, 0ERP01-ZV-IN07, Rev. 19, effective October 22, 2020.

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Section 2.3. It is estimated for weekend and evening scenarios that 10% of households with returning commuters during the week (55%) will have a commuter at work during those times, or approximately 6% of households overall.

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.

Assume these vacations, in aggregate, are uniformly dispersed over 10 weeks, i.e., 10%

of the population is on vacation during each twoweek interval.

Assume half of these vacationers leave the area.

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.

Employment is assumed to be at its peak (100%) during the winter, midweek, midday scenarios.

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 assumed that only 10% of the employees are working in the evenings and during the weekends.

Transient activity is estimated to be at its peak (100%) during summer weekends and less (85%)

during winter weekends, as there a large percentage of transients who are using beaches, parks and marinas (see Table E2) which can occur during summer or winter months. It was assumed to be less during the weekday (65% during a summer weekday and 50% during a winter weekday). As shown in Table E3 and Table E4, a significant number of transients use campgrounds and lodging facilities the offer overnight accommodation in the EPZ, offset by the other transit facilities in which evening use is minimal; thus, transient activity is estimated to be relatively high during evening hours 45% for winter and 55% for summer.

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 scenariospecific 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:

1,416 20% 1 35%

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One special event - A holiday weekend with beachgoers at Matagorda Beach - was considered as Scenario 11 during the summer, weekend, midday with good weather conditions. Thus, the special event traffic is 100% evacuated for Scenario 11, and 0% for all other scenarios.

As discussed in Section 7, schools are in session during the winter season, midweek, midday and 100% of buses will be needed under those circumstances. 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 to evacuate school children are needed under those circumstances.

Transit buses for the transitdependent population are set to 100% for all scenarios as it is assumed that the transitdependent population is present in the EPZ for all scenarios.

External traffic is estimated to be 100% for all midday scenarios, while it is significantly less (40%)

during the evening scenarios.

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Table 61. Description of Evacuation Regions Radial Regions Protective Response Zone Region Description 12 2 3 4 5 6 7 8 9 10 11 R01 2Mile Region X R02 5Mile Region X X X X X R03 Full EPZ X X X X X X X X X X X Evacuate 2Mile Region and Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 12 2 3 4 5 6 7 8 9 10 11 R04 34450 X X R05 51106 X X X R06 107140 X X R07 141174 X X X R08 175230 X X R09 231286 X X X R10 287331 X X N/A 332343 Refer to Region R01 Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind From Protective Response Zone Region (in Degrees) 12 2 3 4 5 6 7 8 9 10 11 R11 34450 X X X X R12 5161 X X X X X X R13 6295 X X X X X R14 96106 X X X X X X R15 107129 X X X X X R16 130140 X X X X R17 141163 X X X X X R18 164174 X X X X X X R19 175219 X X X X R20 220230 X X X R21 231286 X X X X X R22 287298 X X X R23 299331 X X X X R24 332343 X X Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 12 2 3 4 5 6 7 8 9 10 11 R25 5Mile Region X X X X X R26 34450 X X R27 51106 X X X R28 107140 X X R29 141174 X X X R30 175230 X X R31 231286 X X X R32 287331 X X N/A 332343 Refer to Region R01 PRZ(s) ShelterinPlace until 90% ETE for R01, then PRZ(s) Evacuate PRZ(s) ShelterinPlace Evacuate 2

PRZ 1 also includes the South Texas Project Reservoir.

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Table 62. Evacuation Scenario Definitions Day of Scenario Season3 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 None 8 Winter Weekend Midday Good None 9 Winter Weekend Midday Rain None Midweek, 10 Winter Evening Good None Weekend Special Event:

Holiday weekend 11 Winter Midweek Midday Good with Beachgoers at Matagorda Beach Roadway Impact 12 Summer Midweek Midday Good Road Closure on FM 5214 3

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).

4 Scenario 12 will consider a roadway closure of FM 521 eastbound (from FM 2668 to SH 60) and westbound (FM 1468 to CR 392).

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Table 63. Percent of Population Groups Evacuating for Various Scenarios Households Households With Without External Returning Returning Special School Transit Through Scenario Commuters Commuters Employees Transients Shadow Event Buses Buses Traffic 1 55% 45% 96% 65% 35% 0% 10% 100% 100%

2 55% 45% 96% 65% 35% 0% 10% 100% 100%

3 6% 94% 10% 100% 22% 0% 0% 100% 100%

4 6% 94% 10% 100% 22% 0% 0% 100% 100%

5 6% 94% 10% 55% 22% 0% 0% 100% 40%

6 55% 45% 100% 50% 36% 0% 100% 100% 100%

7 55% 45% 100% 50% 36% 0% 100% 100% 100%

8 6% 94% 10% 85% 22% 0% 0% 100% 100%

9 6% 94% 10% 85% 22% 0% 0% 100% 100%

10 6% 94% 10% 45% 22% 0% 0% 100% 40%

11 6% 94% 10% 100% 22% 100% 0% 100% 100%

12 55% 45% 96% 65% 35% 0% 10% 100% 100%

Resident Households with Commuters ....... Households of EPZ residents who await the return of commuters prior to beginning the evacuation trip.

Resident Households with No 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.

School and Transit Buses............................ Vehicleequivalents present on the road during evacuation servicing schools and transitdependent people (1 bus is equivalent to 2 passenger vehicles).

External Through Traffic............................. Traffic passing through the EPZ on interstates/freeways and major arterial roads at the start of the evacuation. This traffic is stopped by access control approximately 120 minutes after the evacuation begins.

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Table 64. Vehicle Estimates by Scenario5 Households Households With Without External Total Returning Returning Special School Transit Through Scenario Scenario Commuters Commuters Employees Transients6 Shadow Event Buses Buses Traffic Vehicles 1 1,052 851 1,416 298 5,736 0 1 6 1,416 10,776 2 1,052 851 1,416 298 5,736 0 1 6 1,416 10,776 3 105 1,798 148 458 3,544 0 0 6 1,416 7,475 4 105 1,798 148 458 3,544 0 0 6 1,416 7,475 5 105 1,798 148 252 3,544 0 0 6 566 6,419 6 1,052 851 1,475 229 5,838 0 14 6 1,416 10,881 7 1,052 851 1,475 229 5,838 0 14 6 1,416 10,881 8 105 1,798 148 389 3,544 0 0 6 1,416 7,406 9 105 1,798 148 389 3,544 0 0 6 1,416 7,406 10 105 1,798 148 206 3,544 0 0 6 566 6,373 11 105 1,798 148 458 3,544 2,250 0 6 1,416 9,725 12 1,052 851 1,416 298 5,736 0 1 6 1,416 10,776 5

Vehicle estimates are for an evacuation of the entire EPZ (Region R03).

6 Transient vehicles also include those vehicles at Matagorda Beach located within the Shadow Region.

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Figure 61. PRZs Comprising the STP EPZ South Texas Project Electric Generating Station 68 KLD Engineering, P.C.

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7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE)

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 32 Regions within the STP EPZ and the 12 Evacuation Scenarios discussed in Section 6.

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.

The tabulated values of ETE are obtained from the DYNEV II System outputs which are generated at 5minute intervals.

7.1 Voluntary Evacuation and Shadow Evacuation Voluntary evacuees are permanent residents within the EPZ in PRZs 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.

The ETE for the STP EPZ addresses the issue of voluntary evacuees in the manner shown in Figure

71. Within the EPZ, 20 percent of permanent residents located in PRZs outside of the Evacuation Region who are not advised to evacuate, are assumed to elect to evacuate. Similarly, it is assumed that 20 percent of those permanent residents in the Shadow Region will also choose to leave the area.

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 15 miles radially from STP. The population and number of evacuating vehicles in the Shadow Region were estimated using the same methodology that was used for the permanent residents within the EPZ (see Section 3.1).

As discussed in Section 3.2, it is estimated that a total of 25,607 peranent resdients reside in the Shadow Region; 20 percent of them would evacuate. See Table 64 for the number of evacuating vehicles (including employees) from the Shadow Region.

Traffic generated within this Shadow Region, including externalexternal traffic, traveling away from the plant location, has the potential for impeding evacuating vehicles from within the Evacuation Region. All ETE calculations include this shadow traffic movement.

7.2 Staged Evacuation As defined in NUREG/CR7002 Rev.1, staged evacuation consists of the following:

1. PRZs comprising the 2Mile Region are advised to evacuate immediately.

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2. PRZs comprising regions extending from 2 to 5 miles downwind are advised to shelter in place while the 2Mile Region is cleared.

3. As vehicles evacuate the 2Mile Region, people from 2 to 5 miles downwind continue preparation for evacuation while they shelter.

4. The population sheltering in the 2 to 5Mile Region is advised to evacuate when approximately 90 percent of those originally within the 2Mile Region evacuating traffic crosses the 2Mile Region boundary.

5. Noncompliance with the shelter recommendation is the same as the shadow evacuation percentage of 20 percent.

See Section 5.4.3 for additional information on staged evacuation.

7.3 Patterns of Traffic Congestion during Evacuation Figure 73 through Figure 76 illustrate the patterns of traffic congestion (or absences of congestion) that arise for the case when the entire EPZ (Region R03) is advised to evacuate during the winter, midweek, midday period under good weather conditions (Scenario 6).

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):

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:

• Demandtocapacity ratios describe the extent to which demand exceeds capacity during the analysis period (e.g., by 1%, 15%).

• Duration of LOS F describes how long the condition persists (e.g., 15 min, 1 h, 3 h).

• 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.

All highway "links" which experience LOS F are delineated in these figures by a thick red line; all others are lightly indicated. During the entire evacuation, the roadways within the STP study area do not exhibit LOS F conditions. Congestion develops rapidly around concentrations of population and traffic bottlenecks.

Figure 73 displays congestion patterns within the study area at 45 minutes after the ATE. There are some congestion (LOS C and LOS D) that begins to delevop in the EPZ. STP employees are experiencing congestion (LOS D conditions) on Plant Access Road, as they try to leave the plant to access Farm to Market (FM) 521. Congestion (LOS C and LOS D) also exists on SH 60 within the Town of Wadsworth, as many of these vehicles evacuating northbound on SH 60 turn onto FM South Texas Project Electric Generating Station 72 KLD Engineering, P.C.

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521 eastbound to exit the EPZ. As such, FM 521 experiences slight congestion (LOS C) from SH 60 to beyond the Shadow Region. All other roads within the study area are exhibiting no congestion and are operating at LOS A. At this time, approximately 33% of vehicles have mobilized and 21%

of vehicles have successfully evacuated the EPZ.

At 1 hours1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes after the ATE, the 2Mile Region (Region R01) and the 5Mile Region (Region R02) is clear of congestion, as shown in Figure 74. Roadways within Bay City begin to exhibit minor congestion (LOS C). Minor Congestion still exists along SH 60 as vehicles approach the intersection with FM 521. The minor congestion (LOS C) on FM 521 has been reduced and is now operating at a LOS B, east of SH 60. At this time, about 50% of vehicles have mobilized and 39% of vehicles have successfully evacuated the EPZ.

At 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE, Figure 75 shows congestion no longer exists within the entire EPZ (Region R03) and roadways within the EPZ are operating at a LOS A. Therefore, any evacuees who depart after this time encounters no traffic congestion or delays within the EPZ.

Congestion has now intensified within Bay City, located in the Shadow Region. Major congestion (LOS E) is observed along 4th Street as evacuees are trying to locate an alternate route to gain access to SH 35 which is also exhibiting congestion (LOS D) east of Bay City. At this time, about 74% of vehicles have mobilized and 68% of vehicles have successfully evacuated the EPZ.

At 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 35 minutes after the EPZ , approximately 92% of vehicles have mobilized and 90%

of vehicles have successfully evacuated the EPZ. This indicates that the trip generation plus the time to travel to the EPZ boundary (4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> and 55 minutes) is dicating the 100th percentile ETE.

Figure 76 displays the major congestion on 4th Street and SH 35 has dissipated and are now operating at LOS B within Bay City, which clears 25 minutes later at 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> after the ATE.

7.4 Evacuation Rates Evacuation is a continuous process, as implied by Figure 77 through Figure 718. 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.

As indicated in Figure 77 through Figure 712, there is typically a long "tail" to these distributions due to the mobilization and not congestion (low population demand). 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 evacuees (those with the longest mobilization times) travel freely out of the EPZ.

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 South Texas Project Electric Generating Station 73 KLD Engineering, P.C.

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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.

7.5 Evacuation Time Estimate (ETE) Results Table 71 and Table 72 present the ETE values for all 32 Evacuation Regions and all 12 Evacuation Scenarios. Table 73 through Table 74 present the ETE values for the 2Mile Region for both staged and unstaged keyhole regions downwind to 5 miles.

The tables are organized as follows:

Table Contents The ETE represents the elapsed time required for 90 percent of the 71 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.

The ETE represents the elapsed time required for 100 percent of the 72 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.

The ETE represents the elapsed time required for 90 percent of the population within the 2Mile Region, to evacuate from the 2Mile 73 Region with both Concurrent and Staged Evacuations of additional PRZs downwind in the keyhole Region.

The ETE represents the elapsed time required for 100 percent of the population within the 2Mile Region, to evacuate from the 2Mile 74 Region with both Concurrent and Staged Evacuations of additional PRZs downwind in the keyhole Region.

The animation snapshots described in Section 7.3 reflect the ETE statistics for the concurrent (un staged) evacuation scenarios and regions, which are displayed in Figure 73 through Figure 76.

There is no congestion (LOS B or better) within the EPZ, except for some minor congestion within the 2Mile Region on Plant Access Road (which clears at 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes) and outside the 5Mile Region on SH 60 and FM 521 which results in ETE values which parallel the mobilization time. This is reflected in the ETE statistics:

The 2Mile Region (R02) consists of only plant employee vehicles. There is congestion for a limited time during the evacuation as the employees try to access FM 521. Employees mobilize quickly (within 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE), as shown in Figure 54. As such, the 90th percentile ETE for R02, mimics the mobilization of employees and ranges between 1:15 (hr:min) and 1:20 for all scenarios.

The 90th percentile ETE for the 5Mile Region are at most 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 30 minutes longer than R01. The 5Mile Region (R02) includes permanent residents and transients.

Transients mobilize quickly, while the permanent residents with commuters take much longer to mobilze, as shown in Figure 54. As such, the 90th percentile ETE for the 5Mile Region mimics the combination of the quick mobilizing transients and the slow mobilizing South Texas Project Electric Generating Station 74 KLD Engineering, P.C.

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permanent residents with commuters. On the weekends, when there is an increased number of transients at Matagorda Beach there are longer ETEs for Region R02. Even though Matagorda Beach is in the Shadow Region, the only evacuation route available to the transients is SH 60 northbound towards Bay City. These extra vechilces on the main evacuation route increases the congestion during those scenarios. As a result, the 90th percentile ETE for Region R02 ranges between 1:55 and 2:45.

The 90th percentile ETE for the full EPZ (Region R03) are at most 40 minutes longer than R02 due to some congestion on SH 60 and FM 521 and the larger number of permanent residents within the full EPZ (Region R03) that take longer to mobilize. As a result, the 90th percentile ETE for Region R03 range between 2:20 and 2:45.

The 100th percentile ETE for all Evacuation Cases parallel mobilization time, as the minimal congestion within the EPZ dissipates (no speed and capacity reductions exist) after 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE, as displayed in Figure 75. As Region R01, contains only plant employees, the mobilization of employees (1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes) dicates the 100th percentile ETE for all scenarios in Region R01. The 100th percentile ETE, for all other Regions ranges from 4:45 to 4:55 (the mobilization time plus 10 minutes to travel out of the EPZ).

Comparison of Scenarios 3 and 11 in Table 71 and Table 72 indicate that the Special Event -

holiday weekends with beachgoers at Matagorda beach - has no impact to the 90th percentile ETE, except Regions which include PRZ 3 and PRZ 7, which increases the 90th percentile ETE by at most 45 minutes. As discussed in Section 3.7, the influx of traffic is from Matagorda beach through the town of Matagorda northbound on SH 60. These additional 2,250 vehicles considered will delay the departure of evacuees from the town of Matagorda; therefore increasing the 90th percentile ETE only for those Regions that include PRZ 3 and PRZ 7. Due to the excess capacity to service the additional evacuating demand, traffic congestion within the EPZ clears before the trip generation (plus the travel time to the EPZ boundary). As a result, the 100th percentile ETE are not impacted by the special event.

Comparison of Scenarios 1 and 14 in Table 71 and Table 72 indicate that the roadway closure -

FM 521 eastbound from the intersection with FM 2668 to SH 60 and FM 521 westbound from the intersection with FM 1468 to CR 392 - has no impacts on the 90th or 100th percentile ETE. The location of these closures only affect the plant employees and there is excess capacity at alternate evacuations routes to accomodate the plant employees that would be rerouted due to the closure, especially since they mobilize quicker that the remaining population groups within the EPZ. The roadway closure has no impact on the 100th percentile ETE, as the trip generation (plus the travel time to the EPZ boundary) dictates the ETE.

7.6 Staged Evacuation Results Table 73 and Table 74 present a comparison of the ETE compiled for the concurrent (unstaged) and staged evacuation studies. Note that Regions R25 and R26 through R32 are geographically identical to Regions R02, and R04 through R10, respectively. The times shown in Table 73 and Table 74 are when the 2Mile Region is 90 percent clear and 100 percent clear, respectively.

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The objective of a staged evacuation is to show that the ETE for the 2Mile Region can be significantly reduced (30 mintues or 25%, whichever is less) without significantly impacting people beyon the regions between 2 miles and 5 miles. In all cases, as shown Table 73 and Table 74, the 90th percentile ETE for the 2Mile Region remains the same when a staged evacuation is implemented for all Regions and Scenarios.

As discussed in Section 7.3, there is congestion within the 2Mile Region which clears at 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE. In addition, any congestion that exists beyond the 2Mile Region does not extend upstream to the extent that is penetrates within the 2Mile Region. The 100th percentile ETE remains the same, as the trip generation (plus the travel time to the EPZ boundary) dictates the ETE.

To determine the effect of staged evacuation on the permanent residents beyond the 2Mile Region, the ETE for Regions R02, and R04 through R10 are compared to Regions R25, R26 through R32, respectively, in Table 71 and Table 72. A comparison of ETE between these similar regions reveals that staging increases the 90th percentile ETE for those in the 2 to 5mile area by at most 5 minutes (see Table 71) for the 90th percentile ETE and has no impact on the 100th percentile ETE.

The increase in the 90th percentile ETE is due to 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 vehicles get on the road at once, rather than over time. This spike oversaturates evacuation routes, which increases congestion and prolongs ETE.

Therefore, staging evacuation provides no benefit to the evacuees within the 2Mile Region and adversely impacts evacess located beyond the 2Mile Region. Based on the guidance in NUREG 0654, Supplement 3, this analysis would result in staged evacuation not being implemented for this site.

7.7 Guidance on Using ETE Tables The user first determines the percentile of population for which the ETE is sought (The NRC guidance calls for the 90th percentile). The applicable value of ETE within the chosen table may then be identified using the following procedure:

1. Identify the applicable Scenario (Step 1):

• Season Summer Winter (also Autumn and Spring)

• Day of Week Midweek Weekend

• Time of Day Midday Evening South Texas Project Electric Generating Station 76 KLD Engineering, P.C.

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• Weather Condition Good Weather Rain

• Special Event Holiday weekend with beachgoers at Matagorda Beach

• Roadway Impact

• FM 521 eastbound after the intersection with FM 2668 and FM 521 westbound after the intersection with FM 1468

• 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:

• 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.

• The conditions of a winter evening (either midweek or weekend) and rain are not explicitly identified in the Tables. For these conditions, Scenarios (7) and (9) for rain apply.

• The seasons are defined as follows:

Summer assumes public schools are in session at summer school enrollment levels (lower than normal enrollment).

Winter (includes Spring and Autumn) considers that public schools are in session at normal enrollment levels.

• Time of Day: Midday implies the time over which most commuters are at work or are traveling to/from work.

2. With the desired percentile ETE and Scenario identified, now identify the Evacuation Region (Step 2):

• Determine the projected azimuth direction of the plume (coincident with the wind direction). This direction is expressed in terms of azimuth degrees.

• 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:

2 Miles (Region R01)

To 5 Miles (Region R02, R04 through R10)

To EPZ Boundary (Regions R03, R11 through R24)

• Enter Table 75 and identify the applicable group of candidate Regions based on the distance that the selected Region extends from STP. Select the Evacuation Region identifier in that row, based on the azimuth direction of the plume, from the first column of the Table.

South Texas Project Electric Generating Station 77 KLD Engineering, P.C.

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3. Determine the ETE Table based on the percentile selected. Then, for the Scenario identified in Step 1 and the Evacuation Region identified in Step 2, proceed as follows:

• The columns of Table 71 through Table 74 are labeled with the Scenario numbers.

Identify the proper column in the selected Table using the Scenario number determined in Step 1.

• Identify the row in this table that provides ETE values for the Region identified in Step 2.

• The unique data cell defined by the column and row so determined contains the desired value of ETE expressed in Hours:Minutes.

Example It is desired to identify the ETE for the following conditions:

• Sunday, August 10th at 10:00 PM.

• It is raining.

• Wind direction is from the azimuth direction of 225°.

• Wind speed is such that the distance to be evacuated is judged to be a 2Mile Region and downwind to the EPZ boundary.

• The desired ETE is that value needed to evacuate 90 percent of the population from within the impacted Region.

• A staged evacuation is not desired.

Table 71 is applicable because the 90th percentile ETE is desired. Proceed as follows:

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.

2. Enter Table 75 and locate the Region described as Evacuate 2Mile Radius and Downwind to the EPZ Boundary for wind direction from 225° and read Region R20 in the first column of that row.

3. Enter Table 71 to locate the data cell containing the value of ETE for Scenario 4 and Region R20. This data cell is in column (4) and in the row for Region R20; it contains the ETE value of 2:15.

South Texas Project Electric Generating Station 78 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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R02 1:55 1:55 2:10 2:10 2:15 1:55 1:55 2:10 2:10 2:20 2:45 1:55 R03 2:35 2:35 2:20 2:25 2:30 2:35 2:35 2:20 2:25 2:30 2:45 2:35 2Mile Region and Keyhole to 5 Miles R04 1:25 1:25 1:40 1:45 1:40 1:25 1:25 1:40 1:45 1:40 1:40 1:25 R05 1:30 1:30 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:00 1:30 R06 1:25 1:25 1:45 1:45 1:45 1:25 1:25 1:45 1:45 1:45 1:45 1:25 R07 1:30 1:30 1:45 1:50 1:50 1:30 1:30 1:50 1:50 1:50 1:45 1:30 R08 1:20 1:25 1:30 1:30 1:30 1:20 1:25 1:30 1:30 1:30 1:30 1:20 R09 1:45 1:45 2:00 2:05 2:10 1:45 1:45 2:05 2:05 2:15 2:45 1:45 R10 1:45 1:45 2:00 2:05 2:15 1:45 1:45 2:05 2:05 2:15 2:45 1:45 2Mile Region and Keyhole to EPZ Boundary R11 2:15 2:15 2:15 2:15 2:25 2:15 2:15 2:15 2:15 2:25 2:15 2:15 R12 2:20 2:25 2:15 2:20 2:25 2:20 2:25 2:15 2:20 2:25 2:15 2:20 R13 2:20 2:25 2:15 2:20 2:25 2:20 2:25 2:15 2:20 2:25 2:15 2:20 R14 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:20 2:25 R15 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:20 2:25 R16 2:25 2:25 2:20 2:20 2:30 2:20 2:25 2:20 2:20 2:30 2:20 2:25 R17 2:20 2:25 2:20 2:20 2:30 2:20 2:25 2:20 2:20 2:30 2:20 2:20 R18 2:25 2:30 2:20 2:20 2:30 2:25 2:30 2:20 2:20 2:30 2:45 2:25 R19 2:15 2:15 2:15 2:15 2:20 2:15 2:15 2:15 2:15 2:25 2:45 2:15 R20 2:10 2:10 2:15 2:15 2:20 2:05 2:10 2:15 2:15 2:20 2:50 2:10 R21 2:25 2:25 2:20 2:20 2:25 2:25 2:25 2:20 2:25 2:25 2:50 2:25 R22 2:10 2:10 2:10 2:10 2:20 2:10 2:10 2:15 2:15 2:20 2:45 2:10 R23 2:10 2:10 2:10 2:10 2:20 2:10 2:10 2:15 2:15 2:20 2:45 2:10 R24 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 South Texas Project Electric Generating Station 79 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Staged Evacuation 2Mile Region and Keyhole to 5 Miles R25 1:55 1:55 2:10 2:10 2:15 1:55 1:55 2:10 2:15 2:20 2:45 1:55 R26 1:25 1:25 1:45 1:45 1:45 1:25 1:25 1:45 1:45 1:45 1:45 1:25 R27 1:30 1:30 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:00 1:30 R28 1:30 1:30 1:45 1:45 1:45 1:25 1:30 1:45 1:45 1:45 1:45 1:30 R29 1:30 1:30 1:45 1:50 1:50 1:30 1:30 1:50 1:50 1:50 1:45 1:30 R30 1:25 1:25 1:30 1:30 1:30 1:20 1:25 1:30 1:30 1:30 1:30 1:25 R31 1:45 1:45 2:00 2:05 2:10 1:45 1:45 2:05 2:05 2:15 2:45 1:45 R32 1:45 1:45 2:00 2:05 2:15 1:45 1:50 2:05 2:05 2:15 2:45 1:45 South Texas Project Electric Generating Station 710 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region, 5Mile Region, and EPZ R01 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R02 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R03 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 2Mile Region and Keyhole to 5 Miles R04 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R05 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R06 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R07 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R08 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R09 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R10 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 2Mile Region and Keyhole to EPZ Boundary R11 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R12 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R13 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R14 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R15 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R16 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R17 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R18 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R19 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R20 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R21 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R22 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R23 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 R24 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 4:55 South Texas Project Electric Generating Station 711 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Staged Evacuation 2Mile Region and Keyhole to 5 Miles R25 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R26 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R27 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R28 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R29 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R30 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R31 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 R32 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 4:50 South Texas Project Electric Generating Station 712 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region and 5Mile Region R01 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R02 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R05 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R06 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R07 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R08 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R09 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R10 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 Staged Evacuation 2Mile Region and Keyhole to 5Miles R25 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R26 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R27 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R28 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R29 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R30 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R31 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 R32 1:15 1:15 1:15 1:20 1:15 1:15 1:15 1:15 1:20 1:15 1:15 1:15 South Texas Project Electric Generating Station 713 KLD Engineering, P.C.

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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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Good Good Good Good Special Roadway Rain Rain Rain Rain Weather Weather Weather Weather Weather Weather Event Impact Entire 2Mile Region and 5Mile Region R01 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R02 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 Unstaged Evacuation 2Mile Region and Keyhole to 5Miles R04 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R05 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R06 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R07 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R08 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R09 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R10 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 Staged Evacuation 2Mile Region and Keyhole to 5Miles R25 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R26 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R27 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R28 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R29 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R30 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R31 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 R32 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 1:45 South Texas Project Electric Generating Station 714 KLD Engineering, P.C.

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Table 75. Description of Evacuation Regions Radial Regions Protective Response Zone Region Description 11 2 3 4 5 6 7 8 9 10 11 R01 2Mile Region X R02 5Mile Region X X X X X R03 Full EPZ X X X X X X X X X X X Evacuate 2Mile Region and Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R04 34450 X X R05 51106 X X X R06 107140 X X R07 141174 X X X R08 175230 X X R09 231286 X X X R10 287331 X X N/A 332343 Refer to Region R01 Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R11 34450 X X X X R12 5161 X X X X X X R13 6295 X X X X X R14 96106 X X X X X X R15 107129 X X X X X R16 130140 X X X X R17 141163 X X X X X R18 164174 X X X X X X R19 175219 X X X X R20 220230 X X X R21 231286 X X X X X R22 287298 X X X R23 299331 X X X X R24 332343 X X Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R25 5Mile Region X X X X X R26 34450 X X R27 51106 X X X R28 107140 X X R29 141174 X X X R30 175230 X X R31 231286 X X X R32 287331 X X N/A 332343 Refer to Region R01 PRZ(s) ShelterinPlace until 90% ETE for R01, PRZ(s) Evacuate PRZ(s) ShelterinPlace then Evacuate 1

PRZ 1 also includes the South Texas Project Reservoir.

South Texas Project Electric Generating Station 715 KLD Engineering, P.C.

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Figure 71. Voluntary Evacuation Methodology South Texas Project Electric Generating Station 716 KLD Engineering, P.C.

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Figure 72. STP Shadow Region South Texas Project Electric Generating Station 717 KLD Engineering, P.C.

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Figure 73. Congestion Patterns at 45 Minutes after the Advisory to Evacuate South Texas Project Electric Generating Station 718 KLD Engineering, P.C.

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Figure 74. Congestion Patterns at 1 Hours and 5 Minutes after the Advisory to Evacuate South Texas Project Electric Generating Station 719 KLD Engineering, P.C.

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Figure 75. Congestion Patterns at 1 Hour and 45 minutes after the Advisory to Evacuate South Texas Project Electric Generating Station 720 KLD Engineering, P.C.

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Figure 76. Congestion Patterns at 2 Hours and 35 Minutes after the Advisory to Evacuate South Texas Project Electric Generating Station 721 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Midweek, Midday, Good Weather (Scenario 1) 2Mile Region 5Mile Region Entire EPZ 90% 100%

6 5

Vehicles Evacuating 4

3 (Thousands) 2 1

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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 77. 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%

6 5

Vehicles Evacuating 4

3 (Thousands) 2 1

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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 78. Evacuation Time Estimates Scenario 2 for Region R03 South Texas Project Electric Generating Station 722 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Weekend, Midday, Good Weather (Scenario 3) 2Mile Region 5Mile Region Entire EPZ 90% 100%

5 4.5 4

Vehicles Evacuating 3.5 3

2.5 (Thousands) 2 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 79. 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%

5 4.5 4

Vehicles Evacuating 3.5 3

2.5 (Thousands) 2 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 710. Evacuation Time Estimates Scenario 4 for Region R03 South Texas Project Electric Generating Station 723 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5) 2Mile Region 5Mile Region Entire EPZ 90% 100%

3.5 3

Vehicles Evacuating 2.5 2

(Thousands) 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 711. Evacuation Time Estimates Scenario 5 for Region R03 Evacuation Time Estimates Winter, Midweek, Midday, Good Weather (Scenario 6) 2Mile Region 5Mile Region Entire EPZ 90% 100%

6 5

Vehicles Evacuating 4

3 (Thousands) 2 1

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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 712. Evacuation Time Estimates Scenario 6 for Region R03 South Texas Project Electric Generating Station 724 KLD Engineering, P.C.

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Evacuation Time Estimates Winter, Midweek, Midday, Rain (Scenario 7) 2Mile Region 5Mile Region Entire EPZ 90% 100%

6 5

Vehicles Evacuating 4

3 (Thousands) 2 1

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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 713. Evacuation Time Estimates Scenario 7 for Region R03 Evacuation Time Estimates Winter, Weekend, Midday, Good Weather (Scenario 8) 2Mile Region 5Mile Region Entire EPZ 90% 100%

5 4.5 4

Vehicles Evacuating 3.5 3

2.5 (Thousands) 2 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 714. Evacuation Time Estimates Scenario 8 for Region R03 South Texas Project Electric Generating Station 725 KLD Engineering, P.C.

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Evacuation Time Estimates Winter, Weekend, Midday, Rain (Scenario 9) 2Mile Region 5Mile Region Entire EPZ 90% 100%

5 4.5 4

Vehicles Evacuating 3.5 3

2.5 (Thousands) 2 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 715. Evacuation Time Estimates Scenario 9 for Region R03 Evacuation Time Estimates Winter, Midweek, Weekend, Evening, Good Weather (Scenario 10) 2Mile Region 5Mile Region Entire EPZ 90% 100%

3.5 3

Vehicles Evacuating 2.5 2

(Thousands) 1.5 1

0.5 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 716. Evacuation Time Estimates Scenario 10 for Region R03 South Texas Project Electric Generating Station 726 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Weekend, Midday, Good Weather, Special Event (Scenario 11) 2Mile Region 5Mile Region Entire EPZ 90% 100%

8 7

6 Vehicles Evacuating 5 4

(Thousands) 3 2

1 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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 717. Evacuation Time Estimates Scenario 11 for Region R03 Evacuation Time Estimates Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 12) 2Mile Region 5Mile Region Entire EPZ 90% 100%

6 5

Vehicles Evacuating 4

3 (Thousands) 2 1

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 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 718. Evacuation Time Estimates Scenario 12 for Region R03 South Texas Project Electric Generating Station 727 KLD Engineering, P.C.

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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 evacuation time estimates (ETE) for transit vehicles (buses). The demand for transit service reflects the needs of schools only, since there are no medical or correctional facilities in the STP EPZ. In addition, according to Matagorda County, there are no individuals who are registered with access and/or functional needs in the EPZ.

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.

This equivalence factor represents the longer size and more sluggish operating characteristics of a transit vehicle, relative to those of a pc.

Transit vehicles must be mobilized in preparation for their respective evacuation missions.

Specifically:

• Bus drivers must be alerted

• They must travel to the bus depot

• They must be briefed there and assigned to a route or facility These activities consume time. The location of bus depots impacts the time to travel from the bus depots to the facilities being evacuated. Locations of bus depots were not identified in this study. Rather, the offsite agencies were asked to factor the location of the depots and the distance to the EPZ into the estimate of mobilization time. It is estimated that the bus mobilization will average approximately 60 minutes for school buses and 120 minutes after the ATE, when 85% of residents with no commuters have completed their mobilization activities, as discussed in Section 2.

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 STP EPZ indicates that school children will be evacuated to host schools where they can be picked up by their parents. As such, it is assumed no school children will be picked up by their parents prior to the arrival of the buses.

As discussed in Section 2, this study assumes a rapidly escalating accident at the plant wherein evacuation is ordered promptly, and no early protective actions have been implemented.

Therefore, children at the schools are evacuated to host schools. This report provides estimates of buses under the assumption that no students will be picked up by their parents (in accordance with NUREG/CR7002, Rev. 1), to present an upper bound estimate of buses required. Picking up children at school could add to traffic congestion at the schools, 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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The procedure for computing transitdependent ETE is to:

• Estimate demand for transit service (discussed in Section 3)

• Estimate time to perform all transit functions

• Estimate route travel times to the EPZ boundary and to the reception centers and host schools The ETEs for transit trips were developed using both good weather and adverse weather conditions. 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.

8.1 ETEs for Schools and Transit Dependent People The EPZ bus resources are assigned to evacuating schoolchildren (if school is 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 reception centers and host schools after completing their first evacuation trip, to complete a second wave of providing transport service to evacuees.

Transportation resources available were provided by Matagorda County and are summarized in Table 81. Also included in the table are the number of buses needed to evacuate schools and the transitdependent population. These numbers indicate there are sufficient resources available to evacuate everyone in a single wave. Thus, a second evacuation wave was not calculated. Furthermore, if the impacted Evacuation Region is other than R03 (the entire EPZ),

then will be ample amount of transit resources relative to demand in the impacted Region. As discussed in Section 2, it is assumed that there are enough drivers available to man all resources listed in Table 81.

When school evacuation needs are satisfied, subsequent assignments of buses to service the transitdependent 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 at the various routes shown in Table 101.

Evacuation of Schools Activity: Mobilize Drivers (ABC)

Mobilization is the elapsed time from the ATE until the time the buses arrive at the school to be evacuated. It is assumed school bus drivers would require 60 minutes to be contacted, to travel to the depot, be briefed, and to travel to the schools for a rapidly escalating radiological emergency with no observable indication before the fact. Mobilization time is slightly longer (70 minutes) when raining.

Activity: Board Passengers (CD)

As discussed in Section 2.4 and Section 2.6, a loading time of 15 minutes for good weather (20 minutes for rain) for school buses is assumed.

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Activity: Travel to EPZ Boundary (DE)

The buses servicing the schools are ready to begin their evacuation trips at 75 minutes after the advisory to evacuate - 60 minutes mobilization time plus 15 minutes 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 host school. This is done in UNITES by interactively selecting the series of nodes from the school 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 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., 70 to 75 minutes after the ATE for good weather) were used to compute the average speed for each route, as follows:

60 .

1 .

. 60 .

. . 1 .

The average speed computed (using this methodology) for the buses servicing each of the schools in the EPZ is shown in Table 82 and Table 83 for good weather and rain, respectively. To comply with state bus speed regulations, the computed speeds are restricted to 50 mph and 45 mph, for good weather and rain, respectively. 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 host school was computed assuming an average speed of 50 mph and 45 mph for good weather and rain, respectively.

Table 82 (good weather) and Table 83 (rain) present the following ETEs (rounded up to the nearest 5 minutes) for schools in the EPZ:

(1) The elapsed time from the ATE until the bus exits the EPZ; and (2) The elapsed time until the bus reaches the host school.

The evacuation time out of the EPZ can be computed as the sum of times associated with Activities ABC, CD, and DE (For example: 60 minutes + 15 + 20 = 1:35, for Matagorda Elementary School, in good weather, rounded up to the nearest 5 minutes).

The average ETE for schools is 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 5 minutes less than the 90th percentile ETE (1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 30 minutes) for an evacuation of the entire EPZ (Region R03) of the general population during Scenario 6 conditions (2:35 - 1:30 = 1:05) and will not impact protective action decision making.

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The evacuation time to the host school is determined by adding the time associated with Activity EF (discussed below), to this EPZ evacua on me.

Activity: Travel to Host Schools (EF)

The distances from the EPZ boundary to the host schools are measured using GIS software along the most likely route from the EPZ exit point to the facility. The host schools are mapped in Figure 103. For a singlewave evacuation, this travel time outside the EPZ does not contribute to the ETE. Assumed bus speeds of 50 mph and 45 mph for good weather and rain, respectively, will be applied for this activity for buses servicing the schools in the EPZ. Table 82 (good weather) and Table 83 (rain) present the elapsed time until the bus reaches the host school.

Evacuation of TransitDependent Population (Residents without access to a vehicle)

A detailed computation of transit dependent population was done and is discussed in Section 3.5. The total number of transit dependent people per PRZ was determined using a weighted distribution based on population (see Table 311). The number of buses required to evacuate this population was determined by the capacity of 30 people per bus. The PRZs that were determined to have very few transitdependent person were grouped together and a bus route was assigned.

The three (3) bus routes utilized in this study were designed by KLD to service a single or group of PRZ for the purposes of this study to compute the ETE For the transitdependent population.

These bus routes (as discussed in Section 10) are shown graphically in Figure 102 and described in Table 101. Those buses servicing the transitdependent evacuees will first travel along these routes, then proceed out of the EPZ.

The ETEs for the transit trips were developed using both good weather and rain conditions. Table 84 (good weather) and Table 85 (rain) show the ETE breakdown for each step (discussed below) in the transitdependent evacuation process.

Activity: Mobilize Drivers (ABC)

The 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),

approximately 82% of the evacuees will complete their mobilization at approximately 120 minutes after the ATE. As such, mobilization time for the first buses to arrive at each route will be 120 minutes during good weather and 130 minutes in rain, to account for slower travel speeds and reduced roadway capacity in adverse weather.

Activity: Board Passengers (CD)

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 ,

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:

Assigning reasonable estimates:

• B = 50 seconds: a generous value for a single passenger, carrying personal items, to board per stop

• v = 25 miles per hour (mph) = 37 feet/second (ft/sec)

• a = 4 ft/sec/sec, a moderate average rate Then, P 1 minute per stop. Allowing 30 minutes 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 resulting in a loading time of 40 minutes per bus in rain.

Activity: Travel to EPZ Boundary (DE)

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 evacuation.

Table 84 and Table 85 present the transitdependent population evacuation time estimates for each bus route calculated using the above procedures for good weather, rain and snow, respectively.

For example, the ETE for the bus servicing PRZ 10 (Route 3) is computed as 120 + 8 + 30 = 2:40 for good weather (rounded up to nearest 5 minutes). Here, 8 minutes is the time to travel 7.0 miles at 50 mph, the average speed output by the model for this route starting at 120 minutes.

The average single wave ETE for the transit dependent population (2:50) is 15 minutes longer than the 90th percentile ETE for the general population for a winter, midweek, midday, good weather scenario (Scenario 6 2:35). The 15minute difference is minimal and may potentially impact protective action decision making.

Activity: Travel to Reception Centers (EF)

The distances from the EPZ boundary to the reception centers are measured using GIS software along the most likely route from the EPZ exit point to the facility. The reception centers are mapped in Figure 103. For a singlewave evacuation, this travel time outside the EPZ does not contribute to the ETE. Assumed bus speeds of 50 mph and 45 mph for good weather and rain, respectively, will be applied for this activity for buses servicing the transitdependent population.

The relocation of transitdependent evacuees from the reception centers to congregate care centers, if the counties decide to do so, is not considered in this study.

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Table 81. Summary of Transportation Resources Transportation Wheelchair Buses Ambulances Resource Buses Resources Available Bay City Independent School District 14 2 0 Matagorda Independent School District 28 2 0 Palacios Independent School District 28 2 0 Tidehaven Independent School District 28 2 0 Van Vleck Independent School District 2 2 0 Matagorda County EMS 0 0 4 Palacios Community Medical Center 0 0 1 TOTAL: 100 10 5 Resources Needed TransitDependent Population (Table 36): 3 0 0 Schools (Table 37): 7 0 0 TOTAL TRANSPORTATION NEEDS: 10 0 0 Table 82. School Evacuation Time Estimates Good Weather Travel Travel Time Driver Loading Dist. To Average Time to Dist. EPZ from EPZ Mobilization Time EPZ Bdry Speed EPZ Bdry ETE Bdry to Bdry to H.S. ETA to H.S.

School Time (min) (min) (mi) (mph) (min) (hr:min) H.S. (mi.) (min) (hr:min)

Matagorda Elementary School 60 15 16.7 50.0 20 1:35 3.6 4 1:40 Tidehaven Junior and High School 60 15 6.4 50.0 8 1:25 0.2 1 1:30 Maximum for EPZ: 1:35 Maximum: 1:40 Average for EPZ: 1:30 Average: 1:35 South Texas Project Electric Generating Station 86 KLD Engineering, P.C.

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Table 83. School Evacuation Time Estimates - Rain Travel Travel Time Driver Loading Dist. To Average Time to Dist. EPZ from EPZ Mobilization Time EPZ Bdry Speed EPZ Bdry ETE Bdry to Bdry to H.S. ETA to H.S.

School Time (min) (min) (mi) (mph) (min) (hr:min) H.S. (mi.) (min) (hr:min)

Matagorda Elementary School 70 20 16.7 45.0 22 1:55 3.6 5 2:00 Tidehaven Junior and High School 70 20 6.4 45.0 9 1:40 0.2 1 1:45 Maximum for EPZ: 1:55 Maximum: 2:00 Average for EPZ: 1:50 Average: 1:55 Table 84. TransitDependent Evacuation Time Estimates Good Weather Route Travel Route Travel Pickup Distance Time to UNITES PRZ(s) Mobilization Length Speed Time Time ETE to R. C. R. C. ETA to R.C.

Route Route # Serviced (min) (miles) (mph) (min) (min) (hr:min) (miles) (min) (hr:min) 1 3 3, 6, & 7 120 15.9 50.0 19 30 2:50 5.5 7 3:00 2 7 3, 6, & 7 120 17.0 50.0 20 30 2:50 5.5 7 3:00 3 4 10 120 7.0 50.0 8 30 2:40 12.3 15 2:55 Maximum ETE: 2:50 Maximum ETE: 3:00 Average ETE: 2:50 Average ETE: 3:00 Table 85. TransitDependent Evacuation Time Estimates Rain Route Travel Route Travel Pickup Distance Time to UNITES PRZ(s) Mobilization Length Speed Time Time ETE to R. C. R. C. ETA to R.C.

Route Route # Serviced (min) (miles) (mph) (min) (min) (hr:min) (miles) (min) (hr:min) 1 3 3, 6, & 7 130 15.9 45.0 21 40 3:15 5.5 7 3:25 2 7 3, 6, & 7 130 17.0 45.0 23 40 3:15 5.5 7 3:25 3 4 10 130 7.0 45.0 9 40 3:00 12.3 16 3:20 Maximum ETE: 3:15 Maximum ETE: 3:25 Average ETE: 3:10 Average ETE: 3:25 South Texas Project Electric Generating Station 87 KLD Engineering, P.C.

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(Subsequent Wave)

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 Reception Center/Host School E Bus Exits Region F Bus Arrives at Reception Center/Host School G Bus Available for Second Wave Evacuation Service, if Necessary 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 Reception Center/Host School Outside the EPZ FG Passengers Leave Bus; Driver Takes a Break, If Necessary Figure 81. Chronology of Transit Evacuation Operations South Texas Project Electric Generating Station 88 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 the TMP include:

• Personnel with the capabilities of performing the planned control functions of traffic guides (preferably, not necessarily, law enforcement officers).

• 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:

http://mutcd.fhwa.dot.gov which provides access to the official PDF version.

• A written plan that defines all Traffic Control Point (TCP) and Access Control Point (ACP) locations, provides necessary details and is documented in a format that is readily understood by those assigned to perform traffic control.

The functions to be performed in the field are:

1. Facilitate evacuating traffic movements that safely expedite travel out of the EPZ.

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.

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. For example:

• A driver may be traveling home from work or from another location, to join other family members prior to evacuating.

• An evacuating driver may be travelling to pick up a relative, or other evacuees.

• The driver may be an emergency worker entering the area being evacuated to perform an important emergency service.

The implementation of a TMP must also be flexible enough for the application of sound judgment by the traffic guide.

The TMP is the outcome of the following process:

1. The detailed traffic control tactics discussed in Annex W - Tab 3 of the Emergency Management Plan for Matagorda County, Bay City, and Palacios, dated June 1, 2017, serve as the basis of the TMP, as per NUREG/CR7002, Rev. 1. The ETE analysis treated all controlled intersections that are existing ACP or TCP locations in the offsite agency plans as being controlled by actuated signals. Appendix K identifies the number of intersections that were modeled as TCPs.

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2. The ETE analysis treated all controlled intersections that are existing TCP and ACP locations in the offsite agency plans as being controlled by actuated signals. In Appendix K, Table K1 identifies the number of intersections that were modeled as TCPs.

3. Evacuation simulations were run using DYNEV II to predict traffic congestion during evacuation (see Section 7.3 and Figures 73 through 76. These simulations help to identify the best routing and critical intersections that experience pronounced congestion during evacuation. Any critical intersections that would benefit from traffic or access control which are not already identified in the existing offsite agency plans are examined. No additional TCPs or ACPs were identified, which would benefit the ETE, as part of this study.

4. Prioritization of TCPs and ACPs. 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 farther from the power plant. Key locations for manual traffic control (MTC) were analyzed and their impact to ETE was quantified, as per NUREG/CR7002, Rev. 1. See Appendix G for more detail.

Appendix G documents the existing TMP and list of priority TCPs using the process enumerated above.

9.1 Assumptions The following are TMP assumptions made for this study:

The ETE calculations documented in Sections 7 and 8 assume that the TMP is implemented during evacuation.

The ETE calculations reflect the assumptions that all externalexternal trips are interdicted and diverted after 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> have elapsed from the Advisory to Evacuate (ATE).

All transit vehicles and other responders entering the EPZ to support the evacuation are assumed to be unhindered by personnel manning TCPs and ACPs.

Study assumptions 1 through 3 in Section 2.5 discuss TCP and ACP operations.

9.2 Additional Considerations The use of Intelligent Transportation Systems (ITS) technologies can reduce the manpower and equipment needs, while still facilitating the evacuation process. Dynamic Message Signs (DMS) can also be placed within the EPZ to provide information to travelers regarding traffic conditions, route selection, and reception center information. DMS placed outside of the EPZ will 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 vehicles stereo systems. Automated Traveler Information Systems (ATIS) can also be used to provide evacuees with information. Internet websites can South Texas Project Electric Generating Station 92 KLD Engineering, P.C.

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provide traffic and evacuation route information before the evacuee begins their trip, while the onboard navigation systems (GPS units) and smartphones can be used to provide information during the evacuation trip.

These are only several examples of how ITS technologies can benefit the evacuation process.

Considerations should be given that ITS technologies can be used to facilitate the evacuation process, and any additional signage placed should consider evacuation needs.

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10 EVACUATION ROUTES AND RECEPTION CENTERS 10.1 Evacuation Routes Evacuation routes are comprised of two distinct components:

• Routing from a PRZ being evacuated to the boundary of the Evacuation Region and thence out of the EPZ.

• Routing of transitdependent evacuees from the EPZ boundary to host schools/reception centers.

Evacuees will select routes within the EPZ in such a way as to minimize their exposure to risk.

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 to balance traffic demand relative to the available highway capacity to the extent possible. See Appendices B through D for further discussion.

The major evacuation routes, for the EPZ are presented in Figure 101. These routes will be used by the general population evacuating in private vehicles, and by the transitdependent population evacuating in buses. Transitdependent evacuees will be routed to reception centers or host schools. General population may evacuate to a reception center or some alternate destination (i.e., lodging facilities, relatives home, campgrounds) outside the EPZ. It should be noted that there is also a waterway evacuation route for the Colorado River.

The routing of transitdependent evacuees from the EPZ boundary to reception centers/host schools is designed to minimize the amount of travel outside the EPZ, from the points where these routes cross the EPZ boundary. The 3 bus routes shown graphically in Figure 102 and described in Table 101 were designed by KLD, as no preestablished transitdependent bus routes exist within the EPZ or identified within the county emergency plans, in order to compute ETE. The routes were designed to service the major routes through a single or group of PRZ and then proceed to the reception centers assigned in the most recent public information. This does not imply that these exact routes would be used in an emergency. It is assumed that residents will walk to the nearest major roadway and flag down a passing bus, and that they can arrive at the roadway within the 120minute bus mobilization time (good weather). In addition, representative routes were developed for all schools within each PRZ to a host school.

The specified bus routes for all the transitdependent population are documented in Table 102 (refer to maps of the linknode analysis network in Appendix K for node locations). Transit dependent evacuees are transported to the nearest reception center. It is assumed that all school evacuees will be taken to their appropriate host schools. For ETE computations, Tidehaven Junior and High School students will evacuate to Blessing Elementary School. This study does not consider the transport of evacuees from reception centers to congregate care centers if the county makes the decision to relocate evacuees.

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10.2 Reception Centers/Host Schools According to the current public information for EPZ residents, evacuees will be directed to reception centers. Figure 103 maps the general population reception centers for evacuees and host schools for school evacuation.

Table 103 presents a list of the host school for each evacuating school in the EPZ. Children will be transported to these host schools where they will be subsequently retrieved by their respective families. The Matagorda County Emergency Management Plans states that Tidehaven Junior and High School students will either evacuate to Blessing Elementary School or Markham Elementary School. This study assumes that Tidehaven Junior and High School will evacuate to Blessing Elementary School. School evacuees will subsequently be picked up by parents or guardians. No school children will be picked up by parents prior to the arrival of the buses.

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Table 101. Summary of TransitDependent Bus Routes UNITES No. of PRZ(s) Length Route Route # Buses Route Description Serviced (mi.)

PRZ 3: Zipprian Way in Selkirk Island to River Rd to SH 60 northbound through 1 3 1 3, 6, & 7 15.9 Wadsworth, out of EPZ toward Bay City 2 7 1 PRZ 7: SH 60 from Fisher St, Matagorda, north out of the EPZ toward Bay City 3, 6, & 7 17.0 3 4 1 PRZ 10: FM 2853 northbound from Ashby, out of EPZ toward Blessing 10 7.0 Total: 3 Table 102. Bus Route Descriptions Bus Route Number Description Nodes Traversed from Route Start to EPZ Boundary 880, 870, 1465, 860, 1466, 861, 850, 851, 1179, 1350, 1238, 1495, 852, 90, 91, 92, 98, 93, 94, 1 Matagorda Elementary School 100, 1228, 1221, 1355, 221, 1178, 1501, 220 2 Tidehaven Junior & High School 1432, 640, 1474, 1470, 1216, 1217, 650, 651, 652, 1475, 653, 660, 1267, 1396, 1434, 1268 1417, 1416, 1350, 1238, 1495, 852, 90, 91, 92, 98, 93, 94, 100, 1228, 1221, 1355, 221, 1178, 3 TD 1 1501, 220 890, 900, 1498, 901, 902, 850, 851, 1179, 1350, 1238, 1495, 852, 90, 91, 92, 98, 93, 94, 100, 7 TD 2 1228, 1221, 1355, 221, 1178, 1501, 220 1200, 1204, 1201, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 661, 4 TD 3 1269, 1393, 1395, 1482, 1396, 1434 Table 103. Host Schools for School Evacuation School Host School Matagorda Elementary School Linnie Roberts Elementary School Tidehaven Junior and High School Markham Elementary School or Blessing Elementary School1 1

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Figure 101. Evacuation Routes South Texas Project Electric Generating Station 104 KLD Engineering, P.C.

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Figure 102. TransitDependent Bus Routes South Texas Project Electric Generating Station 105 KLD Engineering, P.C.

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Figure 103. Reception Centers and Host Schools South Texas Project Electric Generating Station 106 KLD Engineering, P.C.

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APPENDIX A Glossary of Traffic Engineering Terms

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.

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.

Measures of Effectiveness Statistics describing traffic operations on a roadway network.

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.

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.

Prevailing Roadway and Relates to the physical features of the roadway, the nature (e.g.,

Traffic Conditions composition) of traffic on the roadway and the ambient conditions (weather, visibility, pavement conditions, etc.).

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.

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).

Service Volume is usually expressed as vph.

Signal Cycle Length The total elapsed time to display all signal indications, in sequence.

The cycle length is expressed in seconds.

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.

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.

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).

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.

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.

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.

Travel Mode Distinguishes between private auto, bus, rail, pedestrian and air travel modes.

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.

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

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.

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.

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.

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.

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.

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 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 (OD 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] movements. DTRAD computations are performed on the path network: DYNEV simulation model, on the geometric network.

B.2.1 DTRAD Description DTRAD is the DTA module for the DYNEV II System.

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.

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:

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.

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.

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 South Texas Project Electric Generating Station B2 KLD Engineering, P.C.

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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.

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 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.

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.

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:

sa = ln (p), 0 p l ; 0 p=

dn = Distance of node, n, from the plant d0 = Distance from the plant where there is zero risk

= Scaling factor The value of do = 11.6 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:

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.

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.,

commuters). Effectively, such drivers learn which routes are best for them over time. Thus, the traffic environment settles down to a nearequilibrium state.

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

Set T0 Clock time.

Archive System State at T0 Define latest Link Turn Percentages Execute Simulation Model from B time, T0 to T1 (burn time)

Provide DTRAD with link MOE at time, T1 Execute DTRAD iteration; Get new Turn Percentages Retrieve System State at T0 ;

Apply new Link Turn Percents DTRAD iteration converges?

No Yes Next iteration Simulate from T0 to T2 (DTA session duration)

Set Clock to T2 B A Figure B1. Flow Diagram of SimulationDTRAD Interface South Texas Project Electric Generating Station B5 KLD Engineering, P.C.

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APPENDIX C DYNEV Traffic Simulation Model

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.

Model Features Include:

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.

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.

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.

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.

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.

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.

A twoway interface with DTRAD: (1) provides link travel times; (2) receives data that translates into link turn percentages.

Provides MOE to animation software, EVacuation Animator (EVAN).

Calculates Evacuation Time Estimates (ETE) statistics.

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).

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.

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.

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

. 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.

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.

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

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.

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.

Set iteration counter, n = 0, k k , and E E .

2. Calculate v k such that k 130 using the analytical representations of the fundamental diagram.

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

Calculate queue length, L Q LN

3. Calculate t TI . If t 0 , set t E O 0 ; Else, E E .

4. Then E E E ; t TI t

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

6. Else Q Cap O Q , RCap Cap O

7. If M RCap , then t Cap

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 South Texas Project Electric Generating 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

9. Else M O 0 If t 0 , then O RCap , Q M O E Calculate Q and M using Algorithm A

10. Else t 0 M M If M ,

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

11. Calculate a new estimate of average density, k k 2k k ,

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.

If k k and n N where N max number of iterations, and is a convergence criterion, then

12. set n n 1 , and return to step 2 to perform iteration, n, using k k .

End if Computation of unit problem is now complete. Check for excessive inflow causing spillback.

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13. If Q M , then The number of excess vehicles that cause spillback is: SB Q M ,

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 .

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.

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 Q

Qe length, Q , formed by that portion of M and E that reaches the stopbar within the TI, but could not v discharge due to inadequate capacity. That is, Q Mb M E . This queue length, Q Q v L3 M E Cap can be extended to Q by traffic entering the approach during the current TI, traveling t1 t3 at speed, v, and reaching the rear of the queue within T the TI. A portion of the entering 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 .

When t 0 and Q Cap:

L L Define: L Q . From the sketch, L v TI t t L Q E .

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:

L t such that 0 t TI t E L v

TI LN If the denominator, v 0, set t TI t .

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.

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.

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.

Within each sweep, processing solves the unit problem for each turn movement on each link.

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.

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.

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.

Note that there is no spacediscretization other than the specification of network links.

C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD)

The DYNEV II system reflects 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.

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.

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.

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)

Mean Travel Time Minutes Evacuation Trips; Network South Texas Project Electric Generating 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)

Destination (exit) nodes Network topology defined in terms of downstream nodes for each receiving link Node Coordinates (X,Y)

Nuclear Power Plant Coordinates (X,Y)

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)

Stop and Yield signs Rightturnonred (RTOR)

Route diversion specifications Turn restrictions Lane control (e.g., lane closure, movementspecific)

DRIVERS AND OPERATIONAL CHARACTERISTICS Drivers (vehiclespecific) response mechanisms: freeflow speed, discharge headway Bus route designation.

DYNAMIC TRAFFIC ASSIGNMENT Candidate destination nodes for each origin (optional)

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 South Texas Project Electric Generating 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.

The number of vehicles, of a particular movement, that enter the link over the E

time interval. The portion, ETI, can reach the stopbar within the TI.

The green time: cycle time ratio that services the vehicles of a particular turn G/C movement on a link.

h The mean queue discharge headway, seconds.

k Density in vehicles per lane per mile.

The average density of moving vehicles of a particular movement over a TI, on a k

link.

L The length of the link in feet.

The queue length in feet of a particular movement, at the [beginning, end] of a L ,L time interval.

The number of lanes, expressed as a floating point number, allocated to service a LN particular movement on a link.

L The mean effective length of a queued vehicle including the vehicle spacing, feet.

M Metering factor (Multiplier): 1.

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.

The total number of vehicles of a particular movement that are discharged from a O

link over a time interval.

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.

The percentage, expressed as a fraction, of the total flow on the link that P

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

[beginning, end] of the time interval.

The maximum flow rate that can be serviced by a link for a particular movement in the absence of a control device. It is specified by the analyst as an estimate of Q

link capacity, based upon a field survey, with reference to the Highway Capacity Manual (HCM) 2016.

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 .

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.

S Service rate for movement x, vehicles per hour (vph).

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.

TI The time interval, in seconds, which is used as the simulation time step.

v The mean speed of travel, in feet per second (fps) or miles per hour (mph), of moving vehicles on the link.

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.

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 South Texas Project Electric Generating 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

v L

Mb Me Up t1 t2 Time E1 E2 TI Figure C3. A UNIT Problem Configuration with t1 > 0 South Texas Project Electric Generating Station C13 KLD Engineering, P.C.

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Sequence Network Links Next Timestep, of duration, TI A

Next sweep; Define E, M, S for all B

Links C Next Link D Next Turn Movement, x Get lanes, LNx Service Rate, Sx ; G/Cx Get inputs to Unit Problem:

Q b , Mb , E Solve Unit Problem: Q e , Me , O No D Last Movement ?

Yes No Last Link ? C Yes No B Last Sweep ?

Yes Calc., store all Link MOE Set up next TI :

No A Last Time - step ?

Yes DONE Figure C4. Flow of Simulation Processing (See Glossary: Table C3)

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APPENDIX D Detailed Description of Study Procedure

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.

Step 1 The first activity was to obtain 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.

The base map incorporates the local roadway topology, a suitable topographic background and the EPZ boundary.

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. Employee data was estimated based on data provided by Matagorda County and South Texas Plant Nuclear Operating Company (plant employment data). Data for schools and transient facilities were obtained from Matagorda County and the previous ETE study (reviewed and confirmed still accurate), supplemented by internet searches where data was missing. In addition, transportation resources available during an emergency were also provided by Matagorda County.

Step 3 A kickoff meeting was conducted with major stakeholders (state and local emergency officials, and onsite and offsite STPNOC personnel). 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 officials and STPNOC utility managers. Unique features of the study area were discussed to identify the local concerns that should be addressed by the ETE study.

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 factors including the average number of evacuating vehicles used by each household, and the time required to perform preevacuation mobilization activities.

Step 6 A computerized representation of the physical roadway system, called a linknode analysis network, was updated 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.

Step 7 The EPZ is subdivided into 11 Protective Response Zones (PRZ). Based on wind direction and speed, Regions (groupings of PRZ) that may be advised to evacuate, were developed.

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.

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.

Step 9 After creating this input stream, the DYNEV II model 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.

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) produced by DYNEV II and reviewing the statistics output by the model. This is a labor intensive 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.

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:

The results are satisfactory; or The input stream must be modified accordingly.

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.

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, adding routes (which are paved and traversable) that were not previously modelled but may assist in an 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.

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.

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 model 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 and school buses are introduced into the final prototype evacuation case data set. DYNEV II generates routespecific speeds over time for use in the estimation of evacuation times for the transit dependent and special facility population groups.

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.

Step 15 All evacuation cases were executed using the DYNEV II model to compute ETE. Once results were available, quality control procedures were used to assure the results were consistent, dynamic routing was reasonable, and traffic congestion/bottlenecks were addressed properly.

Traffic management plans are analyzed, and traffic control points are prioritized, if applicable.

Additional analysis is conducted to identify the sensitivity of the ETE to changes in some base evacuation conditions and model assumptions.

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, hospitals, and other special facilities.

Step 17 The simulation results are analyzed, tabulated, and graphed. The results are then documented, as required by NUREG/CR7002, Rev. 1.

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 1 Step 10 Create GIS Base Map Examine Prototype Evacuation Case using EVAN and DYNEV II Output Step 2 Gather Census Block and Demographic Data for Study Results Satisfactory Area.

Step 11 Step 3 Modify Evacuation Destinations and/or Develop Traffic Conduct Kickoff Meeting with Stakeholders Control Treatments Step 4 Step 12 Field Survey of Roadways within Study Area Modify Database to Reflect Changes to Prototype Evacuation Case Step 5 Conduct Demographic Survey and Develop Trip Generation Characteristics B

Step 13 Step 6 Establish Transit and Special Facility Evacuation Routes Update LinkNode Analysis Network and Update DYNEV II Database Step 14 Step 7 Generate DYNEV II Input Streams for All Evacuation Cases Develop Evacuation Regions and Scenarios Step 15 Step 8 Use DYNEVII to Simulate All Evacuation Cases and Create and Debug DYNEV II Input Stream Compute ETE Step 16 Step 9 Use DYNEV II Average Speed Output to Compute ETE for Transit and Special Facility Routes B Execute DYNEV II for Prototype Evacuation Case Step 17 Documentation A Step 18 Complete ETE Criteria Checklist Figure D1. Flow Diagram of Activities South Texas Project Electric Generating Station D5 KLD Engineering, P.C.

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APPENDIX E Facility Data

E. FACILITY DATA The following tables list population information, as of May 2022, for facilities that are located within the STP EPZ. Special facilities are defined as schools. Transient population data is included in the tables for recreational areas (campgrounds, golf courses, marinas, and parks) and lodging facilities. Employment data is included in the table for major employers. 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, major employer, recreational area (campground, golf course, marina and park), and lodging facility are also provided.

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Table E1. Schools within the EPZ Distance Dire Enroll PRZ (miles) ction School Name Street Address Municipality ment MATAGORDA COUNTY 7 8.4 SE Matagorda Elementary School 717 Wightman St Matagorda 135 10 8.3 NW Tidehaven Junior and High School 2469 FM 459 El Maton 210 Matagorda County Subtotal: 345 EPZ TOTAL: 345 Table E2. Major Employers within the EPZ

% Employee Employees Employees Vehicles Distance Dire Employees Commuting Commuting Commuting PRZ (miles) ction Facility Name Street Address Municipality (Max Shift) into the EPZ into the EPZ into the EPZ MATAGORDA COUNTY South Texas Project 1 Electric Generating Station 8330 FM 521 Bay City 1,263 95.0% 1,200 1,101 2 5.1 NNE OQ Corporation 2001 FM 3057 Bay City 175 98.0% 172 158 3 6.7 E Lyondell Chemicals 17042 TX60 S Bay City 237 99.0% 235 216 Matagorda County Subtotal: 1,675 1,607 1,475 EPZ TOTAL: 1,675 1,607 1,475 South Texas Project Electric Generating Station E2 KLD Engineering, P.C.

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Table E3. Recreational Areas within the EPZ Distance Dire PRZ (miles) ction Facility Name Street Address Municipality Facility Type Transients Vehicles MATAGORDA COUNTY 2 4.6 NNE BayCel Golf Course 2011 FM 3057 Bay City Golf Course 6 3 3 3.2 E FM 521 River Park 14690 FM 521 Bay City Park 71 60 6 8.9 NNE Riverside Campgrounds 7330 FM 2668 Bay City Campground 50 23 6 9.2 NNE Rio Colorado Golf Course 7320 FM2668 Bay City Golf Course 24 18 7 6.9 ESE Lighthouse RV Park 18411 Hwy 60 Bay City Campground 90 75 7 8.4 SE Seabird RV Park 426 Cypress St Matagorda Campground 30 20 7 8.8 SE Matagorda Harbor 189 County Rd 213 Matagorda Marina 157 66 9 6.2 W Carl Park 3372 FM 521 Palacios Park 5 2 S.R.1 14.1 SSE Matagorda Bay Nature Park & Campgrounds End of FM 4420 Matagorda Park 350 132 S.R.1 14.2 SSE Matagorda Beach and Jetty Park End of FM 4423 Matagorda Park Matagorda County Subtotal: 783 399 EPZ TOTAL: 783 399 Table E4. Lodging Facilities within the EPZ Distance Dire PRZ (miles) ction Facility Name Street Address Municipality Transients Vehicles MATAGORDA COUNTY 7 8.6 SE Westwood Inn Matagorda 23082 TX60 Matagorda 50 21 7 8.7 SE Fisherman's Motel 40 Fisher St Matagorda 18 12 7 8.8 SE Shell Motel 1 778 Market St Matagorda 52 26 Matagorda County Subtotal: 120 59 EPZ TOTAL: 120 59 1

These facilities are in the S.R. (Shadow Region) but would evacuate according to the county emergency plans.

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Figure E1. Schools within the EPZ South Texas Project Electric Generating Station E4 KLD Engineering, P.C.

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Figure E2. Major Employers within the EPZ South Texas Project Electric Generating Station E5 KLD Engineering, P.C.

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Figure E3. Recreational Areas within the EPZ South Texas Project Electric Generating Station E6 KLD Engineering, P.C.

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Figure E4. Lodging Facilities within the EPZ South Texas Project Electric Generating Station E7 KLD Engineering, P.C.

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APPENDIX F Demographic Survey

F. DEMOGRAPHIC SURVEY F.1 Introduction The development of evacuation time estimates for the STP EPZ requires the identification of travel patterns, car ownership and household size of the population within the EPZ.

Demographic information can be obtained from Census data. 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.

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 ?).

F.2 Survey Instrument and Sampling Plan Attachment A presents the final survey instrument used for the demographic survey. 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.

Following the completion of the instrument, a sampling plan was developed. Since the demographic survey discussed herein was performed prior to the release of the 2020 Census data, 2010 Census data, extrapolated to 2020, was used to develop the sampling plan.

A sample size of approximately 349 completed survey forms yield results with a sampling error of +/-4.5% at the 95% confidence level. The sample must be drawn from the EPZ population.

Consequently, a list of zip codes in the EPZ was developed using 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 Census data 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.

A total of 274 completed samples were obtained corresponding to a sampling error of 5.27% at the 95% confidence level based on the 2020 Census data. This is slightly more than the 4.5%

sampling plan. This was discussed with STPNOC and after multiple attempts to increase the number of responses, a 5.39% sampling error was deemed acceptable for this study. Table F1 also 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.

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.

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. According to the demographic survey results, the average household contains 2.62 people. The estimated household size from the 2020 Census data is 2.40 people.

The difference between the Census data and survey data is 9.17%, which exceeds the sampling error of 5.27%. Upon discussions with STPNOC, it was decided that the U.S. Census estimate of 2.40 people per household should be used for this study. This results in a more conservative estimate when determining the number of households and evacuating vehicles. A sensitivity study was conducted to determine the impact of the average household size on ETE, see Appendix M.

Automobile Ownership The average number of automobiles available per household in the EPZ is 2.26. It should be noted that all but one household in the EPZ (0.37% of households) have access to an automobile according to the demographic survey. The distribution of automobile ownership is presented in Figure F2. Figure F3 and Figure F4 present the automobile availability by household size.

Ridesharing About 75% of the households surveyed responded that they would share a ride with a neighbor, relative, or friend if a car was not available to them when advised to evacuate in the event of an emergency, as shown in Figure F5.

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Commuters Figure F6 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 1.30 commuters in each household in the EPZ, and approximately 76% of households have at least one commuter.

Commuter Travel Modes Figure F7 presents the mode of travel that commuters use on a daily basis. The vast majority (90%) of commuters use their private automobiles to travel to work. The data shows an average of 1.09 commuters per vehicle, assuming 2 people per vehicle - on average - for carpools.

Impact of COVID19 on Commuters Figure F8 presents the distribution of the number of commuters in each household that were temporarily impacted by the COVID19 pandemic. The data shows an average of 0.61 commuters per household were affected by the COVID19 pandemic. Thirtyfour percent (34%)

of households indicated someone in their household had a work and/or school commute that was temporarily impacted by the COVID19 pandemic.

Functional and/or Transportation Needs Figure F9 presents the distribution of the number of individuals with functional or transportation need. The survey results indicate that approximately 3.6% of households have functional or transportation needs. Of those with functional or transportation needs, 19%

require a medical bus/van, 41% require a wheelchair accessible van, 31% require an ambulance, and 9% would require another type of vehicle that was not specified. No household (0%)

responded that they require bus transportation.

F.3.2 Evacuation Response Several questions were asked to gauge the populations response to an emergency. These are now discussed:

How many of the vehicles would your household use during an evacuation? The response is shown in Figure F10. On average, evacuating households would use 1.56 vehicles.

Would your family await the return of other family members prior to evacuating the area?

Of the survey participants who responded, 73% said they would await the return of other family members before evacuating and 27% indicated that they would not await the return of other family members, as shown in Figure F11.

Emergency officials advise you to shelterinplace in an emergency because you are not in the area of risk. Would you? This question is designed to elicit information regarding compliance with instructions to shelter in place.

As shown in Figure F12, the results indicate that 86% of households who are advised to shelter in place would do so; the remaining 14% 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 South Texas Project Electric Generating Station F3 KLD Engineering, P.C.

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2.5.2 of NUREG/CR7002, Rev. 1. Thus, the data obtained above is in close agreement (6% less) with the federal guidance. A sensitivity study was conducted to estimate the impact of shadow evacuation noncompliance of shelter advisory on ETE - see Table M2 in Appendix M.

Emergency officials advise you to shelterinplace 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 F13, 67% of households would follow instructions and delay the start of evacuation until so advised, while the other 33% would choose to begin evacuating immediately.

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.

Approximately 44% of households indicated that they would evacuate to a friend or relatives home, 27% to a hotel, motel or campground, 7% to a second or seasonal home, 2% state they would not evacuate, and the remaining 20% answered other/dont know to this question, as shown in Figure F14. Note that no households (0%) stated they would evacuate to a reception center.

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, 73% of households have a family pet. Of the households with pets, about 18% indicated that they would take their pets with them to a shelter, about 75% indicated that they would take their pets somewhere else and about 7%

would leave their pet at home, as shown in Figure F15.

Of the households that would evacuate with their pets, 96% indicated that they have sufficient room in their vehicle to evacuate with their pet(s)/animal(s).

What type of pet(s) and/or animal(s) do you have? Based on responses from the survey, about 80% of households have a household pet (dog, cat, bird, reptile, or fish), about 18% of households have farm animals (horse, chicken, goat, pig, etc.), and about 2% have other small pets/animals.

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.

As discussed in Section F.3.1 and shown in Figure F8, the majority of respondents (%) indicated no commuters were impacted by the COVID19 pandemic; therefore, the results for the time distribution of commuters (time to prepare to leave work and time to travel home from work) were used as is in this study.

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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.

How long does it take the commuter to complete preparation for leaving work? Figure F16 presents the cumulative distribution for the survey responses. Approximately 88% of households have commuters who can leave work within 45 minutes, the remaining require up to an additional 45 minutes.

How long would it take the commuter to travel home? Figure F17 presents the work to home travel time for the EPZ. Approximately 89% of commuters can arrive within 45 minutes of leaving work, all commuters within 90 minutes.

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. The distribution shown in Figure F18 has a long tail. Approximately, 80% of households can be ready to leave home within 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 30 minutes; the remaining households require up to an additional 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and 30 minutes.

When compared with demographic survey results obtained from surveys of EPZ residents at other nuclear sites, the STP results presented in Figure F16 seem excessive. Both the mean value and standard deviation of this distribution are more than double the value for any other site studied to date. A reason for this is the fact that that the location has seen in large increase in tropical storms and severe hurricanes within the study area. As the demographic survey is not specific to what incident is occurring to prepare for, the EPZ residents may have responded to this survey question with these storms in mind. Consequently, responses to this question are indicative of a level of hurricane preparation that is not relevant to the nuclear power plant evacuation scenario. A complete discussion of this is presented in Section 5.4.1 which discusses comparisons and presents a methodology for handling this issue.

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.

Approximately 77% of households indicated that they have very reliable signal to receive texts and phone calls, 5% indicated that their signal is reliable for text messages only, 17% indicated that they do not always receive cell communications at their residence, and about 1% indicated that they do not have cell service at their residence, as shown in Figure F19.

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 STP. How likely would you be to take action 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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Approximately 65% of households indicated that they are highly likely to take action on these directions, about 27% indicated likely, 6% indicated neither likely nor unlikely, 1% indicated unlikely, and another 1% indicated highly unlikely for them to take action on emergency management officials directions, as shown in Figure F20.

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 EPZ.

Approximately 74% of households indicated that a text message from emergency officials would be most likely to alert them at their residence, 14% indicated that a siren sounding near their home would be the most likely method, 4% indicated an alert broadcast on the TV, 3%

indicated that a phone call/text message from a family member, friend or neighbor, 3%

indicated that information on Twitter or Facebook, 1% indicated that an alert broadcast on the radio would be the most likely way to alert them at their residence and 1% answered other to this question, as shown in Figure F21.

Table F1. STP Demographic Survey Sampling Plan Population within EPZ Households Desired Obtained Zip Code (2020) (2020) Sample Samples 77414 904 380 101 171 77419 227 95 25 10 77428 49 21 6 3 77440 30 13 3 2 77456 21 9 2 8 77457 571 240 64 22 77465 1,034 434 115 46 Total 3,132 1,316 349 274 South Texas Project Electric Generating Station F6 KLD Engineering, P.C.

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Household Size 50%

40%

Percent of Households 30%

20%

10%

0%

1 2 3 4 5 6+

People Figure F1. Household Size in the EPZ Vehicle Availability 60%

48.54%

50%

Percent of Households 40%

30%

24.09%

20% 17.88%

10% 7.66%

0.37% 1.46%

0%

0 1 2 3 4 5+

Vehicles Figure F2. Household Vehicle Availability South Texas Project Electric Generating Station F7 KLD Engineering, P.C.

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Distribution of Vehicles by HH Size 14 Person Households 1 Person 2 People 3 People 4 People 100%

80%

Percent of Households 60%

40%

20%

0%

0 1 2 3 4 5+

Vehicles Figure F3. Vehicle Availability 1 to 4 Person Households Distribution of Vehicles by HH Size 58 Person Households 5 People 6 People 7 People 8 People 100%

80%

Percent of Households 60%

40%

20%

0%

1 2 3 4 5+

Vehicles Figure F4. Vehicle Availability 5 to 8 Person Households South Texas Project Electric Generating Station F8 KLD Engineering, P.C.

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Rideshare with Neighbor/Friend 100%

80%

Percent of Households 60%

40%

20%

0%

Yes No Figure F5. Household Ridesharing Preference Commuters per Household 50%

40%

Percent of Households 30%

20%

10%

0%

0 1 2 3 4+

Commuters Figure F6. Commuters per Households in the EPZ South Texas Project Electric Generating Station F9 KLD Engineering, P.C.

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Travel Mode to Work 100%

89.2%

80%

Percent of Commuters 60%

40%

20%

8.7%

0.3% 1.2% 0.6%

0%

Rail Bus Walk/Bike Drive Alone Carpool (2+)

Mode of Travel Figure F7. Modes of Travel in the EPZ COVID19 Impact to Commuters 70%

60%

50%

Percent of Households 40%

30%

20%

10%

0%

0 1 2 3 4+

Commuters Figure F8. Impact to Commuters due to the COVID19 Pandemic South Texas Project Electric Generating Station F10 KLD Engineering, P.C.

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Functional Vehicle Transportation Needs 50%

41%

40%

Percent of Households 31%

30%

20% 19%

9%

10%

0%

0%

Bus Medical Bus/Van Wheelchair Ambulance Other Accessible Vehicle Figure F9. Households with Functional or Transportation Needs Evacuating Vehicles Per Household 100%

80%

Percent of Households 60%

51.5%

41.5%

40%

20%

4.8%

0.4% 1.8%

0%

0 1 2 3 4+

Vehicles Figure F10. Number of Vehicles Used for Evacuation South Texas Project Electric Generating Station F11 KLD Engineering, P.C.

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Await Returning Commuter 100%

80%

Percent of Households 60%

40%

20%

0%

Yes, would await return No, would evacuate Figure F11. Percent of Households that Await Returning Commuter Before Leaving Shelter in Place Characteristics 100%

Percent of Households 80%

60%

40%

20%

0%

Shelter Evacuate Figure F12. Shelter in Place Characteristics South Texas Project Electric Generating Station F12 KLD Engineering, P.C.

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Shelter then Evacuate Characteristics 100%

80%

Percent of Households 60%

40%

20%

0%

Shelter, then Evacuate Evacuate Immediately Figure F13. Shelter Then Evacuate Characteristics Shelter Locations 50%

43.9%

40%

Percent of Households 30%

27.5%

19.7%

20%

10%

6.7%

2.2%

0.0%

0%

Friend/Relative's Reception Center Hotel, Motel, or A Would not Other/Don't Home Campground Second/Seasonal Evacuate Know Home Figure F14. Study Area Evacuation Destinations South Texas Project Electric Generating Station F13 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

Households Evacuating with Pets/Animals 80%

60%

Percent of Households 40%

20%

0%

Take with me to a Shelter Take with me to Somewhere Leave Pet at Home Else Figure F15. Households Evacuating with Pets/Animals Time to Prepare to Leave Work/College 100%

80%

Percent of Commuters 60%

40%

20%

0%

0 10 20 30 40 50 60 70 80 90 100 Preparation Time (min)

Figure F16. Time Required to Prepare to Leave Work/College South Texas Project Electric Generating Station F14 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

Time to Commute Home From Work/College 100%

80%

Percent of Commuters 60%

40%

20%

0%

0 10 20 30 40 50 60 70 80 90 100 Travel Time (min)

Figure F17. Time to Commute Home from Work/College Time to Prepare to Leave Home 100%

80%

Percent of Households 60%

40%

20%

0%

0 60 120 180 240 300 360 420 Preparation Time (min)

Figure F18. Time to Prepare Home for Evacuation South Texas Project Electric Generating Station F15 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

Cell Phone Signal Reliability 100%

80% 76.7%

Percent of Households 60%

40%

20% 17.0%

5.2%

1.1%

0%

VERY RELIABLE TO RELIABLE FOR TEXT I DO NOT ALWAYS I DO NOT HAVE CELL RECEIVE MESSAGES ONLY RECEIVE CELL SERVICE TEXTS AND PHONE COMMUNICATIONS AT AT MY RESIDENCE CALLS MY RESIDENCE Figure F19. Cell Phone Signal Reliability Likelihood to Take Action Based off Guidelines 100%

80%

Percent of Households 65.3%

60%

40%

26.7%

20%

5.8%

1.1% 1.1%

0%

HIGHLY LIKELY LIKELY NEITHER LIKELY UNLIKELY HIGHLY UNLIKELY NOR UNLIKELY Figure F20. Likelihood to Take Action Based off Emergency Management Officials Guidelines South Texas Project Electric Generating Station F16 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

Emergency Communications 100%

80% 74.0%

Percent of Households 60%

40%

20% 14.3%

4.0% 3.3% 3.3%

0.7% 0.4%

0%

A SIREN A TEXT ALERT ALERT Phone Information on Other SOUNDING MESSAGE BROADCAST BROADCAST call/Text Twitter or NEAR YOUR FROM ON RADIO ON TV message from Facebook HOME EMERGENCY family, friend, OFFICIALS or neighbor Figure F21. Emergency Communication Alert South Texas Project Electric Generating Station F17 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

ATTACHMENT A Demographic Survey Instrument South Texas Project Electric Generating Station F18 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 0

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APPENDIX G Traffic Management Plan

G. TRAFFIC MANAGEMENT PLAN NUREG/CR7002, Rev. 1 indicates that the existing Traffic and Access Control Points (TACP) identified by the offsite agencies should be used in the evacuation simulation modeling. The traffic control plans for the Emergency Planning Zone (EPZ) were provided by Matagorda County.

These plans were reviewed and the TACPs were modeled accordingly. An analysis of the TACP locations was performed, and it was determined to model the ETE simulations with existing TACPs that were provided in the approved county and state emergency plans, with no additional TACPs recommended.

G.1 Manual Traffic Control The TACPs 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 pre timed signal, stop, or yield control, and the intersection is identified as a traffic control point (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. MTCs 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/ACP, the control type is indicated as TACP in Table K1.

These MTC points, as shown in the Emergency Management Plan for Matagorda County, Bay City, and Palacios (Annex W - Tab 3 Evacuation) dated June 2017, Rev. 15, are mapped as light green dots in Figure G1. No additional locations for MTC are suggested in this study.

It is assumed that the TACPs will be established within 120 minutes of the advisory to evacuate (ATE) to discourage through travelers from using major through routes which traverse the EPZ.

As discussed in Section 3.8 external traffic was considered on SH 35 and FM 616 in this analysis.

G.2 Analysis of Key TACP 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 (TMPs) 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 TMPs.

The majority of the TACPs 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 currently exists at each location. To determine the impact of MTC at these locations, a winter, midweek, midday, with good weather scenario (Scenario 6) evacuation of the 2Mile Region, 5Mile Region, and the South Texas Project Electric Generating Station G1 KLD Engineering, P.C.

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entire EPZ (Region R01, R02, R03) were simulated wherein these intersections were left as is (without MTC). The results are shown in Table G2.

The results were compared to the results presented in Section 7. The ETE remained unchanged when compared to the cases wherein these controlled intersections were modeled as actuated signals (with MTC) for Scenario 6 Regions R01, R02, and R03. Although localized congestion worsened, there is no change in ETE at both the 90th and 100th percentile when MTC was not present at these intersections. The remaining TACPs at controlled intersections were left as actuated signals in the model and, therefore, had no impact to ETE.

As shown in Figure 73 through Figure 76, majority of the EPZ experiences no congestion throughout the evacuation of the full EPZ, except for small portions of PRZ 1 (on Plant Access Road) and PRZ 6 (on SH 60 and FM 521).The congestion clears in the EPZ by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE. As such, the TACPs do very little to help the 90th percentile ETE for the full EPZ. As there is no significant congestion within Regions R01 and R02, there is no benefit to ETE from the MTC for these regions. In addition, congestion within the EPZ clears prior to the completion of the trip generation time (as the time to mobilize, plus travel time to EPZ boundary) and dictates the 100th percentile ETE); as a result, the MTC has no impact on the 100th percentile ETEs.

Although there is no reduction in ETE when MTC is implemented, traffic and access control can be beneficial in the reduction of localized 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 TACPs, the list of locations provided in Table G1 could be considered as priority locations when implementing the TMP as the few remaining TCPs already have actuated traffic signals which would mimic MTC or they are located along the Columbia River which does not impact the evacuees using vehicles during an evacuation.

South Texas Project Electric Generating Station G2 KLD Engineering, P.C.

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Table G1. List of Key Manual Traffic Control Locations Previous Control 1

TACP # Node # (Prior to being a TACP)

CP4 690 Stop Sign CP6 1350 Stop Sign CP9 1225 Stop Sign CP10 1176 Stop Sign CP12 90 Stop Sign CP13 93 Stop Sign CP15 1191 Stop Sign CP16 230 Stop Sign CP17 1262 Stop Sign CP18 640 Stop Sign CP19 730 Stop Sign Table G2. ETE with No Manual Traffic Control Scenario 6 th Region 90 Percentile ETE 100th Percentile ETE Base No MTC Difference Base No MTC Difference R01 (2Mile) 1:15 1:15 0:00 1:45 1:45 0:00 R02 (5Mile) 1:55 1:55 0:00 4:50 4:50 0:00 R03 (Full EPZ) 2:35 2:35 0:00 4:55 4:55 0:00 1

Source: Emergency Management Plan for Matagorda County, Bay City, and Palacios, Annex W - Tab 3 South Texas Project Electric Generating Station G3 KLD Engineering, P.C.

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Figure G1. Traffic and Access Control Points for the STP EPZ South Texas Project Electric Generating Station G4 KLD Engineering, P.C.

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APPENDIX H Evacuation Regions

H EVACUATION REGIONS This appendix presents the evacuation percentages for each Evacuation Region (Table H1) and maps of all Evacuation Regions. The percentages presented in Table H1 are based on the methodology discussed in assumption 7 of Section 2.2 and shown in Figure 21.

Note the baseline ETE study assumes 20 percent of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR7002, Rev. 1.

South Texas Project Electric Generating Station H1 KLD Engineering, P.C.

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Table H1. Percent of PRZ Population Evacuating for Each Region Radial Regions Protective Response Zone Region Description 11 2 3 4 5 6 7 8 9 10 11 R01 2Mile Region 100% 20% 20% 20% 20% 20% 20% 20% 20% 20% 20%

R02 5Mile Region 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20%

R03 Full EPZ 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

Evacuate 2Mile Region and Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R04 34450 100% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20%

R05 51106 100% 20% 20% 100% 100% 20% 20% 20% 20% 20% 20%

R06 107140 100% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20%

R07 141174 100% 100% 20% 20% 100% 20% 20% 20% 20% 20% 20%

R08 175230 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20%

R09 231286 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20%

R10 287331 100% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20%

N/A 332343 Refer to Region R01 Evacuate 2Mile Region and Downwind to the EPZ Boundary Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R11 34450 100% 20% 20% 100% 20% 20% 20% 100% 100% 20% 20%

R12 5161 100% 20% 20% 100% 100% 20% 20% 100% 100% 100% 20%

R13 6295 100% 20% 20% 100% 100% 20% 20% 20% 100% 100% 20%

R14 96106 100% 20% 20% 100% 100% 20% 20% 20% 100% 100% 100%

R15 107129 100% 20% 20% 20% 100% 20% 20% 20% 100% 100% 100%

R16 130140 100% 20% 20% 20% 100% 20% 20% 20% 20% 100% 100%

R17 141163 100% 100% 20% 20% 100% 20% 20% 20% 20% 100% 100%

R18 164174 100% 100% 20% 20% 100% 100% 20% 20% 20% 100% 100%

R19 175219 100% 100% 20% 20% 20% 100% 20% 20% 20% 20% 100%

R20 220230 100% 100% 20% 20% 20% 100% 20% 20% 20% 20% 20%

R21 231286 100% 100% 100% 20% 20% 100% 100% 20% 20% 20% 20%

R22 287298 100% 20% 100% 20% 20% 20% 100% 20% 20% 20% 20%

R23 299331 100% 20% 100% 20% 20% 20% 100% 100% 20% 20% 20%

R24 332343 100% 20% 20% 20% 20% 20% 20% 100% 20% 20% 20%

Staged Evacuation 2Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind From Protective Response Zone Region (in Degrees) 11 2 3 4 5 6 7 8 9 10 11 R25 5Mile Region 100% 100% 100% 100% 100% 20% 20% 20% 20% 20% 20%

R26 34450 100% 20% 20% 100% 20% 20% 20% 20% 20% 20% 20%

R27 51106 100% 20% 20% 100% 100% 20% 20% 20% 20% 20% 20%

R28 107140 100% 20% 20% 20% 100% 20% 20% 20% 20% 20% 20%

R29 141174 100% 100% 20% 20% 100% 20% 20% 20% 20% 20% 20%

R30 175230 100% 100% 20% 20% 20% 20% 20% 20% 20% 20% 20%

R31 231286 100% 100% 100% 20% 20% 20% 20% 20% 20% 20% 20%

R32 287331 100% 20% 100% 20% 20% 20% 20% 20% 20% 20% 20%

N/A 332343 Refer to Region R01 PRZ(s) ShelterinPlace until 90% ETE for R01, PRZ(s) Evacuate PRZ(s) ShelterinPlace then Evacuate 1

PRZ 1 also includes the South Texas Project Reservoir.

South Texas Project Electric Generating Station H2 KLD Engineering, P.C.

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Figure H1. Region R01 South Texas Project Electric Generating Station H3 KLD Engineering, P.C.

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Figure H2. Region R02 South Texas Project Electric Generating Station H4 KLD Engineering, P.C.

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Figure H3. Region R03 South Texas Project Electric Generating Station H5 KLD Engineering, P.C.

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Figure H4. Region R04 South Texas Project Electric Generating Station H6 KLD Engineering, P.C.

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Figure H5. Region R05 South Texas Project Electric Generating Station H7 KLD Engineering, P.C.

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Figure H6. Region R06 South Texas Project Electric Generating Station H8 KLD Engineering, P.C.

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Figure H7. Region R07 South Texas Project Electric Generating Station H9 KLD Engineering, P.C.

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Figure H8. Region R08 South Texas Project Electric Generating Station H10 KLD Engineering, P.C.

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Figure H9. Region R09 South Texas Project Electric Generating Station H11 KLD Engineering, P.C.

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Figure H10. Region R10 South Texas Project Electric Generating Station H12 KLD Engineering, P.C.

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Figure H11. Region R11 South Texas Project Electric Generating Station H13 KLD Engineering, P.C.

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Figure H12. Region R12 South Texas Project Electric Generating Station H14 KLD Engineering, P.C.

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Figure H13. Region R13 South Texas Project Electric Generating Station H15 KLD Engineering, P.C.

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Figure H14. Region R14 South Texas Project Electric Generating Station H16 KLD Engineering, P.C.

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Figure H15. Region R15 South Texas Project Electric Generating Station H17 KLD Engineering, P.C.

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Figure H16. Region R16 South Texas Project Electric Generating Station H18 KLD Engineering, P.C.

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Figure H17. Region R17 South Texas Project Electric Generating Station H19 KLD Engineering, P.C.

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Figure H18. Region R18 South Texas Project Electric Generating Station H20 KLD Engineering, P.C.

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Figure H19. Region R19 South Texas Project Electric Generating Station H21 KLD Engineering, P.C.

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Figure H20. Region R20 South Texas Project Electric Generating Station H22 KLD Engineering, P.C.

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Figure H21. Region R21 South Texas Project Electric Generating Station H23 KLD Engineering, P.C.

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Figure H22. Region R22 South Texas Project Electric Generating Station H24 KLD Engineering, P.C.

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Figure H23. Region R23 South Texas Project Electric Generating Station H25 KLD Engineering, P.C.

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Figure H24. Region R24 South Texas Project Electric Generating Station H26 KLD Engineering, P.C.

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Figure H25. Region R25 South Texas Project Electric Generating Station H27 KLD Engineering, P.C.

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Figure H26. Region R26 South Texas Project Electric Generating Station H28 KLD Engineering, P.C.

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Figure H27. Region R27 South Texas Project Electric Generating Station H29 KLD Engineering, P.C.

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Figure H28. Region R28 South Texas Project Electric Generating Station H30 KLD Engineering, P.C.

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Figure H29. Region R29 South Texas Project Electric Generating Station H31 KLD Engineering, P.C.

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Figure H30. Region R30 South Texas Project Electric Generating Station H32 KLD Engineering, P.C.

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Figure H31. Region R31 South Texas Project Electric Generating Station H33 KLD Engineering, P.C.

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Figure H32. Region R32 South Texas Project Electric Generating Station H34 KLD Engineering, P.C.

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APPENDIX J Representative Inputs to and Outputs from the DYNEV II System

J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM This appendix presents data input to and output from the DYNEV II System.

Table J1 provides source (vehicle loading) and destination information for several roadway segments (links) in the analysis network. In total, there are a total of 116 source links (origins) in the model. The source links are shown as centroid points in Figure J1. On average, evacuees travel a straightline distance of 3.41 miles to exit the network.

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 scenarios (Scenarios 2, 4, 7 and 9), exhibit slower average speeds, higher delays, and longer average travel times when compared to good weather scenarios. When comparing scenario 11 (special event) and scenario 3, the additional vehicles from the special event lowers the average speeds, causes higher delays and increases the travel time.

Table J3 provides statistics (average speed and travel time) for the major evacuation routes -

SH 35 and SH 60 - for an evacuation of the entire EPZ (Region R03) under Scenario 1 conditions.

The study area has ample roadway capacity to service all evacuating vehicles within the EPZ and Shadow Region. As discussed in Section 7.3 and shown in Figures 73 through 76, SH 35 and SH 60 experience minor congestion, specifically in Bay City in the Shadow Region which clears at 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> after the Advisory to Evacuate (ATE). As such, the average speeds are slightly slower (and travel times longer) on the major roadways from the beginning of the evacuation until 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br />, after this time the speeds are relatively close to the free flow speed on SH 35 and SH 60.

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.

Figure J2 through Figure J13 plot the trip generation time versus the ETE for each of the 12 Scenarios considered. The distance between the trip generation and ETE curves is the travel time. Plots of trip generation 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 J13, the curves are close together as a result of the minimal traffic congestion in the EPZ, discussed in detail in Section 7.3, for all scenarios except during the summer, weekend, midday with good weather and special event scenario (Scenario 11). During Scenario 11, there is a large number of transients from the beachgoers to Matagorda Beach during a holiday weekend. Congestion exists until approximately 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> following the ATE, as seen in Figure J12 (curves are spatially separated for about 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and then become closer together as a result of the minimal traffic congestion within the EPZ at this time).

1 Computed as the difference of the average travel time and the average ideal travel time under free flow conditions.

South Texas Project Electric Generating Station J1 KLD Engineering, P.C.

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Table J1. Sample Simulation Model Input Vehicles Entering Link Upstream Downstream Network Directional Destination Destination Number Node Node on this Link Preference Nodes Capacity 8622 1,700 87 550 560 17 N 8621 1,700 8982 1,700 156 821 1252 10 SW 8844 1,700 8481 2,850 243 1154 1155 37 N 8101 1,700 8622 1,700 8481 2,850 291 1208 1209 76 NW 8101 1,700 8622 1,700 8141 1,700 350 1272 1223 794 E 8481 2,850 8101 1,700 8481 2,850 375 1352 1000 40 W 8101 1,700 8622 1,700 8481 2,850 427 1395 1482 147 N 8101 1,700 8101 1,700 450 1417 1416 93 N 8481 2,850 8481 2,850 493 1451 560 42 N 8101 1,700 South Texas Project Electric Generating Station J2 KLD Engineering, P.C.

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Table J2. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03)

Scenario 1 2 3 4 5 6 NetworkWide Average 1.2 1.3 1.2 1.3 1.2 1.2 Travel Time (Min/VehMi)

NetworkWide Average 0.2 0.3 0.2 0.3 0.2 0.2 Delay Time (Min/VehMi)

NetworkWide Average 50.6 46.3 51.5 47.1 50.1 50.6 Speed (mph)

Total Vehicles 11,373 11,389 7,942 7,952 6,666 11,470 Exiting Network Scenario 7 8 9 10 11 12 NetworkWide Average 1.3 1.2 1.3 1.2 1.7 1.2 Travel Time (Min/VehMi)

NetworkWide Average 0.3 0.2 0.3 0.2 0.7 0.2 Delay Time (Min/VehMi)

NetworkWide Average 46.2 51.5 47.1 50.1 35.0 50.1 Speed (mph)

Total Vehicles 11,486 7,867 7,877 6,615 10,441 11,373 Exiting Network Table J3. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Scenario 1)

Elapsed Time (hours) 1:00 2:00 3:00 4:00 4:55 Travel Length Speed Time Travel Travel Travel Travel Route Name (miles) (mph) (min) Speed Time Speed Time Speed Time Speed Time SH 35 Westbound 40.3 58.4 41.4 58.0 41.6 60.9 39.7 61.5 39.3 57.7 41.9 SH 35 Eastbound 40.5 56.7 42.9 56.7 42.9 56.9 42.8 56.7 42.9 63.4 38.3 SH 60 Northbound 23.3 51.0 27.4 51.5 27.1 51.1 27.4 51.3 27.3 59.0 23.7 Table J4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 Elapsed Time (hh:mm)

Upstream Downstream 1:00 2:00 3:00 4:00 4:55 Road Name Node Node Cumulative Vehicles Discharged by the Indicated Time Cumulative Percent of Vehicles Discharged by the Indicated Time 375 818 1,063 1,148 1,160 FM 521 Eastbound 140 141 22% 13% 11% 10% 10%

540 2,554 4,175 4,735 4,846 SH 35 Eastbound 480 481 32% 40% 42% 42% 43%

13 71 131 153 156 SH 71 Northbound 622 1447 1% 1% 1% 1% 1%

384 1,084 1,565 1,666 1,685 FM 616 Westbound 981 982 23% 17% 16% 15% 15%

30 227 349 381 387 SH 111 Westbound 1446 621 2% 4% 4% 3% 3%

192 903 1,457 1,665 1,707 SH 60 Northbound 1469 1103 11% 14% 15% 15% 15%

162 662 1,215 1,397 1,434 SH 35 Westbound 1481 1477 10% 10% 12% 13% 13%

South Texas Project Electric Generating Station J3 KLD Engineering, P.C.

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Figure J1. Network Sources/Origins South Texas Project Electric Generating Station J4 KLD Engineering, P.C.

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ETE and Trip Generation Summer, Midweek, Midday, Good Weather (Scenario 1)

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 Elapsed Time (h:mm)

Figure J2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1)

ETE and Trip Generation Summer, Midweek, Midday, Rain (Scenario 2)

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 Elapsed Time (h:mm)

Figure J3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2)

South Texas Project Electric Generating Station J5 KLD Engineering, P.C.

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ETE and Trip Generation Summer, Weekend, Midday, Good Weather (Scenario 3)

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 Elapsed Time (h:mm)

Figure J4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3)

ETE and Trip Generation Summer, Weekend, Midday, Rain (Scenario 4)

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 Elapsed Time (h:mm)

Figure J5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4)

South Texas Project Electric Generating Station J6 KLD Engineering, P.C.

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ETE and Trip Generation Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)

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 Elapsed Time (h:mm)

Figure J6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)

ETE and Trip Generation Winter, Midweek, Midday, Good Weather (Scenario 6)

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 Elapsed Time (h:mm)

Figure J7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6)

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ETE and Trip Generation Winter, Midweek, Midday, Rain (Scenario 7)

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 Elapsed Time (h:mm)

Figure J8. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7)

ETE and Trip Generation Winter, Weekend, Midday, Good Weather (Scenario 8)

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 Elapsed Time (h:mm)

Figure J9. ETE and Trip Generation: Winter, Weekend, Midday, Good (Scenario 8)

South Texas Project Electric Generating Station J8 KLD Engineering, P.C.

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ETE and Trip Generation Winter, Weekend, Midday, Rain (Scenario 9)

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 Elapsed Time (h:mm)

Figure J10. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 9)

ETE and Trip Generation Winter, Midweek, Weekend, Evening, Good Weather (Scenario 10)

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 Elapsed Time (h:mm)

Figure J11. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 10)

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ETE and Trip Generation Summer, Weekend, Midday, Good Weather, Special Event (Scenario 11)

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 Elapsed Time (h:mm)

Figure J12. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather, Special Event (Scenario 11)

ETE and Trip Generation Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 12)

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 Elapsed Time (h:mm)

Figure J13. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 12)

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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 23 more detailed figures (Figure K2 through Figure K24) which show each of the links and nodes in the network.

The analysis network was calibrated using the observations made during the field surveys conducted in April 2021.

Table K1 summarizes the number of nodes by the type of control (stop sign, yield sign, pre timed signal, actuated signal, traffic and access control point [TACP], uncontrolled).

Table K1. Summary of Nodes by the Type of Control Number of Control Type Nodes Uncontrolled 307 Pretimed 3 Actuated 23 Stop 63 TCAP 20 Yield 8 Total: 424 South Texas Project Electric Generating Station K1 KLD Engineering, P.C.

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Figure K1. STP LinkNode Analysis Network South Texas Project Electric Generating Station K2 KLD Engineering, P.C.

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Figure K2. LinkNode Analysis Network - Grid 1 South Texas Project Electric Generating Station K3 KLD Engineering, P.C.

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Figure K3. LinkNode Analysis Network - Grid 2 South Texas Project Electric Generating Station K4 KLD Engineering, P.C.

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Figure K4. LinkNode Analysis Network - Grid 3 South Texas Project Electric Generating Station K5 KLD Engineering, P.C.

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Figure K5. LinkNode Analysis Network - Grid 4 South Texas Project Electric Generating Station K6 KLD Engineering, P.C.

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Figure K6. LinkNode Analysis Network - Grid 5 South Texas Project Electric Generating Station K7 KLD Engineering, P.C.

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Figure K7. LinkNode Analysis Network - Grid 6 South Texas Project Electric Generating Station K8 KLD Engineering, P.C.

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Figure K8. LinkNode Analysis Network - Grid 7 South Texas Project Electric Generating Station K9 KLD Engineering, P.C.

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Figure K9. LinkNode Analysis Network - Grid 8 South Texas Project Electric Generating Station K10 KLD Engineering, P.C.

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Figure K10. LinkNode Analysis Network - Grid 9 South Texas Project Electric Generating Station K11 KLD Engineering, P.C.

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Figure K11. LinkNode Analysis Network - Grid 10 South Texas Project Electric Generating Station K12 KLD Engineering, P.C.

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Figure K12. LinkNode Analysis Network - Grid 11 South Texas Project Electric Generating Station K13 KLD Engineering, P.C.

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Figure K13. LinkNode Analysis Network - Grid 12 South Texas Project Electric Generating Station K14 KLD Engineering, P.C.

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Figure K14. LinkNode Analysis Network - Grid 13 South Texas Project Electric Generating Station K15 KLD Engineering, P.C.

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Figure K15. LinkNode Analysis Network - Grid 14 South Texas Project Electric Generating Station K16 KLD Engineering, P.C.

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Figure K16. LinkNode Analysis Network - Grid 15 South Texas Project Electric Generating Station K17 KLD Engineering, P.C.

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Figure K17. LinkNode Analysis Network - Grid 16 South Texas Project Electric Generating Station K18 KLD Engineering, P.C.

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Figure K18. LinkNode Analysis Network - Grid 17 South Texas Project Electric Generating Station K19 KLD Engineering, P.C.

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Figure K19. LinkNode Analysis Network - Grid 18 South Texas Project Electric Generating Station K20 KLD Engineering, P.C.

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Figure K20. LinkNode Analysis Network - Grid 19 South Texas Project Electric Generating Station K21 KLD Engineering, P.C.

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Figure K21. LinkNode Analysis Network - Grid 20 South Texas Project Electric Generating Station K22 KLD Engineering, P.C.

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Figure K22. LinkNode Analysis Network - Grid 21 South Texas Project Electric Generating Station K23 KLD Engineering, P.C.

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Figure K23. LinkNode Analysis Network - Grid 22 South Texas Project Electric Generating Station K24 KLD Engineering, P.C.

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Figure K24. LinkNode Analysis Network - Grid 23 South Texas Project Electric Generating Station K25 KLD Engineering, P.C.

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APPENDIX L Protective Response Zone Boundaries

L. PROTECTIVE RESPONSE ZONE (PRZ) BOUNDARIES PRZ 1 An area generally north and northeast of the South Texas Project Electric Generating Station (STP) and FM 521, running in an arc around the northern portion of the Station.

(Note: No resident population in this area.)

PRZ 2 An area generally northeast of the STP within these boundaries: East of FM 1468, south of FM 3057, west of FM 2668, and north of FM 521 east, and which includes OXEA/Celanese.

PRZ 3 An area generally southeast of the STP within these boundaries: East of the Colorado River and Kelly Lake, south of FM 521, west of SH 60, north of the protection levee at Matagorda, and includes Selkirk Island, Exotic Isle, and Lyondellbasell.

PRZ 4 An area generally west of the STP within these boundaries: East of FM 1095, south of FM 521, west of CR 392, north of CR 391, and which includes Tin Top and Citrus Grove Community.

PRZ 5 An area generally northwest of the STP within these boundaries: East of the Tres Palacios River, south of Wilson Creek, west of FM 1468, and north of FM 521.

PRZ 6 An area generally northeast of the STP within these boundaries: East of the Colorado River and Celanese, south and west of Live Oak Creek, west of CR 262, north of FM 521, FM 3057, and includes Riverside Park, Hales Acres, and Meadowbrook Estates.

PRZ 7 An area generally east and southeast of the STP within these boundaries: East of SH 60, west of CR 262, and CR 248, south of CR 237 and south of the Protection Levy of Matagorda, north of St. Mary's Bayou which includes the town of Matagorda and the Intracoastal Waterway east of the Colorado River.

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PRZ 8 An area generally south of the STP within these boundaries: East of Mad Island Slough, south of the STP south property boundary, west of the Colorado River, and north of West Matagorda Bay.

PRZ 9 An area generally southwest of the STP within these boundaries: East of SH 35, south of FM 521, west of FM 1095, and Mad Island Slough, and which includes Collegeport and the northern portion of Tres Palacios Bay.

PRZ 10 An area generally northwest of the STP within these boundaries: East and south of SH 35, west of the northern portion of FM 1095 and the Tres Palacios River, north of FM 521, and which includes Tidewater Oaks and Tres Palacios Oaks.

PRZ 11 An area generally north of the STP within these boundaries: East of the northern portion of FM 1095, south of SH 35, west of the northern portion of the Colorado River, north of Wilson Creek, and which includes El Maton and Buckeye.

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APPENDIX M Evacuation Sensitivity Studies

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.

M.1 Effect of Changes in Trip Generation Times A sensitivity study was performed to determine whether changes in the estimated trip generation time have an effect on the ETE for the entire Emergency Planning Zone (EPZ).

Specifically, if the tail of the mobilization distribution were truncated (i.e., if those who responded most slowly to the Advisory to Evacuate (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 6, Region 3; a winter, midweek, midday, with good weather evacuation of the entire EPZ. Table M1 presents the results of this study.

If evacuees mobilize one hour quicker, the 90th percentile ETE is reduced by 5 minutes and the 100th percentile ETE is reduced by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> (a significant change). If evacuees mobilize one hour slower, the 90th percentile ETE by 55 minutes and the 100th percentile ETE by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> - a significant change.

As discussed in Section 7.3, there is traffic congestion within the EPZ that persists until 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE, well before the completion of trip generation time. As such, congestion dictates the 100th percentile ETE until 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes after the ATE. After this time, trip generation (plus a 10minute travel time to the EPZ boundary) dictates the ETE at the 100th percentile. As such the 100th percentile ETE are directly impacted by increases in trip generation times. The 90th percentile ETE are relatively insensitive to truncating the tail of the mobilization time distribution. However, elongating the tail of the mobilization time distribution has a significant impact to the 90th percentile ETE.

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 6, Region 3; a winter, midweek, midday, with good weather evacuation for 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.

Table M2 presents the ETE for each of the cases considered. The results show decreasing or increasing the shadow evacuation by any value has no impact on the 100th percentile ETE. This is due to the 100th percentile ETE being dictated by trip generation time. An elimination of the shadow evacuation (0%) decreases the 90th percentile ETE by 5 minutes - not a significant change.

Tripling (60%) the shadow evacuation increases the 90th percentile ETE by 10 minutes. A full South Texas Project Electric Generating Station M1 KLD Engineering, P.C.

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evacuation of the Shadow Region (100%) results in the 90th percentile ETE increasing by 15 minutes.

Note, the demographic survey results presented in Appendix F indicate that 14 percent of households would elect to evacuate if advised to shelter, which differs slightly from the 20 percent noncompliance as suggested in NUREG/CR7002, Rev. 1.A sensitivity study was run using 14 percent shadow evacuation and the ETE decreases by 5 minutes for the 90th percentile ETE and the 100th percentile ETE remains the same.

The Shadow Region for STP is sparsely populated except for areas of Matagorda beach, south of the plant, Bay City and Palacios. In addition, as shown in Figures 73 through Figure 76, congestion exists within the Shadow Region in Bay City and just east of Wadsworth on FM 512, such that the EPZ evacuees would be delayed during an evacuation trip. Therefore, any additional shadow residents that decide to voluntarily evacuate increases this congestion, delay the egress of EPZ evacuees and prolong ETE.

M.3 Effect of Changes in the Permanent Resident Population A sensitivity study was conducted to determine the effect on ETE due to changes in the permanent 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.

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).

The sensitivity study was conducted using the following planning assumptions:

1. The percent change in population within the study area was increased by up to 150%.

Changes in population were applied to permanent residents only (as per federal guidance), in both the EPZ and the Shadow Region.

2. The transportation infrastructure (as presented in Appendix K) remained fixed; the presence of future proposed roadway changes and/or highway capacity improvements were not considered.

3. The study was performed for the 2Mile Region (R01), the 5Mile Region (R02) and the entire EPZ (R03).

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4. The scenario (excluding roadway impact) which yielded the highest 90th percentile ETE values was selected as the case to be considered in this sensitivity study (Scenario 11 -

Summer, Weekend, Midday, with Good Weather, Special Event). The special event considered for this study, a holiday weekend with beachgoers at Matagorda Beach, which is justified due that the event can occur multiple times during the peak season.

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. The base ETE value for the 2Mile Region (R01) is less than 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />; R01 criterion for update is 19 minutes (75 minutes multiplied by 25%). Base ETE value for the 5Mile Region (R02), and entire EPZ (R03) are greater than 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />; 25 percent of the base ETE is always equal or greater than 30 minutes; therefore, the criterion for updating is 30 minutes.

Those percent population changes which result in the longest 90th percentile ETE change greater than or equal to 30 minutes are highlighted in red in Table M3 - a 150% or greater increase in the full EPZ permanent population (includes 20% of the Shadow Region permanent resident population). STPNOC will have to estimate the EPZ population on an annual basis. If the study area population increases by 150% or more, an updated ETE analysis will be needed.

M.4 Effect of Changes in Average Household Size As discussed in Appendix F, the average household size obtained from the results of the demographic survey is 2.62 people per household. The 2020 census indicates an average household size of 2.40 people per household. The difference between the Census data and survey data is 9.17%, which exceeds the sampling error of 5.27%. Upon discussions with STPNOC, it was decided that the 2020 Census estimate of 2.40 people per household would be used in the 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 6, Region 3; a winter, midweek, midday, with good weather evacuation of the 2Mile Region, 5Mile Region, and entire EPZ. Table M4 presents the results of this study.

Increasing the average household size (decreasing the total number evacuating vehicles) to 2.62 people per household decreases in the 90th percentile ETE by 5 minutes for the 2Mile Region and full EPZ and has no impact on the 100th percentile ETE. There is no impact to the 2Mile Region 90th percentile ETE, as there are no permanent residents within the 2Mile Region. The difference in evacuating vehicles is about 4% of the total evacuating traffic (437 vehicles of 10,881 vehicles for this scenario - see Table 64). This 4% reduction in evacuating vehicles has minimal impact to congestion in the study area, and therefore minimal impacts to the ETE.

As previously mentioned, the ETE is dictated by trip mobilization time at the 100th percentile. As a result, regardless of the reduction in vehicles, the 100th percentile ETE will remain the same.

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M.5 Enhancements in Evacuation Time This appendix documents sensitivity studies on critical variables that could potentially impact ETE.

Possible improvements to ETE are further discussed below:

Prolonging the trip generation time by an hour significantly impacts both the 90th and 100th percentile ETE since the trip generation dictates ETE (Section M.1). Public outreach could be considered to inform people within the EPZ to mobilize in a timely manner.

Increasing the shadow evacuation percent has minimal impact on ETE (Section M.2).

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.

Population growth results in more evacuating vehicles which could significantly increase ETE (Section M.3). Public outreach to inform 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.

Increasing the average household size (decreasing the total number of evacuating vehicles), has little impact on ETE (decreasing the 90th percentile ETE by at most 5 minutes) and no impact to the 100th percentile ETE, since trip generation within the EPZ dictates ETE (Appendix M.4). Thus, public outreach to inform people within the EPZ to evacuate as a family in a single vehicle would reduce the number of evacuating vehicles and could reduce the 90th percentile ETE.

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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 3 Hours 45 Minutes 2:30 3:55 4 Hours 45 Minutes (Base) 2:35 4:55 5 Hours 45 Minutes 3:30 5:55 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 2:30 4:55 14 4,086 2:30 4:55 20 (Base) 5,838 2:35 4:55 40 11,675 2:40 4:55 60 17,513 2:45 4:55 80 23,350 2:45 4:55 100 29,188 2:50 4:55 Table M3. ETE Variation with Population Change EPZ and 20% Population Change Shadow Permanent Base 148% 149% 150%

Resident Population 8,023 19,898 19,978 20,059 ETE (hrs:min) for the 90th Percentile Population Change Region Base 148% 149% 150%

2MILE 1:15 1:15 1:15 1:15 5MILE 2:45 2:45 2:45 2:45 FULL EPZ 2:45 3:10 3:10 3:15 ETE (hrs:min) for the 100th Percentile Population Change Region Base 148% 149% 150%

2MILE 1:45 1:45 1:45 1:45 5MILE 4:50 4:50 4:50 4:50 FULL EPZ 4:55 4:55 4:55 4:55 1

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 M4. ETE Results for Change in Average Household Size EPZ and 20% Base Case Sensitivity Case Shadow Average Household Size Average Household Size Permanent (2.40 people per household) (2.62 people per household)

Resident Population 8,023 people 7,350 people th ETE for the 90 Percentile Region Base Case Sensitivity Case 2MILE 1:15 1:15 5MILE 1:55 1:50 FULL EPZ 2:35 2:30 ETE for the 100th Percentile Region Base Case Sensitivity Case 2MILE 1:45 1:45 5MILE 4:50 4:50 FULL EPZ 4:55 4:55 South Texas Project Electric Generating Station M6 KLD Engineering, P.C.

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APPENDIX N ETE Criteria Checklist

N. ETE CRITERIA CHECKLIST Table N1. ETE Review Criteria Checklist Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 1.0 Introduction

a. The emergency planning zone (EPZ) and surrounding area is Yes Section 1.2 described.

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.

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.

1.1 Approach

a. The general approach is described in the report as outlined Yes Section 1.1, Section 1.3, Appendix D, in Section 1.1, Approach. Table 11, 1.2 Assumptions

a. Assumptions consistent with Table 12, General Yes Section 2 Assumptions, of NUREG/CR7002 are provided and include the basis to support use.

1.3 Scenario Development

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 Comments Analysis (Yes/No/NA) 1.4 Evacuation Planning Areas

a. A map of the EPZ with emergency response planning areas Yes Figure 31, Figure 61 (ERPAs) is included.

1.4.1 Keyhole Evacuation

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.

1.4.2 Staged Evacuation

a. The approach used in development of a staged evacuation is Yes Section 5.4.3, Section 7.2 discussed.

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.

2.0 Demand Estimation

a. Demand estimation is developed for the four population Yes Section 3 groups (permanent residents of the EPZ, transients, special facilities, and schools).

2.1 Permanent Residents and Transient Population

a. The U.S. Census is the source of the population values, or Yes Section 3.1 another credible source is provided.

b. The availability date of the census data is provided. Yes Section 3.1

c. Population values are adjusted as necessary for growth to N/A N/A 2020 Census used as the base reflect population estimates to the year of the ETE. year of the analysis South Texas Project Electric Generating Station N2 KLD Engineering, P.C.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

d. A sector diagram, similar to Figure 21, Population by Yes Figure 32 Sector, is included showing the population distribution for permanent residents.

2.1.1 Permanent Residents with Vehicles

a. The persons per vehicle value is between 1 and 3 or Yes Section 3.1, Appendix F justification is provided for other values.

2.1.2 Transient Population

a. A list of facilities that attract transient populations is Yes Section 3.3, Table E3 through Table E4 included, and peak and average attendance for these facilities is listed. The source of information used to develop attendance values is provided.

b. Major employers are listed. Yes Section 3.4, Table E2

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 and employee population by scenario - see Table 64.

d. The percentage of permanent residents assumed to be at Yes Section 3.3 and Section 3.4 facilities is estimated.

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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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

f. A sector diagram is included, similar to Figure 21, Yes Figure 36 (transients) and Figure 38 Population by Sector, is included showing the population (employees) distribution for the transient population.

2.2 Transit Dependent Permanent Residents

a. The methodology (e.g., surveys, registration programs) used Yes Section 3.6 to determine the number of transit dependent residents is discussed.

b. The State and local evacuation plans for transit dependent Yes Section 8.1 residents are used in the analysis.

c. The methodology used to determine the number of people N/A As per Matagorda County, no residents with disabilities and those with access and functional needs with access and/or functional needs are who may need assistance and do not reside in special registered within the EPZ.

facilities is provided. Data from local/county registration programs are used in the estimate.

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.

e. An estimate of the transit dependent population is provided. Yes Section 3.6, Table 37, Table 39

f. A summary table showing the total number of buses, Yes Table 310, 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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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 2.3 Special Facility Residents

a. Special facilities, including the type of facility, location, and N/A No medical facilities or correctional average population, are listed. Special facility staff is facilities exist within the EPZ included in the total special facility population.

b. The method of obtaining special facility data is discussed.

c. An estimate of the number and capacity of vehicles assumed available to support the evacuation of the facility is provided.

d. The logistics for mobilizing specially trained staff (e.g.,

medical support or security support for prisons, jails, and other correctional facilities) are discussed when appropriate.

2.4 Schools

a. A list of schools including name, location, student Yes Table 36, Table E1, Section 3.5 population, and transportation resources required to support the evacuation, is provided. The source of this information should be identified.

b. Transportation resources for elementary and middle schools Yes Section 3.5 are based on 100 percent of the school capacity.

c. The estimate of high school students who will use personal Yes Section 3.5 vehicle to evacuate is provided and a basis for the values used is given.

d. The need for return trips is identified. Yes Section 8.1 - no return trips are needed South Texas Project Electric Generating Station N5 KLD Engineering, P.C.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 2.5 Other Demand Estimate Considerations 2.5.1 Special Events

a. A complete list of special events is provided including Yes Section 3.7 information on the population, estimated duration, and season of the event.

b. The special event that encompasses the peak transient Yes Section 3.7 population is analyzed in the ETE.

c. The percentage of permanent residents attending the event Yes Section 3.7 is estimated.

2.5.2 Shadow Evacuation

a. A shadow evacuation of 20 percent is included consistent Yes Assumption 7 of Section 2.2, Figure 21 with the approach outlined in Section 2.5.2, Shadow and Figure 71, Section 3.2 Evacuation.

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.

c. The loading of the shadow evacuation onto the roadway Yes Section 5 - Table 58 (footnote) network is consistent with the trip generation time generated for the permanent resident population.

2.5.3 Background and Pass Through Traffic

a. The volume of background traffic and passthrough traffic is Yes Section 3.8 and Section 3.9 based on the average daytime traffic. Values may be reduced for nighttime scenarios.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

b. The method of reducing background and passthrough traffic Yes Section 2.2 - Assumptions 10 and 11 is described. Section 2.5 Section 3.8 and Section 3.9 Table 63 - External Through Traffic footnote

c. Passthrough traffic is assumed to have stopped entering the Yes Section 2.5, Section 3.8 EPZ about two (2) hours after the initial notification.

2.6 Summary of Demand Estimation

a. A summary table is provided that identifies the total Yes Table 39, Table 310, and Table 64 populations and total vehicles used in the analysis for permanent residents, transients, transit dependent residents, special facilities, schools, shadow population, and passthrough demand in each scenario.

3.0 Roadway Capacity

a. The method(s) used to assess roadway capacity is discussed. Yes Section 4 3.1 Roadway Characteristics

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.

b. Legible maps are provided that identify nodes and links of Yes Appendix K the 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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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 3.2 Model Approach

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.

b. Route assignment follows expected evacuation routes and Yes Appendix B and Appendix C traffic volumes.

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.

d. Dynamic traffic assignment models are described including Yes Appendix B and Appendix C calibration of the route assignment.

3.3 Intersection Control

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.

b. The use of signal cycle timing, including adjustments for Yes Section 4, Appendix G manned traffic control, is discussed.

3.4 Adverse Weather

a. The adverse weather conditions are identified. Yes Assumption 2 and 3 of Section 2.6

b. The speed and capacity reduction factors identified in Table Yes Assumption 2 of Section 2.6, Table 22 31, Weather Capacity Factors, are used or a basis is provided for other values, as applicable to the model.

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 Assumption 4 of Section 2.6, Table 22; and assumptions for snow removal on streets and driveways snow is not considered for this site.

are identified, when applicable.

4.0 Development of Evacuation Times 4.1 Traffic Simulation Models

a. General information about the traffic simulation model used Yes Section 1.3, Table 13, Appendix B, in the analysis is provided. Appendix C

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.

analytical approach used.

4.2 Traffic Simulation Model Input

a. Traffic simulation model assumptions and a representative Yes Section 2, Appendix J set of model inputs are provided.

b. The number of origin nodes and method for distributing Yes Appendix J, Appendix C vehicles among the origin nodes are described.

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.

4.3 Trip Generation Time

a. The process used to develop trip generation times is Yes Section 5 identified.

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.

c. Data used to develop trip generation times are summarized. Yes Appendix F, Section 5 South Texas Project Electric Generating Station N9 KLD Engineering, P.C.

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d. The trip generation time for each population group is Yes Section 5 developed from sitespecific information.

e. The methods used to reduce uncertainty when developing Yes Appendix F, Section 5.4.2 trip generation times are discussed, if applicable.

4.3.1 Permanent Residents and Transient Population

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 commuters. Table 63 presents the of residents will need to return home before evacuating. percentage of households with returning commuters and the percentage of households either without returning commuters or with no commuters. Appendix F presents the percent households who will await the return of commuters.

Section 2.3, Assumption 4

b. The trip generation time accounts for the time and method Yes Section 5 to notify transients at various locations.

c. The trip generation time accounts for transients potentially Yes Section 5, Figure 51 returning to hotels before evacuating.

d. The effect of public transportation resources used during Yes Section 3.7 special events where a large number of transients are Public transportation is not provided expected is considered. and was therefore not considered.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 4.3.2 Transit Dependent Permanent Residents

a. If available, existing and approved plans and bus routes are N/A Established bus routes do not exist.

used in the ETE analysis. Basic bus routes were developed for the ETE analysis.

Section 8.1 under Evacuation of TransitDependent Population (Residents without access to a vehicle)

b. The means of evacuating ambulatory and nonambulatory Yes Section 8.1 - Evacuation of Transit residents are discussed. Dependent Population (Residents without access to a vehicle)

As per Matagorda County, no residents with access and/or functional needs are registered within the EPZ.

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.

d. The estimated time for transit dependent residents to Yes Section 8.1 under Evacuation of prepare and then travel to a bus pickup point, including the TransitDependent People (Residents expected means of travel to the pickup point, is described. without access to a vehicle)

e. The number of bus stops and time needed to load Yes Section 8.1, Table 84 and Table 85 passengers are discussed.

f. A map of bus routes is included. Yes Figure 102

g. The trip generation time for nonambulatory persons N/A As per Matagorda County, no residents including the time to mobilize ambulances or special with access and/or functional needs are vehicles, time to drive to the home of residents, time to load, registered within the EPZ.

and time to drive out of the EPZ, is provided.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

h. Information is provided to support analysis of return trips, if N/A Section 8.1 no return trips are needed necessary.

4.3.3 Special Facilities

a. Information on evacuation logistics and mobilization times is N/A No medical or correctional facilities provided. exist within the EPZ

b. The logistics of evacuating wheelchair and bed bound residents are discussed.

c. Time for loading of residents is provided.

d. Information is provided that indicates whether the evacuation can be completed in a single trip or if additional trips are needed.

e. Discussion is provided on whether special facility residents are expected to pass through the reception center before being evacuated to their final destination.

f. Supporting information is provided to quantify the time elements for each trip, including destinations if return trips are needed.

4.3.4 Schools

a. Information on evacuation logistics and mobilization times is Yes Section 2.4, Section 8.1, Table 82 and provided. Table 83

b. Time for loading of students is provided. Yes Section 2.4, Section 8.1, Table 82 and Table 83

c. Information is provided that indicates whether the Yes Section 8.1 evacuation can be completed in a single trip or if additional trips are needed.

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d. If used, reception centers should be identified. A discussion Yes Section 8.1, Table 103 is provided on whether students are expected to pass through the reception center before being evacuated to their final destination.

e. Supporting information is provided to quantify the time Yes Section 8.1, Table 82 and Table 83 elements for each trip, including destinations if return trips are needed.

4.4 Stochastic Model Runs

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 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 dynamic traffic assignment model to seeds for evacuation of the full EPZ under Summer, obtain the "average" (stable) network Midweek, 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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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 4.5 Model Boundaries

a. The method used to establish the simulation model Yes Section 4.5 boundaries is discussed.

b. Significant capacity reductions or population centers that Yes Section 4.5 may influence the ETE and that are located beyond the evacuation area or shadow region are identified and included in the model, if needed.

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.

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

3. Number of vehicles arriving at each destination node. based on the time the last

4. Total number and percentage of evacuee vehicles not vehicle exits the evacuation exiting the EPZ. zone

5. A plot that provides both the mobilization curve and 5. Figures J2 through J13 (one evacuation curve identifying the cumulative percentage plot for each scenario of evacuees who have mobilized and exited the EPZ. considered)

6. Average speed for each major evacuation route that exits 6. Table J3 the EPZ.

c. Color coded roadway maps are provided for various times Yes Figure 73 through Figure 76 (e.g., at 2, 4, 6 hrs.) during a full EPZ evacuation scenario, identifying areas where congestion exists.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 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.

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.

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, Section data is explained. 5.4.2 Table 72 - 100th percentile ETE for general population

d. Tables are provided for the 90 and 100 percent ETEs similar Yes Table 73 and Table 74 to Table 43, ETEs for a Staged Evacuation, and Table 44, ETEs for a Keyhole Evacuation.

e. ETEs are provided for the 100 percent evacuation of special Yes Section 8 facilities, transit dependent, and school populations.

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.

b. Adjustments or additions to the traffic control plan that Yes Section 9, Appendix G affect the ETE is provided.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 5.2 Enhancements in Evacuation Time

a. The results of assessments for enhancing evacuations are Yes Appendix M provided.

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 agencies at the final project meeting. Comments on the draft report were provided and were addressed in the final report.

There are no unresolved issues.

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.

5.4.1 Extreme Conditions

a. The updated ETE analysis reflects the impact of EPZ N/A This ETE is being updated as a result of conditions not adequately reflected in the scenario the availability of US Census Bureau variations. decennial census data.

5.5 Reception Centers and Congregate Care Center

a. A map of congregate care centers and reception centers is Yes Figure 103 provided.

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