ML12355A748

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Evacuation Time Estimate Study; Cover Through Section 4
ML12355A748
Person / Time
Site: Palo Verde  Arizona Public Service icon.png
Issue date: 12/31/2012
From:
KLD Engineering, PC
To:
Office of Nuclear Material Safety and Safeguards
References
Download: ML12355A748 (86)
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ENCLOSURE PALO VERDE NUCLEAR GENERATING STATION EVACUATION TIME ESTIMATE STUDY

KLD__ KLENGINEERINGPC Palo Verde Nuclear GeneratingStation Development of EvacuationTime Estimates Work performedfor Arizona PublicService, by:

KLD Engineering, P.C.

43 Corporate Drive Hauppauge, NY 11788 mailto:kweinischLkldcompanies.com December 2012 Final Report, Rev. 1 KLD TR -513

Table of Contents 1 INTRODUCTION .................................................................................................................................. 1-1 1.1 Overview of the ETE Process ...................................................................................................... 1-1 1.2 The Palo Verde Nuclear Generating Station Location ............................................................... 1-3 1.3 Prelim inary Activities ................................................................................................................. 1-5 1.4 Com parison w ith Prior ETE Study .............................................................................................. 1-9 2 STUDY ESTIM ATES AND ASSUM PTIONS ............................................................................................. 2-1 2.1 Data Estim ates ........................................................................................................................... 2-1 2.2 Study M ethodological Assum ptions .......................................................................................... 2-1 2.3 Study Assum ptions ..................................................................................................................... 2-5 3 DEM AND ESTIM ATION ....................................................................................................................... 3-1 3.1 Perm anent Residents ................................................................................................................. 3-2 3.2 Shadow Population .................................................................................................................... 3-8 3.3 Transient Population ................................................................................................................ 3-12 3.4 Em ployees ................................................................................................................................ 3-16 3.5 Total Dem and in Addition to Perm anent Population .............................................................. 3-20 3.6 Special Event ............................................................................................................................ 3-20 3.7 Sum m ary of Dem and ............................................................................................................... 3-22 4 ESTIM ATION OF HIGHW AY CAPACITY ................................................................................................ 4-1 4.1 Capacity Estim ations on Approaches to Intersections .............................................................. 4-2 4.2 Capacity Estim ation along Sections of Highway ....................................................................... 4-4 4.3 Application to the Palo Verde Nuclear Generating Station Study Area ..................................... 4-6 4.3.1 Two-Lane Roads ................................................................................................................. 4-6 4.3.2 M ulti-Lane Highway ........................................................................................................... 4-6 4.3.3 Freeways ............................................................................................................................ 4-7 4.3.4 Intersections ...................................................................................................................... 4-8 4.4 Sim ulation and Capacity Estim ation .......................................................................................... 4-8 5 ESTIM ATION OF TRIP GENERATION TIM E.......................................................................................... 5-1 5.1 Background ................................................................................................................................ 5-1 5.2 Fundam ental Considerations ..................................................................................................... 5-3 5.3 Estim ated Tim e Distributions of Activities Preceding Event S ................................................... 5-6 5.4 Calculation of Trip Generation Tim e Distribution .................................................................... 5-11 5.4.1 Statistical Outliers ............................................................................................................ 5-12 5.4.2 Staged Evacuation Trip Generation ................................................................................. 5-15 5.4.3 Trip Generation Tim e for Recreational Areas .................................................................. 5-17 6 DEM AND ESTIM ATION FOR EVACUATION SCENARIOS ..................................................................... 6-1 7 GENERAL POPULATION EVACUATION TIM E ESTIM ATES (ETE) .......................................................... 7-1 7.1 Voluntary Evacuation and Shadow Evacuation ......................................................................... 7-1 7.2 Staged Evacuation ...................................................................................................................... 7-1 7.3 Patterns of Traffic Congestion during Evacuation ..................................................................... 7-2 7.4 Evacuation Rates ........................................................................................................................ 7-3 Palo Verde i KLD Engineering, P.C.

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7.5 Evacuation Tim e Estim ate (ETE) Results .................................................................................... 7-4 7.6 Staged Evacuation Results ......................................................................................................... 7-5 7.7 Guidance on Using ETE Tables ................................................................................................... 7-6 8 TRANSIT-DEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES ........................... 8-1 8.1 Transit Dependent People Dem and Estim ate ............................................................................ 8-2 8.2 School Population - Transit Dem and ......................................................................................... 8-4 8.3 Evacuation Tim e Estim ates for Transit Dependent People ....................................................... 8-4 8.4 Special Needs Population ........................................................................................................... 8-9 9 TRAFFIC M ANAGEM ENT STRATEGY ............................................................................................. 9-1 10 EVACUATION RO UTES .................................................................................................................. 10-1 11 SURVEILLANCE OF EVACUATIO N O PERATIO NS ........................................................................... 11-1 12 CO NFIRM ATION TIM E.................................................................................................................. 12-1 List of Appendices A. GLOSSARY O F TRAFFIC ENGINEERING TERM S ............................................................................. A-1 B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL ................................................... B-1 C. DYNEV TRAFFIC SIM ULATION M ODEL ........................................................................................... C-1 C.1 M ethodology .............................................................................................................................. C-5 C.1.1 The Fundam ental Diagram ........................................................................................... C-5 C.1.2 The Sim ulation M odel .................................................................................................. C-5 C.1.3 Lane Assignm ent ......................................................................................................... C-13 C.2 Im plem entation ....................................................................................................................... C-13 C.2.1 Com putational Procedure ........................................................................................... C-13 C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD) .............................................. C-16 D. DETAILED DESCRIPTION O F STUDY PROCEDURE .......................................................................... D-1 E. SPECIAL FACILITY DATA ...................................................................................................................... E-1 F. TELEPHONE SURVEY ........................................................................................................................... F-1 F.1 Introduction ............................................................................................................................... F-1 F.2 Survey Instrum ent and Sam pling Plan ....................................................................................... F-2 F.3 Survey Results ............................................................................................................................ F-3 F.3.1 Household Dem ographic Results ........................................................................................... F-3 F.3.2 Evacuation Response ............................................................................................................. F-8 F.3.3 Tim e Distribution Results ................................................................................................ F-10 F.4 Conclusions .............................................................................................................................. F-13 G. TRAFFIC M ANAGEM ENT PLAN .................................................................................................... G-1 G.1 Traffic Control Points ........................................................................................................... G-1 G.2 Access Control Points ........................................................................................................... G-1 H EVACUATIO N REGIONS ..................................................................................................................... H-1 Palo Verde ii KLD Engineering, P.C.

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J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM ................................. J-1 K. EVACUATION ROADW AY NETW ORK .............................................................................................. K-1 L. SECTO R BO UNDA RIES ........................................................................................................................ L-1 M. EVACUATION SENSITIVITY STUDIES ......................................................................................... M -1 M.1 Effect of Changes in Trip Generation Times ........................................................................ M-1 M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate ................. M-2 M.3 Effect of Changes in EPZ Resident Population ......................................................................... M-3 N. ETE CRITERIA CH ECKLIST ................................................................................................................... N-1 Note: Appendix I intentionallyskipped Palo Verde iii KLD Engineering, P.C.

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List of Figures Figure 1-1. Palo Verde Nuclear Generating Station Location ................................................................... 1-4 Figure 1-2. PVNGS Link-Node Analysis Network ....................................................................................... 1-7 Figure 2-1. Voluntary Evacuation Methodology ....................................................................................... 2-4 Figure 3-1. Palo Verde EPZ ........................................................................................................................ 3-3 Figure 3-2. Permanent Resident Population by Sector ............................................................................. 3-6 Figure 3-3. Permanent Resident Vehicles by Sector ................................................................................. 3-7 Figure 3-4. Shadow Population by Sector ............................................................................................... 3-10 Figure 3-5. Shadow Vehicles by Sector ................................................................................................... 3-11 Figure 3-6. Transient Population by Sector ............................................................................................. 3-14 Figure 3-7. Transient Vehicles by Sector ................................................................................................. 3-15 Figure 3-8. Employee Population by Sector ............................................................................................ 3-18 Figure 3-9. Employee Vehicles by Sector ................................................................................................ 3-19 Figure 4-1. Fundamental Diagrams ......................................................................................................... 4-10 Figure 5-1. Events and Activities Preceding the Evacuation Trip .............................................................. 5-5 Figure 5-2. Evacuation Mobilization Activities ........................................................................................ 5-10 Figure 5-3. Comparison of Data Distribution and Normal Distribution ....................................................... 5-14 Figure 5-4. Comparison of Trip Generation Distributions ....................................................................... 5-19 Figure 5-5. Comparison of Staged and Un-staged Trip Generation Distributions in the 2 to 5 Mile Region ........................................................................................................................................... 5-21 Figure 6-1. Palo Verde EPZ Sectors ........................................................................................................... 6-5 Figure 7-1. Voluntary Evacuation Methodology ..................................................................................... 7-20 Figure 7-2. Palo Verde Shadow Region ................................................................................................... 7-21 Figure 7-3. Congestion Patterns at 30 Minutes after the Advisory to Evacuate .................................... 7-22 Figure 7-4. Congestion Patterns at 1 Hour after the Advisory to Evacuate ............................................ 7-23 Figure 7-5. Congestion Patterns at 1 Hour 10 Minutes after the Advisory to Evacuate ......................... 7-24 Figure 7-6. Congestion Patterns at 1 Hour 40 Minutes after the Advisory to Evacuate ......................... 7-25 Figure 7-7. Evacuation Time Estimates - Scenario 1 for Region R03 ...................................................... 7-26 Figure 7-8. Evacuation Time Estimates - Scenario 2 for Region R03 ...................................................... 7-26 Figure 7-9. Evacuation Time Estimates - Scenario 3 for Region R03 ...................................................... 7-27 Figure 7-10. Evacuation Time Estimates - Scenario 4 for Region R03 .................................................... 7-27 Figure 7-11. Evacuation Time Estimates - Scenario 5 for Region R03 .................................................... 7-28 Figure 7-12. Evacuation Time Estimates - Scenario 6 for Region R03 .................................................... 7-28 Figure 7-13. Evacuation Time Estimates - Scenario 7 for Region R03 .................................................... 7-29 Figure 7-14. Evacuation Time Estimates - Scenario 8 for Region R03 .................................................... 7-29 Figure 7-15. Evacuation Time Estimates - Scenario 9 for Region R03 .................................................... 7-30 Figure 7-16. Evacuation Time Estimates - Scenario 10 for Region R03 .................................................. 7-30 Figure 7-17. Evacuation Time Estimates - Scenario 11 for Region R03 .................................................. 7-31 Figure 7-18. Evacuation Time Estimates - Scenario 12 for Region R03 .................................................. 7-31 Figure 8-1. Chronology of Transit Evacuation Operations ...................................................................... 8-10 Figure 8-2. Transit-Dependent Bus Routes ............................................................................................. 8-11 Figure 10-1. Reception and Care Centers ............................................................................................... 10-2 Figure 10-2. Major Evacuation Routes .................................................................................................... 10-3 Figure B-1. Flow Diagram of Simulation-DTRAD Interface .................................................................... B-5 Figure C-1. Representative Analysis Network ........................................................................................... C-4 Figure C-2. Fundamental Diagrams ........................................................................................................... C-6 Palo Verde iv KLD Engineering, P.C.

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Figure C-3. A UNIT Problem Configuration with t, > 0 .............................................................................. C-7 Figure C-4. Flow of Simulation Processing (See Glossary: Table C-3) .............................................. C-i5 Figure D-1. Flow Diagram of Activities ..................................................................................................... D-5 Figure E-1. Schools within the EPZ.; ......................................................................................................... E-4 Figure E-2. M ajor Em ployers within the EPZ ............................................................................................. E-5 Figure E-3. Recreational Areas within the EPZ .......................................................................................... E-6 Figure E-4. Lodging within the EPZ ............................................................................................................ E-7 Figure F-i. Household Size in the EPZ ....................................................................................................... F-4 Figure F-2. Household Vehicle Availability .................................................................................... ............ F-4 Figure F-3. Vehicle Availability - 1 to 5 Person Households ...................................................................... F-5 Figure F-4. Vehicle Availability - 6 to 9+ Person Households: ............................................................. F-5 Figure F-5. Household Ridesharing Preference ......................................................................................... F-6 Figure F-6. Com m uters in Households in the EPZ ..................................................................................... F-7 Figure F-7. M odes of Travel in the EPZ ..................................................................................................... F-8 Figure F-8. Num ber of Vehicles Used, for Evacuation ............................................................................... F-9 Figure F-9. Households Evacuating with Pets ........................................................................................... F-9 Figure F-10. Time Required to Prepare to Leave W ork/School .......................................................... F-11 Figure F-11. W ork to Home Travel Time ........................................................................................... F-11 Figure F-12. Time to Prepare Home for Evacuation ................................................................................ F-12 Figure G-1. Traffic and Access Control Points for the PVNGS Site ........................................................... G-2 Figure H-1. Region R01 ............................................................................................................................. H-4 Figure H-2. Region R02 ............................................................................................................................. H-5 Figure H-3. Region R03 ............................................................................................................................. H-6 Figure H-4. Region R04 ............................................................................................................................. H-7 Figure H-5. Region R05 ............................................................................................................................. H-8 Figure H-6. Region R06 ............................................................................................................................. H-9 Figure H-7. Region R07 ........................................................................................................................... H-iO Figure H-8. Region R08 ........................................................................................................................... H-11 Figure H-9. Region R09 ....................... .................................................................................................... H-12 Figure H-iO. Region RiO ......................................................................................................................... H-13 Figure H-11. Region R11 ......................................................................................................................... H-14 Figure H-i2. Region R22 ......................................................................................................................... H-15 Figure H-13. Region R13 ......................................................................................................................... H-16 Figure H-i4. Region R14 ......................................................................................................................... H-17 Figure H-15. Region R15 ......................................................................................................................... H-18 Figure H-16. Region R16 .......................................................................................................................... H-19 Figure H-i7. Region R17 ......................................................................................................................... H-20 Figure H-18. Region R18 ......................................................................................................................... H-21 Figure H-19. Region R19 ......................................................................................................................... H-22 Figure H-20. Region R20 ......................................................................................................................... H-23 Figure H-21. Region R21 ......................................................................................................................... H-24 Figure H-22. Region R22 ......................................................................................................................... H-25 Figure H-23. Region R23 ......................................................................................................................... H-26 Figure H-24. Region R24 ......................................................................................................................... H-27 Figure H-25. Region R25 ......................................................................................................................... H-28 Figure H-26. Region R26 ......................................................................................................................... H-29 Figure H-27. Region R27 ......................................................................................................................... H-30 Palo Verde v KLD Engineering, P.C.

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Figure H-28. Region R28 ......................................................................................................................... H-31 Figure H-29. Region R29 ......................................................................................................................... H-32 Figure H-30. Region R30 ......................................................................................................................... H-33 Figure H-31. Region R31 ......................................................................................................................... H-34 Figure H-32. Region R32 ......................................................................................................................... H-35 Figure H-33. Region R33 ......................................................................................................................... H-36 Figure H-34. Region R34 .................................................................... ..................................................... H-37 Figure H-35. Region R35 ............................................................................................................. a........... H-38 Figure H-36. Region R36 ............................................................................................. .... ..... . ..... H-39 Figure H-37. Region R37 ......................................................................................................................... H-40 Figure H-38. Region R38 ................................................................................. I........................................ H-41 Figure H-39. Region R39............................... .......................................................................................... H-42 Figure H-40. Region R40 ......................................................................................................................... H-43 Figure H-41. Region R41 ......................................................................................................................... H-44 Figure H-42. Region R42 ............................... ........................................................................................... H-45 Figure H-43. Region R43 ......................................................................................................................... H-46 Figure H-44. Region R44 .......................................................................................................................... H-47 Figure H-45. Region R45 ......................................................................................................................... H-48 Figure H-46. Region R46 ......................................................................................................................... H-49 Figure H-47. Region R47 ......................................................................................................................... H-50 Figure H-48. Region R48 ......................................................................................................................... H-51 Figure H-49. Region R49 ......................................................................................................................... H-52 Figure H-50. Region R50 ......................................................................................................................... H-53 Figure H-51. Region R51 ......................................................................................................................... H-54 Figure H-52. Region R52 ............................... .......................................................................................... H-55 Figure J-1. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1) ...... J-8 Figure J-2. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2) ............................... J-8 Figure J-3. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3) ...... J-9 Figure J-4. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4) .......................... J-9 Figure J-5. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5) .............................................................................................................................................. J-10 Figure J-6. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6) .............. J-10 Figure J-7. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7) ............................... J-11 Figure J-8. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 8) ...... J-11 Figure 1-9. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 9) ............................... J-12 Figure J-10.. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 10) ............................................................................................................................................ J-12 Figure J-11. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather, Special Event (Scenario 11) ............................................................................................................................................ J-13 Figure J-12. ETE and Trip Generation: Summer, Midweek, Midday Good Weather, Roadway Impact (Scenario 12 ............................................................................................................................................. J-13 Figure K-1. Palo Verde Nuclear Generating Station Link-Node Analysis Network .................................... K-2 Figure K-2. Link-Node Analysis Netw ork - Grid 1 ..................................................................................... K-3 Figure K-3. Link-Node Analysis Network- Grid 2 .................................... K-4 Figure K-4. Link-Node Analysis Netw ork- Grid 3 ............................................................................... K-5 Figure K-5. Link-Node Analysis Netw ork - Grid 4 ..................................................................................... K-6 Figure K-6. Link-Node Analysis Netw ork - Grid 5 ..................................................................................... K-7 Palo Verde vi KLD Engineering, P.C.

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Figure K-7. Link-Node Analysis Network - Grid 6 ............................................................................... K-8 Figure K-8. Link-Node Analysis Netw ork - Grid 7 ..................................................................................... K-9 Figure K-9. Link-Node Analysis Network - Grid 8 ............................................................................ K-10 Figure K-10. Link-Node Analysis Network - Grid 9 ............................................................................ K-11 Figure K-11. Link-Node Analysis Network - Grid 10 ............................................................................... K-12 Figure K-12. Link-Node Analysis Network- Grid 11 ............................................................................... K-13 Figure K-13. Link-Node Analysis Network - Grid 12 ........................... I.................................................. K-14 Figure K-14. Link-Node Analysis Network - Grid 13 .......................................................................... K-15 FigureK-15. Link-Node Analysis Network - Grid 14 .................................. K-16 FigureK-16. Link-Node Analysis Network - Grid 15 .......................................................................... K-17 Figure K-17. Link-Node Analysis Network- Grid 16 .......................................................................... K-18 Figure K-18. Link-Node Analysis Network- Grid 17 .................................. K-19 Figure L-1. PV NGS Sectors ......................................................................................................................... L-1 Palo Verde vii KLD Engineering, P.C.

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List of Tables Table 1-1. Stakeholder Interaction ........................................................................................................... 1-1 Table 1-2. Highw ay Characteristics ........................................................................................................... 1-5 Table 1-3. ETE Study Com parisons ............................................................................................................ 1-9 Table 2-1. Evacuation Scenario Definitions ............................................................................................... 2-3 Table 2-2. Model Adjustment for Adverse Weather ................................................................................. 2-7 Table 3-1. EPZ Permanent Resident Population ....................................................................................... 3-4 Table 3-2. Permanent Resident Population and Vehicles by Sector ......................................................... 3-5 Table 3-3. Shadow Population Growth Rate .............................................................................................. 3-8 Table 3-4. Shadow Population and Vehicles by Sector ............................................................................. 3-9 Table 3-5. Summary of Transients and Transient Vehicles ..................................................................... 3-13 Table 3-6. Summary of Non-EPZ Resident Employees and Employee Vehicles ...................................... 3-17 Table 3-7. Palo Verde EPZ External Traffic .............................................................................................. 3-21 Table 3-8. Summary of Population Demand ........................................................................................... 3-23 Table 3-9. Summary of Vehicle Demand ................................................................................................. 3-24 Table 5-1. Event Sequence for Evacuation Activities ................................................................................ 5-3 Table 5-2. Time Distribution for Notifying the Public ............................................................................... 5-6 Table 5-3. Time Distribution for Employees to Prepare to Leave Work ................................................... 5-7 Table 5-4. Time Distribution for Commuters to Travel Home ............................................................ 5-8 Table 5-5. Time Distribution for Population to Prepare to Evacuate ....................................................... 5-9 Table 5-7. Mapping Distributions to Events ............................................................................................ 5-11 Table 5-8. Description of the Distributions ............................................................................................. 5-12 Table 5-9. Trip Generation Histograms for the EPZ Population for Un-staged Evacuation .................... 5-18 Table 5-10. Trip Generation Histograms for the EPZ Population for Staged Evacuation ....................... 5-20 Table 6-1. Description of Evacuation Regions ........................................................................................... 6-3 Table 6-2. Evacuation Scenario Definitions ............................................................................................... 6-6 Table 6-3. Percent of Population Groups Evacuating for Various Scenarios ............................................ 6-7 Table 6-4. Vehicle Estim ates by Scenario .................................................................................................. 6-8 Table 7-1. Time to Clear the Indicated Area of 90 Percent of the Affected Population ........................... 7-8 Table 7-2. Time to Clear the Indicated Area of 100 Percent of the Affected Population ....................... 7-11 Table 7-3. Time to Clear 90 Percent of the 2-Mile Area within the Indicated Region ............................ 7-14 Table 7-4. Time to Clear 100 Percent of the 2-Mile Area within the Indicated Region .......................... 7-16 Table 7-5. Description of Evacuation Regions ......................................................................................... 7-18 Table 8-1. Transit-Dependent Population Estimates .............................................................................. 8-12 Table 8-2. School Population Demand Estimates ................................................................................... 8-13 Table 8-3. School Reception and Care Centers ....................................................................................... 8-13 Table 8-4. Summary of Transportation Resources .................................................................................. 8-13 Table 8-5. Bus Route Descriptions .......................................................................................................... 8-14 Table 8-6. School Evacuation Time Estimates - Good Weather .............................................................. 8-15 Table 8-7. School Evacuation Time Estimates - Rain ............................................................................... 8-15 Table 8-8. Summary of Transit-Dependent Bus Routes .......................................................................... 8-16 Table 8-9. Transit-Dependent Evacuation Time Estimates - Good Weather .......................................... 8-16 Table 8-10. Transit-Dependent Evacuation Time Estimates - Rain ......................................................... 8-17 Table 8-11. Access and Functional Needs Population Evacuation Time Estimates ................................ 8-17 Table 12-1. Estimated Number of Telephone Calls Required for Confirmation of Evacuation .............. 12-2 Table A-1. Glossary of Traffic Engineering Terms ............................................................................... A-1 Palo Verde viii KLD Engineering, P.C.

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Table C-i. Selected Measures of Effectiveness Output by DYNEV II ........................................................ C-2 Table C-2. Input Requirements for the DYNEV II Model ................................ C-3 Table C-3 . Glo ssary .................................................................................................................................... C-8 Table E-1. Schools w ithin the EPZ ............................................................................................................. E-2 Table E-2. M ajor Em ployers w ithin the EPZ .............................................................................................. E-2 Table E-3. Recreational Attractions within the EPZ .................................................................................. E-3 Table E-4. Lodging Facilities w ithin the EPZ .............................................................................................. E-3 Table F-1. Palo Verde Telephone Survey Sam pling Plan ........................................................................... F-2 Table H-1. Percent of Sector Population Evacuating for Each Region ..................................................... H-2 Table J-1. Characteristics of the Four Signalized Intersections ................................................................. J-3 Table J-2. Sam ple Sim ulation M odel Input ............................................................................................... J-4 Table J-3. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03) ........................... J-5 Table J-4. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Sce n a rio 1) ................................................................................................................................................. J-6 Table J-5. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 ......................... J-7 Table K-i. Evacuation Roadway Network Characteristics ...................................................................... K-20 Table K-2. Nodes in the Link-Node Analysis !Network which are Controlled .......................................... K-36 Table M-1. Evacuation Time Estimates for Trip Generation Sensitivity Study .................................. M-1 Table M-2. Evacuation Time Estimates for Shadow Sensitivity Study ................................................... M-2 Table M -3. ETE Variation w ith Population Change ................................................................................. M -4 Table N-i. ETE Review Criteria Checklist ............................................................................................. N-1 Palo Verde ix 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 Palo Verde Nuclear Generating Station (PVNGS) located in Maricopa County, AZ. ETE are part of the required planning basis and provide Arizona Public Service Company (APS) and State and local governments with site-specific information needed for Protective Action decision-making:

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

" Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR-7002, November 2011.

" Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG-0654/FEMA-REP-1, Rev. 1, November 1980.

" Development of Evacuation Time Estimates for Nuclear Power Plants, NUREG/CR-6863, January 2005.

" 10CFR50, Appendix E - "Emergency Planning and Preparedness for Production and Utilization Facilities" Overview of Proiect Activities This project began in February 2012 and extended over a period of 5 months. The major activities performed are briefly described in chronological sequence:

" Attended "kick-off" meetings with APS personnel and emergency management personnel representing state and county governments.

" Accessed U.S. Census Bureau data files for the year 2010 as well as population data collected by Maricopa County. Studied Geographical Information Systems (GIS) maps of the area in the vicinity of the PVNGS, then conducted a detailed field survey of the highway network.

" Synthesized this information to create an analysis network representing the highway system topology and capacities within the Emergency Planning Zone (EPZ), plus a Shadow Region covering the region between the EPZ boundary and 15 miles radially from the plant.

  • Designed and sponsored a telephone 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.

" Data collection forms (provided to the OROs at the kickoff meeting) were returned with data pertaining to employment, transients, and schools in Maricopa County. Telephone Palo Verde ES-1 KLD Engineering. P.C.

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calls to specific facilities supplemented the data provided.

" The traffic demand and trip-generation rates of evacuating vehicles were estimated from the gathered data. The trip generation rates reflected the estimated mobilization time (i.e., the time required by evacuees to prepare for the evacuation trip) computed using the results of the telephone survey of EPZ residents.

" Following federal guidelines, the EPZ is subdivided into 145 Sectors. These sectors are then grouped within circular areas or "keyhole" configurations (circles plus radial sectors) that define a total of 52 Evacuation Regions.

" The time-varying 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 involving an outage at the plant was considered. One roadway impact scenario was considered wherein a single lane was closed on Interstate 10 eastbound for the duration of the evacuation.

  • Staged evacuation was considered for those regions wherein the 2 mile radius and sectors downwind to 5 miles were evacuated. '

" A rapidly escalating accident at the PVNGS that quickly assumes the status of General Emergency such that the Advisory to Evacuate is virtually coincident with the siren alert, and no early protective actions have been implemented.

" While an unlikely accident scenario, this planning basis will yield ETE, measured as the elapsed time from the Advisory to Evacuate 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 reception and care centers 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 ride-share with relatives, friends or neighbors, or be evacuated by buses provided as specified in the county evacuation plan. Separate ETE are calculated for the transit-dependent evacuees, and for access and functional needs population.

Computation of ETE A total of 624 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 52 Evacuation Regions to evacuate from that Region, under the circumstances defined for one of the 12 Evacuation Scenarios (52 x 12 = 624). Separate ETE are calculated for transit-dependent Palo Verde ES-2 KLD Engineering, P.C.

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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 Advisory to Evacuate 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% of the population within the EPZ but outside the impacted region, will elect to "voluntarily" evacuate. In addition, 20% of the population in the Shadow Region will also elect to evacuate. These voluntary evacuees could impede those who are evacuating from within the impacted region. The impedance that could be caused by voluntary evacuees is considered in the computation of ETE for the impacted region.

Staged evacuation is considered wherein those people within the 2-mile region evacuate immediately, while those beyond 2 miles, but within the EPZ, shelter-in-place. Once 90% of the 2-mile region is evacuated, those people beyond 2 miles begin to evacuate. As per federal guidance, 20% of people beyond 2 miles will evacuate (non-compliance) even though they are advised to shelter-in-place.

The computational procedure is outlined as follows:

" A link-node 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 9 0 th percentile ETE have been identified as the values that should be considered when making protective action decisions because the 1 0 0 th 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/CR-7002.

The use of a public outreach (information) program to emphasize the need for evacuees to minimize the time needed to prepare to evacuate (secure the home, assemble needed clothes, medicines, etc.) should also be considered.

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Evacuation Time Estimate Rev. 1

Traffic Management This study references the comprehensive traffic management plan provided by Maricopa County. Due to the limited traffic congestion within the EPZ, no additional traffic or access control measures have been identified as a result of this study.

Selected Results A compilation of selected information is presented on the following pages in the form of Figures and Tables extracted fr6m the body of the report; these are described below.

" Figure 6-1 displays a map of the PVNGS EPZ showing the layout of the 145 Sectors that comprise, in aggregate, the EPZ.

" Table 3-1 presents the estimates of permanent resident population in each sector based on 2011 population data provided my Maricopa County.

" Table 6-1 defines each of the 52 Evacuation Regions in terms of their respective groups of Sectors.

" Table 6-2 lists the Evacuation Scenarios.

" Tables 7-1 and 7-2 are compilations of ETE. 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 sectors within the EPZ and from the Shadow Region.

  • Tables 7-3 and 7-4 present ETE for the 2-mile region for un-staged and staged evacuations for the 9 0 th and 1 0 0 th percentiles, respectively.

" Table 8-6 presents ETE for the schoolchildren in good weather.

  • Table 8-9 presents ETE for the transit-dependent population in good weather.

" Figure H-8 presents an example of an Evacuation Region (Region R08) to be evacuated under the circumstances defined in Table 6-1. Maps of all regions are provided in Appendix H.

Conclusions

  • General population ETE were computed for 624 unique cases - a combination of 52 unique Evacuation Regions and 12 unique Evacuation Scenarios. Table 7-1 and Table 7-2 document these ETE for the 90th and 100th percentiles. These ETE range from 1:20 (hr:min) to 2:20 at the 90th percentile.
  • Inspection of Table 7-1 and Table 7-2 indicates that the ETE for the 100th percentile are significantly longer than those for the 90th percentile. This is the result of the long trip generation "tail". As these stragglers mobilize, the aggregate rate of egress slows since many vehicles have already left the EPZ. Towards the end of the process, relatively few evacuation routes service the remaining demand. See Figures 7-7 through 7-18.
  • Inspection of Table 7-3 and Table 7-4 indicates that a staged evacuation provides no benefits to evacuees from within the 2 mile region (compare Regions R02, R04 through R19 with Regions R36 through R52, respectively, in Tables 7-1 and 7-2). See Section 7.6 Palo Verde ES-4 KLD Engineering, P.C.

Evacuation Time Estimate Rev. I

for additional discussion.

  • Comparison of Scenarios 6 (winter, midweek, midday) and 11 (winter, midweek, midday) in Table 7-2 indicates that the special event (outage at PVNGS) has a significant impact on the 9 0 th percentile ETE for the 2-mile region (Region R01) and keyhole regions with wind from the north. The additional employee vehicles increase ETE by up to 55 minutes. See Section 7.5 for additional discussion.
  • Comparison of Scenarios 1 and 12 in Table 7-1 indicates that the roadway closure - one lane eastbound on 1-10 from the interchange with S Wintersburg Rd (Exit 98) to the interchange with State Highway 85 (Exit 112) has no material impact on the 9 0 th or 1 0 0 th percentile ETE. Sufficient reserve highway capacity mitigates the impacts of the capacity reduction considered. Also, the ramps to 1-10 are the bottlenecks, not the mainline of the roadway. See Section 7.5 for additional discussion.

" There is minimal traffic congestion within the EPZ. 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 40 minutes after the Advisory to Evacuate. See Section 7.3 and Figures 7-3 through 7-6.

  • Separate ETE were computed for schools, transit-dependent persons and access and functional needs persons. The average single-wave ETE for these facilities are less than or comparable to the general population ETE at the 9 0 th percentile. See Section 8.

" Table 8-5 indicates that there are enough buses and wheelchair buses available to evacuate the transit-dependent and access and functional special needs populations within the EPZ in a single wave.

" The general population ETE at the 9 0 th percentile is insensitive to reductions in the base trip generation time of 5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> due to the traffic congestion along the plant access road.

The general population ETE at the 1 0 0 th percentile, however, closely mirrors trip generation time. See Table M-1.

" The general population ETE is insensitive to the voluntary evacuation of vehicles in the Shadow Region (tripling the shadow evacuation percentage does not increase the 9 0 th percentile ETE). See Table M-2.

  • An increase in permanent resident population of 170% or more, or a decrease in population of 50% or more results in ETE changes which meet the NRC criteria for updating ETE between decennial Censuses. See Section M.3.

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Figure 6-1. PVNGS EPZ Sectors Palo Verde ES-6 KLD Engineering, P.C.

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Table 3-1. EPZ Permanent Resident Population Secto 2000 Pouain 201 Poultin I1-Mile Ring 0 41 A 327 1,714 B 551 1,566 C 333 1,493 D 598 2,939 E 398 1,120 F 286 923 G 332 475 H 67 157 J 5 30 K 4 7 L 7 60 M 21 94 N 0 21 P 30 0 Q 59 590 R 351 1,244 EPZ Population Growth: 270.26%

1 www.census.gov - 2000 U.S. Census Data 2 Maricopa County Palo Verde Population Survey - Residents, December 2011 Palo Verde ES-7 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 1

Table 6-1. Description of Evacuation Regions Sector B C D E F H IJ K L M N P Q I R D1 2Mile Radiu FIS Full EPZ Wind Direction G H J K L M N P Q R Regon From: 2-515-1012-515-iD 2-515-1012-5 SI 255-102-55-102-5 5-10 5-10 2-5 2SSW2-515-10 2-515-1-0 R04 S SSW R05 SW ROS WSW W

ROB WNW R09 NW R10 NNW R11 N R13 NNE R14 NE RIS ENE R16 E R17 ESE - -

RIB

=Ri SE SSE 11111 III LLM I 11541 III I Sectorto W rniles Evactiate 2-Mile Radius and DownvAnd Wind _______ _______

_______ _______ sector _ __ __ _

Direction From:

S SSW SW R20 WSW R26 W

R22 WNW R24 NW R25 NNW R26 N NNE NE ENE R32 E ESE R34 SE R35 SSE I I I I I I I I I I I I ihEI~hiiu~iI~hi Set.,(s) SheLterI.-PIac J-L E Palo Verde ES-8 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 1

.4 C--I KAII D.AI C.'-- .4. C.. - - I a . _I f__M - - s, en acu nwn - es Wind Spefto KI M N p Q Direction I A B C D E I FF El G H J K I LL M N P Oa R 2-1SI

-inZ5I012-Sl 5-101S-1012-51l 2-SI S-212S 201 2-Si S-2012-51 5-201 2-SIS-ii2051ZSl -21 ZS012-SIsil S2051s-i2-515-2012-51 S-iol 2-SI 5-201 2-S51S-20 Region From:

R36 5-Mile Radius PYN

-m R37 R38 R39 M~O S

SSW SW I

WSW R41 W R42 WNW R43 NW R4 NNW R45 N R46 NNE R47 NE R48 ENE

,49 E RSO ESE R52 SE Sector1s) Ehhhlheh-hII;hIIE Palo Verde ES-9 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 1

Table 6-2. Evacuation Scenario Definitions 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 Weekend Evening Good None 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 Weekend Evening Good None 11 Winter Midweek Midday Good Outage at PVNGS Roadway Impact - Lane 12 Summer Midweek Midday Good Closure on 1-10 Eastbound 3 Winter assumes that school is in session (also applies to spring and autumn). Summer assumes that school is not in session.

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Table 7-1. Time to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek weekend Eire Weekend Midweek WeekendEPZ Weekend Midweek Midweek Midday Midday Evening Midday Midday Evening Midday Midday Region Good l 2ood0 2:n 2oo5 2ood5 2: i2ood: Weather Rood (1:35 2:1c2a1 2oadw2: Region a1n Scnrio: (1:2112) Weather Weather 1(3) 1:35 Weather 1(5) (:6)

Weather 11720 RIn RIn 10)35 91:3 Weather 1:1)

Event (1:2)

Impact Scnrio:

Entire 2-Mile Region, 5-Mile Region, and EPZ RO 120o :2 1:35 " 1:35 1:5 12 :0 :5 13 :5o:0 12 0 R02 2:10 2:10 2:15 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:20 2:10 R02 R03 2:10 2:15 2:00 2:00 2:10 2:10 2:10 2:00 2:00 2:10 2:20 2:10 R03 2-Mile Region and Keyhole to 5 Miles R04 1:55 1:55 2:10 2:10 2:10 1:55 1:55 2:10 2:10 2:10 2:15 1:55 R04 ROS 2:00 2:00 2:10 2:15 2:10 2:00 2:00 2:10 2:10 2:10 2:20 2.00 R05 R06 1:55 1:55 2:10 2:10 2:10 1:55 1:55 2:10 2:10 2:10 2:15 1:55 R06 R07 1:55 1:55 2:10 2:10 2:10 1:55 1:55 2:10 2:10 2:10 2:15 1:55 R07 RO 1:50 1:50 2:10 2:10 2:10 1:50 1:50 2:10 2:10 2:10 2:15 1:50 ROB R09 1:40 1:45 2:05 2:05 2:05 1:40 1:40 2:05 2:05 2:05 2:15 1:40 R09 RIO 1:30 1:30 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:15 1:30 RiO R11 1:25 1:25 1:50 1:50 1:50 1:25 1:25 1:50 1:50 1:50 2:15 1:25 R11 R12 1:20 1:25 1:35 1:35 1:35 1:25 1:25 1:35 1:35 1:35 2:15 1:20 R12 R13 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:15 1:20 R13 R14 1:20 1:20 1:35 1:40 1:35 1:20 1:20 1:35 1:40 1:35 2:10 1:20 R14 RIS 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:00 1:20 RILS R16 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:00 1:20 R16 R17 1:30 1:30 1:55 1:55 1:55 1:30 1:30 1:55 1:55 1:55 2:00 1:30 R17 R18 1:45 1:45 2:05 2:05 2:05 1:45 1:45 2:05 2:05 2:05 2:15 1:45 R18 R19 1:45 1:45 2:05 2:10 2:05 1:45 1:45 2:05 2:10 2:05 2:15 1:45 R19 Palo Verde ES-11 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 1

Summer Summer Summer Winter Winter Winter Winter 'Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend Weekend Weekend Midweek Midweek

-cenrio: - 2) -3) -4) (6--5) ) -7) -- -,,(Scenrio Midday Midday Evening Midday Midday Evening Midday Midday Rain Rooo ain Good Good Good Good Special R n Weather Weather Roadway Region Weather Weather Rain Weather Weather Event Impact 2-Mile Region and Keyhole to EPZ Boundary R21 1:55 1:55 1:40 1:40 2:05 1:50 1:50 1:40 1:40 2:05 2:15 1:55 R21 R23 2:00 2:00 1:55 1:55 2:10 2:00 2:00 1:55 1:55 2:10 2:15 2:05 R23 R25 2:00 2:00 2:10 2:15 2:10 2:00 2:00 2:10 2:15 2:10 2:20 2:00 R25 R27 1:30 1:35 2:05 2:05 2:05 1:30 1:35 2:05 2:05 2:05 2:20 1:30 R27 128 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:15 1:20 pas R129 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:15 1:20 R29 R30 1:20 1:20 1:45 1:45 1:45 1:20 1:20 1:45 1:45 1:45 2:10 1:20 R30 R33 1:30 1:30 1:25 1:25 1:55 1:30 1:30 1:25 1:25 1:40 2:10 1:30 R33 R35 1:45 1:45 1:35 1:35 1:55 1:45 1:45 1:35 1:35 1:50 2:10 1:45 R35 Palo Verde ES-12 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend IWeekend Midweek Weekend Weekend Weekend Midweek Midweek nario: -1 -2 -3) -4) - -6) -)

Midday Midday Evening Midday Midday Evening Midday Midday SRooad WeatheWeather i 1ood1Ran eatherWeat Wehr Good Good Weather Rain Good Rain Good Special Roadway Region I Weather Weather Event Impact Staged Evacuation Mile Region and Keyhole to 5 Miles R36 2:10 2:10 2:15 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:20 2:10 R3 R37 2:05 2:05 2:10 2:10 2:10 2:05 2:05 2:10 2:10 2:10 2:15 2:05 R37 R*8 205 2:05 2:10 2:15 2:10 205 2:05 2:10 2:15 2:10 2:20 2:05R R39 2:00 2:05 2:10 2:10 2:10 2:00 2:00 2:10 2:10 2:10 2:15 2:00 R39 R4 2:05 2:05 2:10 2:10 2:10 205 2:05 2:10 2:10 2:10 2:15 2:05 R40 R41 1:55 1:55 2:10 2:10 2:10 1:55 1:55 2:10 2:10 2:10 2:15 1:55 R41 R42 1:55 1:55 2:05 2:05 2:05 1:55 155 2:05 2:05 2:05 2:15 1:55 R42 R43 1:50 1:50 2:05 2:05 2:05 1:50 1:50 2:05 2:05 2:05 2:15 1:50 R43 R44 1:30 1:35 2:00 2:00 2:00 1:30 1:30 2:00 2:00 2:00 2:15 1:35 R44 R45 1:25 1:25 1:55 1:55 1:55 1:25 1:25 1:55 1:55 1:55 2:15 1:25 R45 R4 1:25 1:25 1:55 1:55 1:55 1:25 1s25 1:55 1:55 1:55 2:15 1:25 R4 R47 1:20 1:20 1:55 1:55 1:55 1:20 1:25 1:55 1:55 1:55 2:15 1:20 R47 R48 1:20 1:20 1:55 1:55 1:55 1:20 1:25 1:55 1:55 1:55 2:15 1:20 R48 R49 1:20 1:20 1:55 1:55 1:55 1:20 1:25 1:55 1:55 1:55 2:15 1:20 R49 R50 1:45 1:50 2:05 2:05 2:05 1:45 1:45 2:05 2:~05 2:05 2:15 1:45 RSO R51 2:00 2:00 2:10 2:10 2:10 2:00 2:00 2:10 2:10 2:10 2:15 2:00 R51 RS2 2:00 2:00 2:10 2:10 2:10 2:00 2:00 2:10 2:10 2:10 2:15 2:00 RS2 KLD Engineering, P.C.

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Table 7-2. Time to Clear the Indicated Area of 100 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Weekend Mdek Midweek Weekend MdekMidweek Midweek Weekend Weekend Midday Midday Evening Midday Midday Evening Midday Midday -

Region 5:05 Weather 5:05 5:05 Weather 5:05 Ran 5:0d Wahr 5 Weathr 5:05 RIn 55 Wahr 5:i 5:05 Wahr Event 50 Ro5:05 Impact Ion Entire 2-Mile Region, 5-Mile Region, and EPZ R04 5:05 5:0 5:05 5:05 5:05 5:05 5:05 5:05 5:0 5 5:05 5:05 5:05 R01 R02 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R02 2-Mile Region and Keyhole to 5 Miles R04 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R04 RO3 5:05 5:105 5:105 5:105 5:105 5:105 5:105 5:105 5:105 5:105 5:105 5:105 R03 R0S 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R06 R.. 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R..

R07 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R07 R10 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 Ri0 R10 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R102 R124 :0 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R12 R16 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R16 R18 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R18 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Midweek Weekend Weekend Midweek Midweek

[,'*Scenario: (1) (2)] (3) (4) (5) (6)] [(7) (8) [(9) (10) [ 1)i (12) Scenai o:

Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good I Rain i Good ] ain Good Special Roadway Region r Rainh RaneodaoothRinerai I Weather,_Rain Weather r Weather We W Ran Weather Event Impact 2-Mile Region and Keyhole to EPZ Boundary P20 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R21 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R21 R22 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R23 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R23 R24 5:10 5:10 5:10 5:10 5:10 5:10 5:0 5:10 5:10 5:10 5:10 5:10 R24 R25 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R25 R26 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 S:10 2 R27 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R27 R28 5:10 5:10 5:10 510 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:0 R28 R29 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R29 R30 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R R31 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R31 R32 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R32 R33 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R33 R34 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R34 R35 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 5:10 R35 KLD Engineering, P.C.

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Evacuation Time Estimate Rev. 1

Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Meekend Weekend Midweek Weekend Weekend Weekend Midweek Midweek nario: -] -2) (1 -3) -4) - -) -6)

Midday Midday Evening Midday Midday Evening Midday Midday ood Reaion RoodI Good Good Gain Good i Good Special Roadway Region Weather Rain Weather Rain Weather Weather In Weather In Weather Event Impact Staged Evacuation Mile Region and Keyhole to 5 Miles R36 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R36 R37 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R37 R38 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R38 R43 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R43 R40 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R40 R41 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R41 R42 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R42 R45 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R45 R43 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 5:05 R43 Palo Verde ES-16 KLD Engineering, P.C.

Evacuation Time Estimate Rev. 1

Table 7-3. Time to Clear 90 Percent of the 2-Mile Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend Weekend Weekend Midweek Midweek Midday Midday Evening Midday Midday Evening Midday Midday Region Good Good Rain Goodo in Good Good Special Roadway Region Weather Weather Weather Weather Weather I Weather Event Impact Unstaged Evacuation Mile Region and Keyhole to 5-Miles Rol 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R01 R02 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R02 R4 1:20 1:20 1:.35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R04 R05 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R05 R06 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R06 R07 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R07 ROB 1:20 1:20 135 135 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 RO R09 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R09 R10 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R10 Rll 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 Rll R1 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R1 R13 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R13 R14 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R14 RIS 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 RIS RI6 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R16 R17 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R17 R18 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 Rlg R19 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R19 KLD Engineering, P.C.

Palo Verde ES-17 ES-17 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend kind Weekend Midweek Midweek

-a - -3) -] (- -- (9) (] ( -7)

Smai Midday Midday Evening Midday Midday Evening Midday Midday ood Reaioi Rin oo Rain Good Good Good ood special Roadway Region Weather Weather Weather Weather Rain Weather I Weather Event Impact Staged Evacuation Mile Region and Keyhole to S-Miles R37 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R37 R37 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R37 R38 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R38 R39 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R43 R40 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R40 R41 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R41 R42 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:3S 2:10 1:20 R42 R43 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R43 R44 1:20.. 1:20.1....1:35 .1:.5.1:20.:20.1..5..:35.120 R45 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R45 R51 1:20 1:20 1:35 1:35 1:35 1:20 1:20 1:35 1:35 1:35 2:10 1:20 R51 Palo Verde ES-18 KLD Engineering, P.C.

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Table 7-4. Time to Clear 100 Percent of the 2-Mile Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend Weekend Weekend Midweek .,Midweek Midday Midday Evening Midday Midday Evening Evening Midday Region Good God Roodn I GoodI Good Special Roadway Region Weather Weather Weather Weather I Weather Weather Event Impact Unstaged Evacuation Mile Region and Keyhole to 5-Miles R01 5:00 5:00 5:00 5:00 5:00 500 5:00 5:00 5:00 5:00 5:00 5:00 Rol R02 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R02 R04 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R04 ROS 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R05 R06 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R06 R07 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R07 ROB 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R08 R09 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R09 RIO 5:00 5:00 5:0 5:00 5:00 50 5:00 5:00 5:00 5:00 5:00 5:00 Rll 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 Rll R12 5:00 5:~00 5:00 5:00 5:00 5:00 5:00 5:00 5:'00 5:00 5:00 5:00 R12 R13 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R13 R14 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R14 RlS 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R15 R16 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R16 R17 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R17 RI7 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 RI1 R19 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R19 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Widweed Weekend Midweek Weekend Weekend Weekend Midweek Midweek

- [()-6) (2) (3 (4) - () - ) -11) -12) -- -io ena Midday Midday Evening Midday Midday Evening Evening Midday Region Good i Good Good Good Good I Good Special Roadway Region Weather Rn Weather Gd W WeatheWeather, Rain Weather Rain Weather Event Impact Staged Evacuation Mile Region and Keyhole to S-Miles R37 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R37 R38 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R38 R39 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R39 R40 5:00 5.00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R40 R41 5:00 5:00 500 500 500 500 500 500 5:00 5:00 5:00 5:00 R41 R45 5:00 5:00 5:00 5:00 5:00 5.00 5:00 5:00 5:00 5:00 5:00 5:00 R45 R47 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 5:00 R47 R49 R46.. 5:00 5:0 5:00 50 5:00

0 5:00 50 5:00
0 5:00 50 500
0 5:00 S0 5:00

...... 5:00 5:00 5:0 5:00

0 R49 4

RS1 5:00 5:00 5:00 5:00 5:00 5:00 500 5:00 5:00 5:00 5:00 5:00 R51 Palo Verde ES-20 KLD Engineering, P.C.

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Table 8-6. School Evacuation Time Estimates - Good Weather KLD Engineering, P.C.

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Table 8-9. Transit-Dependent Evacuation Time Estimates - Good Weather Palo Verde ES-22 KLD Engineering, P.C.

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Figure H-8. Region ROB Palo Verde ES-23 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 Palo Verde Nuclear Generating Station (PVNGS),

located in Maricopa County, Arizona. ETE provide State and local governments with site-specific information needed for Protective Action decision-making.

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

  • Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR-7002, November 2011.

Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG 0654/FEMA REP 1, Rev. 1, November 1980.

Analysis of Techniques for Estimating Evacuation Times for Emergency Planning Zones, NUREG/CR 1745, November 1980.

Development of Evacuation Time Estimates for Nuclear Power Plants, NUREG/CR-6863, January 2005.

The work effort reported herein was supported and guided by local stakeholders who contributed suggestions, critiques, and the local knowledge base required. Table 1-1 presents a summary of stakeholders and interactions.

Table 1-1. Stakeholder Interaction IStkh le Arizona Public Service (APS)

Ia~eo Stkh le Ineaci Meetings to define data requirements and to set Aup contacts with local government agencies Meetings to define data requirements. Obtain Maricopa County Department of Emergency local emergency plans, special facility data, and Management (DEM) residential data.

Arizona Department of Emergency Management Obtain state emergency plan and traffic counts (DEM)

Local and State Police Agencies Obtain existing traffic management plans 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 Arizona Public Service.

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b. Attended meetings with emergency planners from Arizona DEM and Maricopa County DEM to identify issues to be addressed and resources available.
c. Conducted a detailed field survey of the highway system and of area traffic conditions within the Emergency Planning Zone (EPZ) and Shadow Region.
d. Obtained demographic data from the 2010 census, Maricopa County DEM, and Arizona DEM.
e. Conducted a random sample telephone survey of EPZ residents.
f. Conducted a data collection effort to identify and describe schools, recreational areas, motels, major employers, transportation providers, and other important information.
2. Estimated distributions of Trip Generation times representing the time required by various population groups (permanent residents, employees, and transients) to prepare (mobilize) for the evacuation trip. These estimates are primarily based upon the random sample telephone 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 Control Points (TCP) located within the EPZ.
5. Used existing Sectors to define Evacuation Regions. The EPZ is partitioned into 145 sectors by compass direction and radial distance from the plant. "Regions" are groups of contiguous Sectors 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 "key-hole section" within the EPZ as recommended by NUREG/CR-7002.
6. Estimated demand for transit-dependent persons at school and at home.
7. Prepared the input streams for the DYNEV II system.
a. Estimated the evacuation traffic demand, based on the available information derived from Census data, and from data provided by local and state agencies, Arizona Public Service and from the telephone survey.
b. Applied the procedures specified in the 2010 Highway Capacity Manual (HCM')

to the data acquired during the field survey, to estimate the capacity of all highway segments comprising the evacuation routes.

c. Developed the link-node representation of the evacuation network, which is 1 Highway Capacity Manual (HCM 2010), Transportation Research Board, National Research Council, 2010.

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used as the basis for the computer analysis that calculates the ETE.

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 PVNGS.
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/CR-7002.
10. Calculated the ETE for all transit activities including those for schools, for the transit-dependent population and for access and functional needs population.

1.2 The Palo Verde Nuclear Generating Station Location The PVNGS is located in Tonopah, Maricopa County, Arizona. The site is approximately 55 miles west of Phoenix, AZ. The EPZ is entirely within Maricopa County. Figure 1-1 displays the location of the plant relative to Phoenix, as well as the major roads in the area.

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Figure 1-1. Palo Verde Nuclear Generating Station Location Palo Verde 1-4 KLD Engineering, P.C.

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1.3 Preliminary Activities These activities are described below.

Field Surveys of the Highway Network 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 1-2:

Table 1-2. Highway Characteristics

  • Number of lanes 0 Posted speed
  • Lane width 0 Actual free speed
  • Shoulder type & width 0 Abutting land use
  • Interchange geometries 0 Control devices
  • Lane channelization & queuing 0 Intersection configuration (including capacity (including turn bays/lanes) roundabouts where applicable)
  • Geometrics: curves, grades (>4%) 0 Traffic signal type
  • Unusual characteristics: Narrow bridges, sharp curves, poor pavement, flood warning signs, inadequate delineations, toll booths, etc.

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 15-7 in the HCM 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 two-lane highways. Exhibit 15-30 in the HCM shows little sensitivity for the estimates of Service Volumes at Level of Service (LOS) E (near capacity), with respect to FFS, for two-lane highways.

The data from the audio and video recordings were used to create detailed geographical 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.

As documented on page 15-5 of the HCM 2010, the capacity of a two-lane highway is 1700 passenger cars per hour in one direction. For freeway sections, a value of 2250 vehicles per hour per lane is assigned, as per Exhibit 11-17 of the HCM 2010. The road survey has identified several segments which are characterized by adverse geometrics on two-lane 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 Exhibit 15-30. These links may be Palo Verde 1-5 KLD Engineering, P.C.

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identified by reviewing Appendix K. Link capacity is an input to DYNEV II which computes the ETE. Further discussion of roadway capacity is provided in Section 4 of this report.

Traffic signals are either pre-timed (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. TCPs at locations which have control devices are represented as actuated signals in the DYNEV II system.

If no detectors were observed, the signal control at the intersection was considered pre-timed, and detailed signal timings were gathered for several signal cycles. These signal timings were input to the DYNEV II system used to compute ETE, as per NUREG/CR-7002 guidance.

Figure 1-2 presents the link-node 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 1-2 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 were used to calibrate the analysis network.

Telephone Survey A telephone survey was undertaken to gather information needed for the evacuation study.

Appendix F presents the survey instrument, the procedures used and tabulations of data compiled from the survey returns.

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 transit-dependent 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.

Analytical Tools The DYNEV II System that was employed for this study is comprised of several integrated computer models. One of these is the DYNEV (DYnamic Network EVacuation) macroscopic simulation model, a new version of the IDYNEV model that was developed by KLD under contract with the Federal Emergency Management Agency (FEMA).

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Figure 1-2. PVNGS Link-Node Analysis Network KLD Engineering, P.C.

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DYNEV II consists of four sub-models:

" 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" (0) located within the analysis network, where evacuation trips are "generated" over time. This establishes a set of O-D tables.

" A Dynamic Traffic Assignment (DTA), model which assigrs trips to paths of travel (routes) which satisfy the O-D 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 such as LOS, vehicles discharged, average speed, and percent of vehicles evacuated, output by the DYNEV II System. 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, I-DYNEV, the following references are suggested:-

" NUREG/CR-4873 - Benchmark Study of the I-DYNEV Evacuation Time Estimate Computer Code

  • NUREG/CR-4874 - The Sensitivity of Evacuation Time Estimates to Changes in Input Parameters for the I-DYNEV 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.
  • Move traffic in directions that are generally outbound, relative to the location of the PVNGS.

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 Palo Verde 1-8 KLD Engineering, P.C.

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countermeasures may then be tested with the model.

1.4 Comparison with Prior ETE Study Table 1-3 presents a comparison of the present ETE study with the 2010 study. The major factors contributing to the differences between the ETE values obtained in this study and those of the previous study can be summarized as follows:

" An increase in permanent resident population.

" Vehicle occupancy and Trip-generation rates are based on the results of a telephone survey of EPZ residents.

6 Voluntary and shadow evacuations are considered.

S A macroscopic computerized model incorporating concepts from the HCM 2010 was used.

e More evacuating vehicles due to lower vehicle occupancy Table 1-3. ETE Study Comparisons To-ic Peius. td gT urn td Used data supplied by Maricopa Resident Population Data collected by Maricopa County; County; Basis Population = 11,565 Population = 12,474 The automobile occupancy factor was 2.90 persons/household, 1.46 Resident Population estimated at the national average of 2.5 evacuating vehicles/household persons per car. yielding: 1.99 persons/vehicle.

Employee estimates based on information provided about Employee Vehicle estimates for this population were major employers in EPZ. 1.08 Population based o1current figures provided by Palo employees per vehicle based on nVerde of 180 commuter vans, telephone survey results.

Employees = 2,715 Estimates based upon U.S.

Census data and the results of the telephone survey. A total of The Maricopa County Department of 455 people who do not have Emergency Management through return access to a vehicle, requiring 16 Transit-Dependent mail, telephone, personal visits, identifies buses to evacuate. An additional residents requiring special evacuation needs. 627 access and functional needs No number provided, persons needing special transportation to evacuate (525 require a bus, 102 require a wheelchair-accessible vehicle).

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II Toi rvosEEStudy Transient Population:

Curn E Sud Transient estimates based upon Transient The work force at PVNGS is the only information provided about Population significant transient population. transient attractions in EPZ.

See Employee Population above. Transients = 1,061 There aree currently cth ynnoschl special There are currently no special facilities fac Special Facilities located within the 10-mile facilities other than schools (see Population EPZ. below) located within the 1O-mile EPZ.

There are three schools located There are four schools listed in Appendix B within the 10-mile EPZ and one and each is equipped with onsite within the Shadow Region. Each transportation to facilitate evacuation, is equipped with onsite School Population School enrollment = 1,434 transportation to facilitate Staff = 177 evacuation.

Vehicles originating at schools = Not School enrollment = 1,410 provided Staff = 175 Buses = 25 Voluntary 20% of the population within the evacuation from EPZ, but not within the within EPZ in areas Not considered Evacuation Region outside region to be evacuated (see Figure 2-1) 20% of people outside of the EPZ Shadow Evacuation Not considered within the Shadow Region (see Figure 7-2)

Network Size Not Applicable 272 links; 194 nodes Field surveys conducted in Februry 2 oad an Assumptions for the analysis were obtained intersections were video Roadway Geometric from national averages, existing Arizona Data Department of Transportation studies for archived.

roadways, Federal Highway Administration manuals and personal observations. Road capacities based on 2010 HCM.

School Evacuation Not Specified Direct evacuation to designated Reception and Care Center.

50 percent of transit-dependent Ridesharing Not considered persons will evacuate with a I_ I neighbor or friend.

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ET StdCurn TSuy I oicPevos Based on residential telephone Preparation time is the time required for survey of specific pre-trip residents to prepare to evacuate their homes mobilization activities:

and property. Several variables can impact Residents with commuters this time including family size, time of day, returning leave between 30 and and family location. Preparation time is 300 minutes.

Trip Generation for estimated at 30 minutes through practical Residents without commuters Evacuation observation.

returning leave between 15 and 240 minutes.

Total decision time is made up of: Decision time (30 minutes), notification time (15 Employees and transients leave minutes), and preparation time (30 minutes) between 15 and 120 minutes.

= 75 minutes. All times measured from the Advisory to Evacuate.

Normal or Adverse. A speed of 50mph was Normal or Rain. The capacity Weather used for normal conditions and 30mph for and free flow speed of all links in adverse conditions. the network are reduced by 10%

in the event of rain Modeling None DYNEV II System -Version 4.0.8.0 Outage at PVNGS Special Events None considered Special Event Population = 1,560 additional employees 52 Regions (central sector wind 3 Sections x 2 scenarios (unhindered and direction and each adjacent Evacuation Cases advers = 6 scases sector technique used) and 12 Scenarios producing 624 unique cases.

ETE reported for unhindered for a full EPZ ETE reportedpu for 9 h and Ruth Evacuation rtime evacuation and adverse for a full EPZ preente bypRegion and Estimates Reporting evacuation. Results presented by Section. Scenario.

Winter, Midweek, Midday, Good Weather:

90th percentile: 2:10 Normal conditions: 165.9 minutes (2:46) 100th percentile: 5:10 Evacuation Time Estimates Adverse Conditions: 187.3 minutes (3:07) Winter, Midweek, Midday, Rain:

90th percentile: 2:10 1001h percentile: 5:10 1-11 1-11 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 Estimates

1. Population estimates are based upon 2011 data collected and provided by Maricopa County.
2. Estimates of employees who reside outside the EPZ and commute to work within the EPZ are based upon data obtained from surveys of major employers in the EPZ.
3. Population estimates at special facilities are based on available data from the county emergency management department and from phone calls to specific facilities.
4. Roadway capacity estimates are based on field surveys and the application of the Highway Capacity Manual 2010.
5. Population mobilization times are based on a statistical analysis of data acquired from a random sample telephone survey of EPZ residents (see Section 5 and Appendix F).
6. The relationship between resident population and evacuating vehicles is developed from the telephone survey. Average values of 2.90 persons per household and 1.46 evacuating vehicles per household are used. The relationship between persons and vehicles for transients and employees is as follows:
a. Employees: 1.08 employees per vehicle (telephone survey results) for all major employers.
b. Campgrounds and lodging: Assumed average household size of 2.90 people per campsite/room.

2.2 Study Methodological Assumptions

1. ETE are presented for the evacuation of the 90th and 100th percentiles of population for each Region and for each Scenario. The percentile ETE is defined as the elapsed time from the Advisory to Evacuate issued to a specific Region of the EPZ, to the time that Region is clear of the indicated percentile of evacuees. A Region is defined as a group of sectors that is issued an Advisory to Evacuate. A scenario is a combination of circumstances, including time of day, day of week, season, and weather conditions.
2. The ETE are computed and presented in tabular format and graphically, in a format compliant with NUREG/CR-7002.
3. Evacuation movements (paths of travel) are generally outbound relative to the plant to the extent permitted by the highway network. All major evacuation routes are used in the analysis.
4. Regions are defined by the underlying "keyhole" or circular configurations as specified in Section 1.4 of NUREG/CR-7002.
5. As indicated in Figure 2-2 of NUREG/CR-7002, 100% of people within the impacted "keyhole" evacuate. 20% of those people within the EPZ, not within the impacted Palo Verde 2-1 KLD Engineering, P.C.

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keyhole, will voluntarily evacuate. 20% of those people within the Shadow Region will voluntarily evacuate. See Figure 2-1 for a graphical representation of these evacuation percentages. Sensitivity studies explore the effect on ETE of increasing the percentage of voluntary evacuees in the Shadow Region (see Appendix M).

6. A total of 12 "Scenarios" representing different temporal variations (season, time of day, day of week) and weather conditions are considered. These Scenarios are outlined in Table 2-1.

7.*' Scenario 12 considers the closure of a single lane eastbound on Interstate-20 from the I interchange with Wintersburg Rd (Exit 98) to the end of the analysis-network at the interchange with State Highway 85 (Exit 112).

8. 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 new DYNEV II model incorporates the latest technology in traffic simulation and in dynamic traffic assignment. The DYNEV II System is used to compute ETE in this study.

1 Urbanik, T., et. al. Benchmark Study of the I-DYNEV Evacuation Time Estimate Computer Code, NUREG/CR-4873, Nuclear Regulatory Commission, June, 1988.

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Table 2-1. Evacuation Scenario Definitions 3 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None 5 Summer Midweek, 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 10 Winter Midweek, Evening Good None Weekend 11 Winter Midweek Midday Good Outage at PVNGS Roadway Impact Summer Midweek Midday Good - Lane Closure 12 on 1-10 Eastbound Palo Verde 2-3 KLD Engineering, P.C.

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Spz I I JKeybeb: 24AmsNO 85m

&ala ýOuuuiwd IKeybels:240O1s Rala10Mb.ODam~bw Uqad EwMMNui 2-Mm Rooma &£5anm Os..mi

  • PWu Leocsn aftiosm lb.b Evecu~da M0%Evasuatan 20% &*udew Evsa~lsU~wlls, sme EVacUal Figure 2-1. Voluntary Evacuation Methodology Palo Verde 2-4 KLD Engineering, P.C.

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2.3 Study Assumptions

1. The Planning Basis Assumption for the calculation of ETE is a rapidly escalating accident that requires evacuation, and includes the following:
a. Advisory to Evacuate is announced coincident with the siren notification.
b. Mobilization of the general population will commence within 15 minutes after siren notification.
c. ETE are measured relative to the Advisory to Evacuate.
2. It is assumed that everyone within the group of sectors forming a Region that is issued an Advisory to Evacuate will, in fact, respond and evacuate in general accord with the planned routes.
3. 61 percent of the households in the EPZ have at least 1 commuter; 42 percent of those households with commuters will await the return of a commuter before beginning their evacuation trip, based on the telephone survey results. Therefore 26 percent (61% x 42% = 26%) of EPZ households will await the return of a commuter, prior to beginning their evacuation trip.
4. The ETE will also include consideration of "through" (External-External) trips during the time that such traffic is permitted to enter the evacuated Region. "Normal" traffic flow is assumed to be present within the EPZ at the start of the emergency.
5. Access Control Points (ACP) will be staffed within approximately 45 minutes following the siren notifications, to divert traffic attempting to enter the EPZ. Earlier activation of ACP locations could delay returning commuters. It is assumed that no through traffic will enter the EPZ after this 45 minute time period.
6. Traffic Control Points (TCP) within the EPZ will be staffed over time, beginning at the Advisory to Evacuate. Their number and location will depend on the Region to be evacuated and resources available. The objectives of these TCP are:
a. Facilitate the movements of all (mostly evacuating) vehicles at the location.
b. Discourage inadvertent vehicle movements towards the plant.
c. Provide assurance and guidance to any traveler who is unsure of the appropriate actions or routing.
d. Act as local surveillance and communications center.
e. Provide information to the emergency operations center (EOC) as needed, based on direct observation or on information provided by travelers.

In calculating ETE, it is assumed that evacuees will drive safely, travel in directions identified in the plan, and obey all control devices and traffic guides.

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7. Buses will be used to transport those without access to private vehicles:
a. If schools are in session, transport (buses) will evacuate students directly to the designated reception and care centers (RCCs).
b. Transit-dependent general population will be evacuated to RCCs.
c. Schoolchildren, if school is in session, are given priority in assigning transit vehicles.
d. Bus mobilization time is considered in ETE calculations.
e. Analysis 6f the number of required round-trips ("waves") of evacuating transit vehicles iS presented.
f. Transport of transit-dependent evacuees from RCCs to congregate care centers is not considered in this study.
8. Provisions are made for evacuating the transit-dependent portion of the general population to RCCs by bus, based on the assumption that some of these people will ride-share with family, neighbors, and friends, thus reducing the demand for buses. We assume that the percentage of people who rideshare is 50 percent. This assumption is based upon reported experience for other emergencies2 , and on guidance in Section 2.2 of NUREG/CR-7002.
9. One type of adverse weather scenario is 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 weather-related reduction in the number of transients who may be present in the EPZ is assumed.

Adverse weather scenarios affect roadway capacity and the free flow highway speeds.

The factors applied for the ETE study are based on recent research on the effects of weather on roadway operations 3; the factors are shown in Table 2-2.

2 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 76% (Page 5-10).

3 Agarwal, M. et. AL. Impacts of Weather on Urban Freeway Traffic Flow Characteristics and Facility Capacity.

Proceedings of the 2005 Mid-Continent Transportation Research Symposium, August, 2005. The results of this paper are included as Exhibit 10-15 in the HCM 2010.

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10. School buses used to transport students are assumed to transport 70 students per bus for elementary schools and 50 students per bus for middle and high schools, based on discussions with county offices of emergency management. Transit buses used to transport the transit-dependent general population are assumed to transport 30 people per bus.

Table 2-2. Model Adjustment for Adverse Weather Rain 1 90% 1 90% No Effect

  • Adverse weather capacity and speed values are given as a percentage of good weather conditions. Roads are assumed to be passable.

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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 double-counting of vehicles.

Appendix E presents much of the source material for the population estimates. Our primary source of population data, 2011 data collected by Maricopa County, however, is not adequate for directly estimating some transient groups.

Throughout the year, vacationers and tourists enter the EPZ. These non-residents 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 double-counting people and vehicles must be addressed. For example, a resident who works within the EPZ could be counted as a resident and again as an employee.

Furthermore, the number of vehicles at a location depends on time of day. For example, hotel parking lots may be full at dawn and empty at noon. 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 Palo Verde EPZ indicates the need to identify three distinct groups:

" Permanent residents - people who are year round residents of the EPZ.

" Transients - people who reside outside of the EPZ who enter the area for a specific recreational purpose and then leave the area.

  • Employees - people who reside outside of the EPZ and commute to businesses 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 Sector and by polar coordinate representation (population rose).

The Palo Verde EPZ is subdivided into 145 Sectors. The EPZ is shown in Figure 3-1.

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3.1 Permanent Residents Permanent resident population estimates are based upon 2011 data collected by Maricopa County. The Maricopa County Department of Emergency Management (MCDEM) compiles and updates 10-mile Emergency Planning Zone (EPZ) population demographics annually. This information is derived from electric utility connects/disconnects, special surveys and information provided from the county planning department. MCDEM geo-codes the addresses which summarizes population by EPZ sector. This compiled information is provided to PVNGS who then revises the onsite Emergency Plan annually to include the updated demographics.

Table 3-1 provides the 2011 permanent resident population within the EPZ, by sector based on the 2011 data provided. The 2000 population data was estimated using U.S. Census data.

The average household size (2.90 persons/household - See Figure F-i) and the number of evacuating vehicles per household (1.46 vehicles/household - See Figure F-8) were adapted from the telephone survey results.

The year 2011 permanent resident population is divided by the average household size and then multiplied by the average number of evacuating vehicles per household in order to estimate number of vehicles. Permanent resident population and vehicle estimates are presented in Table 3-2. Figure 3-2 and Figure 3-3 present the permanent resident population and permanent resident vehicle estimates by sector and distance from PVNGS. This "rose" was constructed using GIS software.

It can be argued that this 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 percent of all households vacation for a two-week period over the summer.

" Assume these vacations, in aggregate, are uniformly dispersed over 10 weeks, i.e. 10 percent of the population is on vacation during each two-week interval.

" Assume half of these vacationers leave the area.

On this basis, the permanent resident population would be reduced by 5 percent in the summer and by a lesser amount in the off-season. Given the uncertainty in this estimate, we elected to apply no reductions in permanent resident population for the summer scenarios to account for residents who may be out of the area.

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Figure 3-1. Palo Verde EPZ KLD Engineering, P.C.

Palo Verde 3-3 3-3 KLD Engineering, P.C.

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Table 3-1. EPZ Permanent Resident Population Secto 2000 OLlain 201 PO.. Si 1-Mile Ring 0 41 3

A 327 1,714 B 551 1,566 C 333 1,493 D 598 2,939 E 398 1,120 F 286 923 G 332 475 H 67 157 J 5 30 K 4 7 L 7 60 M 21 94 N 0 21 P 30 0 Q 59 590 R 351 1,244 EPZ Population Growth: 270.26%

1 www.census.gov - 2000 U.S. Census Data 2 Maricopa County Palo Verde Population Survey- Residents, December 2011 3 Stage Stop RV Park is located in Sector A. The population at this facility is assumed to be included with the permanent resident population due to the large population reported within Sector A between 2 and 3 miles of the plant and presence of electrical hook-ups at the facility.

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Table 3-2. Permanent Resident Population and Vehicles by Sector l-Mile Ring 41 22 A3 1,714 863 B 1,566 788 C 1,493 752 D 2,939 1,481 E 1,120 564 F 923 465 G 475 240 H 157 79 J 30 15 K 7 4 L 60 31 M 94 49 N 21 11 P 0 0 Q 590 298 R 1,244 627 Palo Verde 3-5 KLD Engineering, P.C.

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N NNW F17__ NNE 0

WNW ENE 2 942

)

S0 W

I-E 0 1r 12 WSW 0 ' ESE 9,

-- SE F475

"- 0

- 10 Miles to EPZ Boundary Ssw I o S 157 N 30 Resident Population 23G 6 0 Miles subtotal by Ring Cumulative Total 0-1 41 41 11 0 1 -2 289 330 2 -3 669 999 00 0 3 -4 1,776 2,775 W 4-5 2,112 4,887 5- 6 96843 6 -7 923 7766 7-8 1,004 8,770 8-9 826 9,596 9 - 10 2,878 12,474 10 -EPZ 0 12,474 Inset Total: 12,474 0- 2 Miles S Figure 3-2. Permanent Resident Population by Sector Palo Verde 3-6 KLD Engineering, P.C.

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N NNW 863 NNE 3100 0 8 F77-WNW ENE WI ~0 WI E I-1 *0

10 56-4 465 WSW 0 , ESE7 490, 5= "

- 0

. 10 Miles to EPZ Boundary-I SSW -. 0o - - " SSE S - - N t- -15 Resident Vehicles Miles Subtotal by Ring Cumulative Total 0-1 22 22 1-2 146 168 2-3 338 506 3-4 896 1,402 W E 4-5 1,064 2,466 5-6 984 3,450 6-7 466 3,916 7-8 506 4,422 8-9 416 4,838 99-10 1,451 6,289 10-EPZ 0 6,289 Inset Total: 6f289 0 - 2 Miles S Figure 3-3. Permanent Resident Vehicles by Sector KLD Engineering, P.C.

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3.2 Shadow Population A portion of the population living outside the evacuation area extending to 15 miles radially from Palo Verde (in the Shadow Region) may elect to evacuate without having been instructed to do so. Based upon NUREG/CR-7002 guidance, it is assumed that 20 percent of the permanent resident population, based on U.S. Census Bureau data, in this Shadow Region will elect to evacuate.

Population estimates are based upon Census 2010 data. The estimates are created by cutting the census block polygons by the Shadow Region boundary. 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 what the population is within the EPZ. This methodology assumes that the population is evenly distributed across a census block. The 2010 Census data was then extrapolated to year 2011 using the compound growth formula. The compound growth rate was computed by comparing the 2000 Census and 2010 Census data, outlined in Table 3-3.

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 3-4, Figure 3-4 and Figure 3-5 present estimates of the shadow population and vehicles, by sector.

Table 3-3. Shadow Population Growth Rate 2000 3,639 2010 6,180 Population Growth Rate = (2010 Population)F2o01-2000

\2000 Populationi 2011 Population = 2010 Population x (1 + Population Growth Rate)

    • Growth rate used exclusively for extrapolating shadow population Palo Verde 3-8 KLD Engineering. P.C.

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Table 3-4. Shadow Population and Vehicles by Sector N 510 260 NNE 22 11 NE 2,718 1,372 ENE 2,590 1,311 E 2,790 1,414 ESE 421 214 SE 0 0 SSE 39 20 S 0 0 SSW 0 0 SW 2 1 WSW 3 2 W 0 0 WNW 111 58 NW 147 76 NNW 193 102 Palo Verde 3-9 KLD Engineering, P.C.

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N NNW 0 NNE 193 _______________22 IZ -i WNW ENE 2,590 12 0

w E 61 2.208 F2,79-01 0

WSW ESE SE SSW *-.L _

  • __J* SSE ~,EPZ Boundary to 11 Miles wS Shadow Population Miles S;ubtotal by Ring Cumulative Total EPZ - 11 2,392 2,392 11-12 1,080 3,472 12-13 2,101 5,573 13-14 1,705 7,278 14-15 2,268 9,546 Total: 9,546 Figure 3-4. Shadow Population by Sector Palo Verde 3-10 KLD Engineering, P.C.

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N NNW 260 NNE 102 WNW ENE 1311 0

w E 32 Z 1,114 r-T---1 1.414 0

wsw ESE wT- 2 SE

~ Boundary toll1 Miles SSw SSE ,EPZ s

Shadow Vehicles Miles Subtotal by Ring Cumulative Total EPZ- 11 1,218 1,218 11 -12 554 1,772 12 -13 1,062 2,834 13- 14 862 3,696 14- 15 1,145 4,841 Total: 4,841 Figure 3-5. Shadow Vehicles by Sector Palo Verde 3-11 KLD Engineering, P.C.

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3.3 Transient Population Transient population groups are defined as those people (who are not permanent residents, nor commuting employees) who enter the EPZ for a specific purpose (recreation, lodging).

Transients may spend less than one day or stay overnight at camping facilities, or motels. The Palo Verde EPZ has two facilities that attract transients:

  • Westward Motel
  • Saddle Mountain RV Resort A survey of Westward Motel was conducted to determine the number of rooms, percentage of occupied rooms at peak times, and the number of people and vehicles per room for each facility. This data was used to estimate the number of transients and evacuating vehicles at this facility. A total of 23 transients in 8 vehicles are assigned to the Westward Motel.

The Saddle Mountain RV Resort was surveyed to determine the number of campsites, peak occupancy, and the number of vehicles and people per campsite for each facility. This data was used to estimate the number of evacuating vehicles for transients at the RV park. A total of 1,038 transients and 700 vehicles are assigned to the Saddle Mountain RV Resort.

Appendix E summarizes the transient data that was estimated for the EPZ. Table E-3 presents the number of transients visiting recreational areas, while Table E-4 presents the number of transients at lodging facilities within the EPZ.

Table 3-5 presents transient population and transient vehicle estimates by Sector. Figure 3-6 and Figure 3-7 present these data by sector and distance from the plant.

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Table 3-5. Summary of Transients and Transient Vehicles Palo Verde 3-13 KLD Engineering, P.C.

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N NNW NNE E w--I 1 Ef S0 0 WNW I

I W

rno WSW 0 Ie

  • 0 SSW -0 r-n- S N 0-*

Transients Miles Subtotal by Ring Cumulative Total 0-1 0 0 1-2 0 0 2-3 0 0 3-4 0 0 W E 4-5 0 0 5-6 0 0 6-7 0 0 7-8 0 0 8-9 1,061 1,061 9-10 0 1,061 10 - EPZ 0 1,061 Inset Total: 1,061 0 - 2 Miles S Figure 3-6. Transient Population by Sector 3-14 3-14 KLD Engineering, P.C.

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N NNW NNE 708- j E --

0 1- 0- '

WNW E---- I I

w WSWo S0 SSW - - - _0 °- SSE - -

Eli-"- El N Transient Vehicles Miles Subtotal by. Ring Cumulative Total 0-1 0 0 1-2 0 0 2-3 0 0 3-4 0 0 W E 4-5 0 0 5-6 0 0 6-7 0 0 7-8 0 0 8-9 708 708 9-10 0 708 10-EPZ 0 708 Inset Total: 708 0 - 2 Miles S Figure 3-7. Transient Vehicles by Sector Palo Verde 3-15 KLD Engineering, P.C.

KLD Engineering, P.C.

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3.4 Employees Employees who work within the EPZ fall into two categories:

" Those who live and work in the EPZ

" Those who live outside of the EPZ and commute to jobs within the EPZ.

Those of the first category are already counted as part of the permanent resident population. To avoid double counting, we focus only on those employees commuting from outside the EPZ who will evacuate along with the permanent resident population.

Data provided by APS and Maricopa County were used to estimate the number of employees commuting into the EPZ.

In Table E-2, the Employees (Max Shift) are multiplied by the percent Non-EPZ factor to determine the number of employees who are not residents of the EPZ. A vehicle occupancy of 1.08 employees per vehicle obtained from the telephone survey (See Figure F-7) was used to determine the number of evacuating employee vehicles for all major employers.

Currently, 1,155 employees at PVNGS use a vanpool system consisting of 150 vans (a vehicle occupancy of 7.7 employees) based on information provided by APS. These employees are assumed to be traveling from outside the EPZ. The remaining 1,478 employees (2,633 - 1,155) evacuate in private vehicles with an occupancy of 1.08 employees per vehicle. Thus, a total of 2,633 employees and 1,519 vehicles were assigned to the plant.

Inmates from the Arizona State Prison are transported to Hickman Farms (located in Section F).

During max shift, there are 152 inmates working at Hickman Farms. These inmates would evacuate on buses. Assuming a capacity of 30 people per bus, 6 buses (12 vehicles) were considered at this facility. For this reason, the number of vehicles used in this study at this facility reflects the number of non-EPZ employees plus the 12 buses needed for the inmates.

Table 3-6 presents non-EPZ Resident employee and vehicle estimates by Sector. Figure 3-8 and Figure 3-9 present these data by sector.

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Table 3-6. Summary of Non-EPZ Resident Employees and Employee Vehicles Sectr Em loyes Em loye Vehcle 1-Mile Ring 2,3159 A 0 0 B 0 0 C 0 0 D 0 0 E 0 0 F 82 88 G 0 0 H 0 0 J 0 0 K 0 0 L 0 0 M 0 0 N 0 0 P 0 0 Q 0 0 R 0 0 Palo Verde 3-17 KLD Engineering, P.C.

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N NNW NNE

= o .- - - 0- 7 WNW ENE I

',E E w E 0

"I

' ESE Ews

, 0 0-. - Boundary SSW--- - SSE S 263 N Employees 0 EnTý Miles Subtotal by Ring Cumulative Total 0- 1 2,633 2,633 1 -2 0 2,633 2- 3 0 2,633 3 -4 0 2,633 W E 4 -5 0 2,633 5-6 0 2,633 6-7 82 2,715 7 -8 0 2,715 8 9 0 2,715 9 10 0 2,715 10 - EPZ 0 2,715 Inset Total: 2,715 0- 2 Miles S Figure 3-8. Employee Population by Sector Palo Verde 3-18 KLD Engineering, P.C.

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N NNW NNE

% 7

-- 0 0 -

WNW ENE L--I-I w I E 0

I I

mZ I

wsw 0 o ESE 0

10m- '

  • 0 Boundary SSW 0 m-s-S 11 N Employee Vehicles Miles Subtotal by Ring Cumulative Total 0-1 1,519 1,519 1-2 0 1,519 2-3 0 1,519 3-4 0 1,519 W 4-5 0 1,519 5-6 0 1,519 6-7 88 1,607 7-8 0 1,607 8-9 0 1,607 9-10 0 1,607 10 - EPZ 0 1,607 Inset Total: 1,607 0-2Miles S Figure 3-9. Employee Vehicles by Sector Palo Verde 3-19 KLD Engineering, P.C.

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3.5 Total Demand in Addition to Permanent Population Vehicles will be traveling through the EPZ (external-external trips) at the time of an accident.

After the Advisory to Evacuate is announced, these through-travelers will also evacuate. These through vehicles are assumed to travel on the major route traversing the EPZ 10. It is assumed that this traffic will continue to enter the EPZ during the first 45 minutes following the Advisory to Evacuate.

Average Annual Daily Traffic (AADT) data was obtained from the Arizona Department of Transportation to estimate the number of vehicles per hour on the aforementioned routes.

The AADT was multiplied by the K-Factor, 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 3 0 th highest hourly traffic volume of the year, measured in vehicles per hour (vph). The DHV is then multiplied by the D-Factor, 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 3-7, for each of the routes considered. The DDHV is then multiplied by 0.75 hours8.680556e-4 days <br />0.0208 hours <br />1.240079e-4 weeks <br />2.85375e-5 months <br /> (access control points - ACP -

are assumed to be activated at 45 minutes - 0.75 hours8.680556e-4 days <br />0.0208 hours <br />1.240079e-4 weeks <br />2.85375e-5 months <br /> - after the advisory to evacuate) to estimate the total number of external vehicles loaded on the analysis network. As indicated, there are 2,288 vehicles entering the EPZ as external-external 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.

3.6 Special Event One special event (Scenario 11) is considered for the ETE study - an outage at the plant.

Outages occur in March and October. Data obtained from APS emergency management personnel indicate there are 1,000 additional workers during an outage at peak times.

Additionally, there are approximately 800 contractors that are on site during an outage, of which 70% work during the day and 30% work at night. During max shift, there are a total of 1,560 additional employees at the PVNGS site. Using a vehicle occupancy factor of 1.08 obtained from the telephone survey, there are a total of 1,444 additional vehicles at the plant during an outage. The special event vehicle trips were generated utilizing the same mobilization distributions as employees.

Public transportation is not provided for this event and was not considered in the special event analysis.

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Table 3-7. Palo Verde EPZ External Traffic 8023 137 1-10 EB 28,500 0.107 0.5 1,525 1,144 80120 1-10 WB 28,500 0.107 0-.5 1,525 ,4 1SHSTrafficLog201O.xlsx, AZDOT 2 HCM 2010 Palo Verde KLD Engineering, P.C.

3-21 KLD Engineering, P.C.

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3.7 Summary of Demand A summary of population and vehicle demand is provided in Table 3-8 and Table 3-9, respectively. This summary includes all population groups described in this section. Additional population groups - transit-dependent and school population - are described in greater detail in Section 8. A total of 20,024 people and 11,942 vehicles are considered in this study.

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Table 3-8. Summary of Population Demand Ring A 1,714 41 0 0 678 0 0 2,433 B 1,566 107 0 0 0 0 0 1,673 C 1,493 32 0 0 0 0 0 1,525 D 2,939 64 0 0 0 0 0 3,003 E 1,120 55 0 0 0 0 0 1,175 F 923 59 0 82 282 0 0 1,346 G 475 46 0 0 0 0 0 521 H 157 23 0 0 0 0 0 180 J 30 0 0 0 0 0 0 30 K 7 18 0 0 0 0 0 25 L 60 5 0 0 0 0 0 65 M 94 0 0 0 0 0 0 94 N 21 0 0 0 0 0 0 21 P 0 0 0 0 0 0 0 0 Q 590 0 0 0 0 0 0 590 R 1,244 5 1,061 0 0 0 0 2,310 Shadow 0 0 0 0 450 1,909 0,359 NOTE: Shadow Population has been reduced to 20%. Refer to Figure 2-1 for additional information.

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Table 3-9. Summary of Vehicle Demand 22 0 0 1,519 0 0 0 1,541 Ring A 863 2 0 0 26 0 0 891 B 788 8 0 0 0 0 0 760 C 752 2 0 0 0 0 0 790 D 1,481 4 0 0 0 0 0 1,485 E 564 4 0 0 0 0 0 568 F 465 4 0 88 10 0 0 567 G 240 4 0 0 0 0 0 244 H 79 2 0 0 0 0 0 81 J 15 0 0 0 0 0 0 15 K 4 2 0 0 0 0 0 6 L 31 0 0 0 0 0 0 31 M 49 0 0 0 0 0 0 49 N 11 0 0 0 0 0 0 11 P 0 0 0 0 0 0 0 0 Q 298 0 0 0 0 0 0 298 R 627 0 708 0 0 0 0 1,335 Shadow 0 0 0 0 14 968 2,288 3,270 NOTE: Buses represented as two passenger vehicles. Refer to Section 8 for additional information.

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 2010 Highway Capacity Manual (HCM 2010).

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 free-flow and high-speed 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" (SV). Service volume 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 service volume at the upper bound of LOS E, only.

This distinction is illustrated in Exhibit 11-17 of the HCM 2010. 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 (rain, snow, fog, wind speed, ice)

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 (BFFS 1 ) according to Exhibit 15-7 of the HCM. Consequently, lane and shoulder widths at the narrowest points were observed during the road survey and these observations were recorded, but no detailed 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 vehicle's speedometer and observing local traffic, under free flow conditions. Capacity is estimated from the procedures of 1 A very rough estimate of BFFS might be taken as the posted speed limit plus 10 mph (HCM 2010 Page 15-15)

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the 2010 HCM. For example, HCM Exhibit 7-1(b) shows the sensitivity of Service Volume at the upper bound of LOS D to grade (capacity is the Service Volume at the upper bound of LOS E).

As discussed in Section 2.3, it is necessary to adjust capacity figures to represent the prevailing conditions during inclement weather. Based on limited empirical data, weather conditions such as rain reduce the values of free 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 2.3, 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 At-grade 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. The existing traffic management plans documented in the county emergency plans are extensive and were adopted without change.

The per-lane capacity of an approach to a signalized intersection can be expressed (simplistically) in the following form:

3600 G- L (3600 Qcap,rn M zhm) X Pm where:

Qcap,m = Capacity of a single lane of traffic on an approach, which executes Palo Verde 4-2 KLD Engineering, P.C.

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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, left-turn, right-turn, and diagonal.

The turn-movement-specific 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, hm = fm(hsat, F1 , F2 , ... )

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 , ---

The estimation of hm for specified values of hsat, F1 , F2 , ... is undertaken within the DYNEV II simulation model by a mathematical mcadel 2. The resulting values for hm always satisfy the condition:

hm > hsat 2Lieberman, 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 Palo Verde 4-3 KLD Engineering, P.C.

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That is, the turn-movement-specific 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 2010.

The above discussion is necessarily brief given the scope of this ETE report and the complexity of the subject of intersection capacity. In fact, Chapters 18, 19 and 20 in the HCM 2010 address this topic. The factors, F1, F2,..., influencing saturation flow rate are identified in equation (18-5) of the HCM 2010.

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 all-red time is assigned between signal phases, typically. If a signal is pre-timed, the yellow and all-red 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 service volume (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 4-1 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 service volume increases as demand volume and density increase, until the service volume 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 service volume) 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.

The value of VF can be expressed as:

VF = R x Capacity where:

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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 fall-off in the service flow rate when congestion occurs at "bottlenecks" or "choke points" on a freeway system. Zhang and Levinson 3 describe a research program that collected data from a computer-based surveillance system (loop detectors) installed on the Interstate Highway System, at 27 active bottlenecks in the twin cities metro area in Minnesota over a 7-week 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 nexta'nd also vary by day of week and time of day based upon local circumstances. The cited reference presents a mean QDF of 2,016 passenger cars per hour per lane (pcphpl). This figure compares with the nominal capacity estimate of 2,250 pcphpl estimated for the ETE and indicated in Appendix K for freeway links. The ratio of these two numbers is 0.896 which translates into a capacity reduction factor of 0.90.

Since the principal objective of evacuation time estimate 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 free-flow speeds and lane capacity. Exhibit 15-30 in the Highway Capacity Manual was referenced to estimate saturation flow rates. The impact of narrow lanes and shoulders on free-flow speed and on capacity is not material, particularly when flow is predominantly in one direction as is the case during an evacuation.

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 2010 HCM. The DYNEV II simulation model determines for each highway section, represented as a network link, whether its capacity would be limited by the "section-specific" service volume, VE, or by the intersection-specific capacity. For each link, the model selects the lower value of capacity.

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

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4.3 Application to the Palo Verde Nuclear Generating Station Study Area As part of the development of the link-node 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:

2010 Highway Capacity Manual (HCM)

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

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

  • Two-Lane roads: Local, State

" Multi-Lane Highways (at-grade)

" Freeways Each of these classifications will be discussed.

4.3.1 Two-Lane Roads Ref: HCM Chapter 15 Two lane roads comprise the majority of highways within the EPZ. The per-lane capacity of a two-lane highway is estimated at 1700 passenger cars per hour (pc/h). This estimate is essentially independent of the directional distribution of traffic volume except that, for extended distances, the two-way capacity will not exceed 3200 pc/h. The HCM procedures then estimate Level of Service (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 time-varying demand: capacity relations.

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

" Most sections of two-lane roads within the EPZ are classified as "Class I', with "level terrain"; some are "rolling terrain".

" "Class II" highways are mostly those within urban and suburban centers.

4.3.2 Multi-Lane Highway Ref: HCM Chapter 14 Exhibit 14-2 of the HCM 2010 presents a set of curves that indicate a per-lane capacity ranging from approximately 1900 to 2200 pc/h, for free-speeds of 45 to 60 mph, respectively. Based on observation, the multi-lane highways outside of urban areas within the EPZ service traffic with free-speeds in this range. The actual time-varying speeds computed by the simulation model reflect the demand: capacity relationship and the impact of control at intersections. A Palo Verde 4-6 KLD Engineering, P.C.

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conservative estimate of per-lane capacity of 1900 pc/h is adopted for this study for multi-lane highways outside of urban areas, as shown in Appendix K.

4.3.3 Freeways Ref: HCM Chapters 10, 11, 12, 13 Chapter 10 of the HCM 2010 describes a procedure for integrating the results obtained in Chapters 11, 12 and 13, which compute capacity and LOS for freeway components. Chapter 10 also presents a discussion of simulation models. The DYNEV II simulation model automatically performs this integration process.

Chapter 11 of the HCM 2010 presents procedures for estimating capacity and LOS for "Basic Freeway Segments". Exhibit 11-17 of the HCM 2010 presents capacity vs. free speed estimates, which are provided below.

FreeSpeed (mph): 55 60 65 70+

Per-Lane Capacity (pc/h): 2250 2300 2350 2400 The inputs to the simulation model are highway geometrics, free-speeds and capacity based on field observations. The simulation logic calculates actual time-varying speeds based on demand:

capacity relationships. A conservative estimate of per-lane capacity of 2250 pc/h is adopted for this study for freeways, as shown in -Appendix K.

Chapter 12 of the HCM 2010 presents procedures for estimating capacity, speed, density and LOS for freeway weaving sections. The simulation model contains logic that relates speed to demand volume: capacity ratio. The value of capacity obtained from the computational procedures detailed in Chapter 12 depends on the "Type" and geometrics of the weaving segment and on the "Volume Ratio" (ratio of weaving volume to total volume).

Chapter 13 of the HCM 2010 presents procedures for estimating capacities of ramps and of "merge" areas. There are three significant factors to the determination of capacity of a ramp-freeway junction: The capacity of the freeway immediately downstream of an on-ramp or immediately upstream of an off-ramp; the capacity of the ramp roadway; and the maximum flow rate entering the ramp influence area. In most cases, the freeway capacity is the controlling factor. Values of this merge area capacity are presented in Exhibit 13-8 of the HCM 2010, and depend on the number of freeway lanes and on the freeway free speed. Ramp capacity is presented in Exhibit 13-10 and is a function of the ramp free flow speed. The DYNEV II simulation model logic simulates the merging operations of the ramp and freeway traffic in accord with the procedures in Chapter 13 of the HCM 2010. If congestion results from an excess of demand relative to capacity, then the model allocates service appropriately to the two entering traffic streams and produces LOS F conditions (The HCM does not address LOS F explicitly).

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4.3.4 Intersections Ref: HCM Chapters 18, 19, 20, 21 Procedures for estimating capacity and LOS for approaches to intersections are presented in Chapter 18 (signalized intersections), Chapters 19, 20 (un-signalized intersections) and Chapter 21 (roundabouts). The complexity of these computations is indicated by the aggregate length of these chapters. The DYNEV IIsimulation logic is likewise complex.

The simulation model explicitly models intersections: Stop/yield controlled intersections (both 2-way and all-way) 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 time-varying 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, contra-flow lanes) is used, the strategy is modeled explicitly. Where applicable, the location and type of traffic control for nodes in the evacuation network are noted in Appendix K. The characteristics of the ten highest volume signalized intersections are detailed in Appendix J.

4.4 Simulation and Capacity Estimation Chapter 6 of the HCM 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 interactionsinvoking several procedural chapters of the HCM. Alternative tools are able to analyze these facilities as a single system."

This statement succinctly describes the analyses required to determine traffic operations across an area encompassing an EPZ 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 - 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 2010 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 Palo Verde 4-8 KLD Engineering, P.C.

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these are: (1) Free flow speed (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 2010, as described earlier. These parameters are listed in Appendix K,for each network link.

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Volume, vph Capacity Drop Qmax -

R Qmax -

--- Qs Density, vpm ,

Speed, mph:

Free Forced:

  • I I I
  • I I I vf R v, -'
  • I I I
  • I
  • I
  • I
  • I I I I I I I * -~ ueniMv J
  • vpm kf keopt Figure 4-1. Fundamental Diagrams 4-10 KLD Engineering, P.C.

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