ML21096A294
| ML21096A294 | |
| Person / Time | |
|---|---|
| Issue date: | 04/30/2021 |
| From: | Pamela Noto Office of Nuclear Material Safety and Safeguards |
| To: | |
| Malone, Tina | |
| Shared Package | |
| ML21096A269 | List: |
| References | |
| NUREG/BR-0058, Rev. 5 | |
| Download: ML21096A294 (150) | |
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APPENDIX H SEVERE ACCIDENT RISK ANALYSIS
H-iii NUREG/BR-0058, Rev. 5, App. H, Rev. 0 TABLE OF CONTENTS 1
LIST OF FIGURES...................................................................................................... H-v 2
LIST OF TABLES..................................................................................................... H-vii 3
ABBREVIATIONS AND ACRONYMS....................................................................... H-ix 4
H.1 PURPOSE......................................................................................................... H-1 5
H.2 BACKGROUND................................................................................................. H-2 6
H.3 SEVERE REACTOR ACCIDENT RISK INFORMATION USED IN SAFETY 7
GOAL EVALUATION AND COST-BENEFIT ANALYSIS................................. H-6 8
H.3.1 Probabilistic Risk Assessment Model Selection Guidance.................................. H-6 9
H.3.1.1 Probabilistic Risk Assessment Model Scope.......................................... H-7 10 H.3.1.2 The Structure of Traditional Nuclear Power Plant Probabilistic Risk 11 Assessment Models............................................................................... H-8 12 H.3.2 Risk Metrics for Evaluating Substantial Safety Benefit........................................ H-9 13 H.3.3 Common Analysis Elements.............................................................................. H-12 14 H.3.3.1 Accident Sequence Analysis................................................................ H-12 15 H.3.3.2 Quantification of Change in Accident Frequency.................................. H-14 16 H.3.3.3 Quantification of Change in Consequences......................................... H-15 17 H.3.3.4 Identification and Estimation of Affected Parameters........................... H-16 18 H.4 GRADED APPROACH TO ANALYSIS........................................................... H-18 19 H.4.1. Example of Approach........................................................................................ H-20 20 H.4.2. Sources of Information...................................................................................... H-22 21 H.5 MAJOR-EFFORT ANALYSIS......................................................................... H-28 22 H.5.1 Accident Sequence Analysis.............................................................................. H-28 23 H.5.2 Severe Accident Progression Analysis.............................................................. H-30 24 H.5.2.1 Sources of Information.......................................................................... H-30 25 H.5.2.2 MELCOR Modeling Approach.............................................................. H-31 26 H.5.3 Offsite Consequence Analysis........................................................................... H-32 27 H.5.3.1 Sources of Information.......................................................................... H-32 28 H.5.3.2 MACCS Modeling Approach................................................................. H-32 29 H.6 SUPPLEMENTAL ANALYSES....................................................................... H-36 30 H.6.1 Uncertainty Analyses......................................................................................... H-36 31 H.6.1.1 Uncertainties in PRA Models................................................................ H-36 32 H.6.2 Sensitivity Analyses and Plant-to-Plant Variability Analyses............................. H-39 33
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-iv H.6.2.1 Sensitivity Analyses.............................................................................. H-40 1
H.6.2.2 Plant-to-Plant Variability Analyses........................................................ H-40 2
H.7 PRESENTATION OF RESULTSINPUTS TO REGULATORY 3
ANALYSIS....................................................................................................... H-42 4
H.7.1 Aggregating Probabilistic Risk Assessment Results from Different Hazards..... H-42 5
H.7.2 Offsite Consequence Measures......................................................................... H-42 6
H.7.2.1 Conditional Consequence Measures.................................................... H-42 7
H.7.3 Evaluation of Regulatory Alternatives................................................................ H-44 8
H.7.3.1 Results from the Core Damage Event Tree Quantification................... H-44 9
H.7.3.2 Results from the Accident Progression Event Tree Quantification....... H-44 10 H.7.3.3 Results from MELCOR Analysis........................................................... H-45 11 H.7.4 Risk Integration Results and Key Insights.......................................................... H-46 12 H.8 REFERENCES................................................................................................ H-50 13 ENCLOSURE H-1: DESCRIPTION OF ANALYTICAL TOOLS AND 14 CAPABILITIES......................................................................... H-58 15 ENCLOSURE H-2:
SUMMARY
OF THE STATE-OF-THE-ART REACTOR 16 CONSEQUENCE ANALYSES (SOARCA) PROJECT............. H-73 17 ENCLOSURE H-3:
SUMMARY
OF DETAILED ANALYSES FOR SECY-12-0157, 18 CONSIDERATION OF ADDITIONAL REQUIREMENTS FOR 19 CONTAINMENT VENTING SYSTEMS FOR BOILING WATER 20 REACTORS WITH MARK I AND MARK II 21 CONTAINMENTS................................................................... H-77 22 ENCLOSURE H-4:
SUMMARY
OF DETAILED ANALYSES FOR SECY-15-0085, 23 EVALUATION OF THE CONTAINMENT PROTECTION AND 24 RELEASE REDUCTION FOR MARK I AND MARK II 25 BOILING-WATER REACTORS RULEMAKING 26 ACTIVITIES............................................................................. H-92 27 ENCLOSURE H-5:
SUMMARY
OF DETAILED ANALYSES FOR SECY-13-0112 28 AND NUREG-2161, CONSEQUENCE STUDY OF A BEYOND-29 DESIGN-BASIS EARTHQUAKE AFFECTING THE SPENT 30 FUEL POOL FOR A U.S. MARK I BOILING-WATER 31 REACTOR............................................................................ H-111 32 ENCLOSURE H-6:
SUMMARY
OF DETAILED ANALYSES IN COMSECY-13-0030, 33 ENCLOSURE 1, REGULATORY ANALYSIS FOR JAPAN 34 LESSONS-LEARNED TIER 3 ISSUE ON EXPEDITED 35 TRANSFER OF SPENT FUEL.............................................. H-130 36
H-v NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
LIST OF FIGURES 2
3 Figure H-1 Overall Logic and Structure of Traditional NPP PRA Models............................. H-9 4
Figure H-2 Distribution of 2016 Point Estimates for Total CDF, U.S. Plants...................... H-11 5
Figure H-3 Distribution of 2016 Point Estimates for LERF, U.S. Plants.............................. H-11 6
Figure H-4 Uncertainty in Average Individual Latent Cancer Fatality Risk (0-10 miles) in 7
the 2015 Containment Protection and Release Reduction Regulatory 8
Analysis............................................................................................................. H-22 9
Figure H-5 Modular Approach to Event Tree Development in CPRR Analysis................... H-29 10 Figure H-6 Parametric Uncertainty Analysis Results for Individual Latent Cancer 11 Fatality Risk...................................................................................................... H-39 12 Figure H-7 Likelihood of a Leak and Magnitude of Releases from Beyond-Design-Basis 13 Earthquake........................................................................................................ H-45 14 Figure H-8 Comparison of Regulatory Analysis Alternatives Using Population Dose 15 Risk (0-50 miles)............................................................................................... H-48 16 Figure H-9 Reduction in 50-mile Offsite Cost Risk ($/reactor-year)................................. H-48 17 Figure H-10 Uncertainty in Reduction in 50-mile Offsite Cost Risk...................................... H-49 18 Figure H-11 Overall Logic and Structure of Traditional NPP PRA Models and Role of 19 SAPHIRE, MELCOR, and MACCS Code Suites.............................................. H-59 20 Figure H-12 Simplified Diagram of Event Tree with Initiating Event (IE) and Two 21 Supporting Fault Trees..................................................................................... H-62 22 Figure H-13 Simplified Event Tree Structure........................................................................ H-82 23 Figure H-14 Reduction in 50-mile Population Dose Risk (person-rem/ry).......................... H-85 24 Figure H-15 Reduction in 50-mile Offsite Cost Risk ($/ry).................................................. H-85 25 Figure H-16 Uncertainty in Reduction in 50-mile Population Dose Risk............................... H-87 26 Figure H-17 Uncertainty in Reduction in 50-mile Offsite Cost Risk...................................... H-87 27 Figure H-18 Uncertainty in Average Individual Latent Cancer Fatality Risk (0-10 miles)..... H-98 28 Figure H-19 Modular Approach to Event Tree Development.............................................. H-100 29 Figure H-20 Conditional Probability of SFP Liner Leakage and SFP Release 30 Magnitude....................................................................................................... H-126 31 32
H-vii NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
LIST OF TABLES 2
3 Table H-1 Options Defining Scope of Commercial NPP PRAs............................................. H-8 4
Table H-2 Reactors with Published SAMA Analyses.......................................................... H-23 5
Table H-3 Salem Nuclear Generating Station Core Damage Frequency for Internal 6
Events at Power................................................................................................. H-26 7
Table H-4 Salem Nuclear Generating Station Breakdown of Population Dose by 8
Containment Release Mode............................................................................... H-27 9
Table H-5 Ratio of Consequences for 1-Year Intermediate Phase Duration 10 Sensitivity Cases to Baseline Cases in the Containment Protection and 11 Release Reduction Analysis............................................................................... H-41 12 Table H-6 Severe Accident Consequence Analysis ResultsExample............................. H-44 13 Table H-7 Risk Estimates by Regulatory Analysis Subalternative...................................... H-47 14 Table H-8 Conditional Annual Average Individual Latent Cancer Fatality Risk from 15 SOARCA Unmitigated Scenarios within 10 miles of the Plant........................... H-75 16 Table H-9 Hypothetical Plant Modifications........................................................................ H-81 17 Table H-10 Mapping of Simplified Event Tree Sequences to Plant Modifications 18 and MELCOR Cases.......................................................................................... H-82 19 Table H-11 Parameter Values Used to Estimate Radiological Release Frequencies........... H-83 20 Table H-12 Mean MACCS Consequence Results for Selected MELCOR Accident 21 Scenarios........................................................................................................... H-83 22 Table H-13 Point Estimate Risk Values for Each Hypothetical Plant Modification................ H-84 23 Table H-14 Risk Reductions from Severe-Accident-Capable Venting System Plant 24 Modifications...................................................................................................... H-84 25 Table H-15 Parameter Uncertainty Distributions.................................................................. H-86 26 Table H-16 Summary of Quantitative Cost-Benefit Analysis Results for Filtered 27 Containment Vent System using a $2,000 per Person-Rem Conversion 28 Factor................................................................................................................. H-89 29 Table H-17 Summary of Adjusted Quantitative Cost-Benefit Analysis Results for 30 Filtered Containment Vent System using a $4,000 per Person-Rem 31 Conversion Factor.............................................................................................. H-89 32 Table H-18 Ratings Assigned to Each Alternative by Qualitative Factor.............................. H-90 33 Table H-19 Summary of Regulatory Subalternatives and Distinguishing Attributes............. H-96 34 Table H-20 MACCS Results for 18 Mark I Source Term Bins............................................ H-103 35 Table H-21 MACCS Results for 9 Mark II Source Term Bins............................................. H-104 36 Table H-22 Risk Estimates by Regulatory Analysis Subalternative.................................... H-106 37 Table H-23 Uncertainty Analysis Inputs.............................................................................. H-107 38 Table H-24 Results for Baseline Cases with Different Site Files........................................ H-108 39 Table H-25 Operating Cycle Phase Descriptions............................................................... H-115 40 Table H-26 Scenario Descriptions for a Given Operating Cycle Phase.............................. H-116 41 Table H-27 Summary of Release Results for High-Density Configurations........................ H-119 42 Table H-28 Summary of Release Results for Low-Density Configurations........................ H-119 43
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-viii Table H-29 Binning of MELCOR Release Sequences into Release Categories for 1
High-Density Configurations............................................................................. H-121 2
Table H-30 Binning of MELCOR Release Sequences into Release Categories for 3
Low-Density Configurations............................................................................. H-121 4
Table H-31 Mean Reduction in Offsite Consequence Results Associated with Option 2... H-123 5
Table H-32 Summary of Benefits and Costs within 50 Miles for Option 2.......................... H-128 6
Table H-33 Combined Effect of $4,000 per Person-Rem Conversion Factor and 7
Consequences Beyond 50 Miles for Option 2.................................................. H-128 8
Table H-34 SFP Groupings Used for the Staff's Technical and Cost-Benefit Analyses..... H-134 9
Table H-35 Key Input Parameters Used for Sensitivity Analyses....................................... H-137 10 Table H-36 Summary of Net Benefits for Each Spent Fuel Pool Group*............................ H-138 11 Table H-37 Net Benefits for Low-Density SFP Storage for Groups 1-4 from Combined 12 Sensitivity Analyses that Analyzed Consequences Beyond 80 kilometers 13 (50 Miles) and Using an Adjusted Dollar per Person-Rem Conversion 14 Factor............................................................................................................... H-139 15 16
H-ix NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
ABBREVIATIONS AND ACRONYMS 2
3 delta or incremental 4
U.S. dollars 5
ADAMS Agency wide Documents Access and Management System 6
ANS American Nuclear Society 7
AP1000 Advanced Passive 1000 8
APET accident progression event tree 9
ASME American Society of Mechanical Engineers 10 ATD atmospheric transport and dispersion 11 Ba chemical element barium 12 B&W Babcock and Wilcox 13 BWR boiling-water reactor 14 C
degrees Celsius 15 Ci consequences for each potential accident i 16 CDET core damage event tree 17 CDF core damage frequency 18 Ce chemical element cerium 19 CE Combustion Engineering 20 CFR Code of Federal Regulations 21 Ci radiation units in Curies 22 CPRR containment protection and release reduction 23 Cs chemical element cesium 24 DF decontamination factor 25 DOE U.S. Department of Energy 26 DW drywell 27 DWF drywell first strategy 28 ELAP extended loss of alternating current power 29 EPA U.S. Environmental Protection Agency 30 EPRI Electrical Power Research Institute 31 EPZ emergency planning zone 32 ESP early site permit 33 ETE evacuation time estimate 34 F
degree Fahrenheit 35 FLEX flexible coping strategies 36 FR Federal Register 37 GE General Electric 38 gpm flow rate in gallons per minute 39 I
chemical element iodine 40 IE initiating event 41 ILRT integrated leak rate testing 42 IPE individual plant examination 43 IPEEE individual plant examination for external events 44 ISLOCA interfacing systems loss-of-coolant accident 45 K
degrees Kelvin 46 Kg/m3 gas density in kilograms per cubic meter 47 Kg/s mass flow rate in kilograms per second 48 KI chemical compound potassium iodide 49 La chemical element lanthanum 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-x LERF large early release frequency 1
LMT liner melt-through 2
LTSBO long-term station blackout 3
LWR light-water reactor 4
MACCS MELCOR Accident Consequence Code System 5
MCi radiation unit in million Curies 6
Mo chemical element molybdenum 7
Mod modification 8
MWt megawatt thermal 9
NEI Nuclear Energy Institute 10 NFPA National Fire Protection Association 11 NPP nuclear power plant 12 NRC U.S. Nuclear Regulatory Commission 13 NSSS nuclear steam supply systems 14 NTTF Near-Term Task Force 15 OCP operating cycle phase 16 OMB Office of Management and Budget 17 OP overpressurization 18 Pi probability or frequency of potential accident i 19 PAG protective action guide 20 PRA probabilistic risk assessment 21 Psi pounds per square inch 22 psig pounds per square inch gauge 23 PWR pressurized-water reactor 24 QHO quantitative health objective 25 R
risk 26 RC release category 27 RPV reactor pressure vessel 28 Ru chemical element rubidium 29 RuO2 chemical compound ruthenium oxide 30 Ry reactor-year 31 SAMA severe accident mitigation alternative 32 SAMDA severe accident mitigation design alternative 33 SAPHIRE Systems Analysis Program for Hands-on Integrated Reliability 34 Evaluations 35 SAWA severe accident water addition 36 SAWM severe accident water management 37 SBO station blackout 38 SFP spent fuel pool 39 SGTR steam generator tube rupture 40 SOARCA State-of-the-Art Reactor Consequence Analyses 41 SPAR Standardized Plant Analysis Risk 42 SRM staff requirements memorandum 43 STSBO short-term station blackout 44 Te chemical element tellurium 45 U.S.
United States 46 W
rate of sensible heat 47 WWF wetwell first strategy 48 Xe chemical element xenon 49
H-1 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 SEVERE ACCIDENT RISK ANALYSIS 1
2 H.1 PURPOSE 3
4 The purpose of this appendix is to provide guidance and best practices for use at the 5
U.S. Nuclear Regulatory Commission (NRC) when performing probabilistic risk assessments 6
(PRAs) and consequence analyses as part of regulatory, backfit, and environmental analyses 7
for nuclear power reactors.
8 9
Used in conjunction with the discussion in Section 5 of this NUREG, this appendix explains how 10 to perform the safety goal evaluation and the valuation of the public health (accident) and 11 economic consequences (offsite property) attributes for the purposes of cost-benefit analysis. It 12 provides references on sources of information and an overview of the tools and methods used 13 to estimate baselines and changes in core damage frequency (CDF), large early release 14 frequency (LERF), public health risk, and offsite economic consequences risk. Onsite risk 15 attributesoccupational health risk (accident) and onsite property riskare also relevant to 16 nuclear power reactor severe accident risk but are not within the scope of this appendix.
17 Finally, the guidance on performing offsite consequence analyses is useful for reference when 18 conducting the severe accident mitigation alternative (SAMA) and severe accident mitigation 19 design alternative (SAMDA) analyses that are required under the National Environmental Policy 20 Act (see Appendix I, National Environmental Policy Act Cost-Benefit Analysis Guidance, to this 21 NUREG).
22 23 This appendix does not impose new requirements, establish NRC policy, or instruct NRC staff in 24 preparing cost estimates. Rather, it provides information on accepted state-of-practice methods 25 for estimating the frequency and consequence components of the risk from hypothetical 26 accidents at nuclear power plants (NPPs), for the purposes of safety goal evaluations and 27 cost-benefit analyses for regulatory, backfitting, forward fitting, issue finality, and National 28 Environmental Policy Act environmental review analyses.
29 30
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-2 H.2 BACKGROUND 1
2 The quantification of risks associated with postulated severe accidents is an integral part of the 3
NRCs regulatory policy and practices. A severe accident is an accident that involves 4
extensive core damage and fission product release into the reactor vessel and containment, 5
with potential release to the environment (NRC, 2013f; ASME/ANS, 2009). The NRC uses 6
PRAs for the severe accident risk quantification that is needed in regulatory, backfit, and 7
environmental analyses.
8 9
The NRC has a long history of using PRA techniques to characterize severe accident risks in 10 support of its regulatory processes and decisions. Since the completion of the seminal Reactor 11 Safety Study (WASH-1400, Reactor Safety Study: An Assessment of Accident Risks in 12 U.S. Commercial Nuclear Power Plants, issued October 1975 (NRC, 1975)), PRAs have 13 provided important, actionable safety insights through a number of different studies. In the late 14 1970s, the NRC used insights from PRA in consideration of topics, including the likelihood of 15 loss-of-coolant accidents, the reliability of direct current power supplies, and the effectiveness of 16 alternate containment designs (NRC, 2016c). In the early 1980s, the NRC relied on PRA 17 techniques to address unresolved safety issues involving accidents such as the anticipated 18 transient without scram (NRC, 1978) and station blackout (SBO) rules (NRC, 1988b). The NRC 19 considered risk arguments in support of licensee requests to extend equipment outage times 20 and the Commission used information from licensee-sponsored PRAs to inform its decision in 21 1985 to allow continued operation of the Indian Point power plants (NRC, 2016c).
22 23 In 1985, the Commission issued a policy statement on severe accidents, which recognized that 24 plant-specific PRAs had exposed unique vulnerabilities to severe accidents and were a 25 potential source of significant new safety information to identify instances of undue risk 26 (NRC, 1985). This policy statement led to the issuance of Generic Letter 88-20, Individual 27 Plant Examination for Severe Accident Vulnerabilities10 CFR 50.54(f), dated 28 November 23, 1988 (NRC, 1988a), asking each licensee to conduct an individual plant 29 examination (IPE) to identify plant-specific vulnerabilities to severe accidents and report the 30 results to the Commission, and later to Generic Letter 88-20, Supplement 4, Individual Plant 31 Examination of External Events (IPEEE) for Severe Accident Vulnerabilities10 CFR 50.54(f),
32 dated June 28, 1991 (NRC, 1991), which focused on severe accidents initiated by external 33 events. As a result, 74 PRAs representing 106 U.S. NPPs were completed; the assessments 34 calculated CDF and LERF1 and gave the utilities a method for tracking improvements made in 35 terms of risk abatement and cost effectiveness (Keller and Modarres, 2005). The NRC 36 documents its staff summary and evaluation of licensee submittals under this program in 37 NUREG-1560, Individual Plant Examination Program: Perspectives on Reactor Safety and 38 Plant Performance, issued December 1997 (NRC, 1997a), and NUREG-1742, Perspectives 39 Gained from the Individual Plant Examination of External Events (IPEEE) ProgramFinal 40 Report, issued April 2002 (NRC, 2002), for the IPEs and IPEEEs, respectively. The NRC had 41 also sponsored an assessment of the risks from severe accidents in five commercial nuclear 42 power plants in the United States which was published in 1990 as NUREG-1150, Severe 43 Accident Risks: An Assessment for Five U.S. Nuclear Power Plants (NRC, 1990b).
44 NUREG-1150 and supplementary studies based on NUREG-1150 were the main sources of 45 information and basis for the NRCs 1997 NUREG/BR-0184, Regulatory Analysis Technical 46 Evaluation Handbook, Final Report (NRC, 1997b); for example, see NUREG/BR-0184, 47 1
LERF is defined as The frequency of a rapid, unmitigated release of airborne fission products from the containment to the environment that occurs before effective implementation of offsite emergency response, and protective actions, such that there is a potential for early health effects (NRC, 2013f).
H-3 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table 5.3 and Appendix B.4.
1 2
The Commission formally endorsed the use of PRA methods in nuclear regulatory activities in 3
its 1995 policy statement (NRC, 1995a), which includes the following precepts:
4 5
The use of PRA technology should be increased in all regulatory matters to the extent 6
supported by the state-of-the-art in PRA methods and data and in a manner that 7
complements the NRCs deterministic approach and supports the NRCs traditional 8
defense-in-depth philosophy.
9 10 PRA and associated analyses (e.g., sensitivity studies, uncertainty analyses, and 11 importance measures) should be used in regulatory matters, where practical within the 12 bounds of the state-of-the-art, to reduce unnecessary conservatism associated with 13 current regulatory requirements, regulatory guides, license commitments, and staff 14 practices. Where appropriate, PRA should be used to support the proposal for 15 additional regulatory requirements in accordance with 10 CFR 50.109 (Backfit Rule) 16
[Title 10 of the Code of Federal Regulations (10 CFR) 50.109, Backfitting].
17 18 PRA evaluations in support of regulatory decisions should be as realistic as practicable 19 and appropriate supporting data should be publicly available for review.
20 21 The 1995 policy statement introduced the concept of risk-informed regulation; which solidified 22 the role of PRA methods and results in regulatory decisionmaking. Today, the NRC conducts 23 risk analyses for a wide range of regulatory activities and processes. Examples of activities that 24 rely on PRA include:
25 26 Regulatory analysis and backfit analysis: PRAs are used to determine whether 27 additional new regulatory requirements for licensees could lead to a substantial safety 28 improvement. Potential benefits such as reduced public health risk or reduced risk of 29 offsite economic consequences are quantified as part of the cost-benefit analysis to 30 justify new or amended rules or guidance.
31 32 New reactor certification and licensing: 10 CFR 52.47, Contents of Applications; 33 Technical Information, requires that an application for standard design certification 34 contain a description of the plant-specific PRA and its results. A similar requirement 35 applies to combined license applicants in 10 CFR 52.79, Contents of Applications; 36 Technical Information in Final Safety Analysis Report.
37 38 Risk-informed decisionmaking:
39 40 o
Changes in plant licensing basis: Operating reactor licensees may use risk 41 information to support a voluntary change from a plants current licensing basis 42 to a new licensing basis. Regulatory Guide 1.174, An Approach for Using 43 Probabilistic Risk Assessment in Risk-Informed Decisions on Plant-Specific 44 Changes to the Licensing Basis (current version), provides guidance on the use 45 of PRA findings and risk insights to a support licensee request for changes to a 46 plants licensing basis.
47 48
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-4 o
Reactor oversight: The NRCs regulatory framework for reactor oversight is 1
risk-informed and performance based.2 The Reactor Oversight Process uses 2
performance indicators and inspection findings that are color coded according to 3
safety/risk significance. Within the Reactor Oversight Processs strategic 4
performance area of reactor safety, significance determinations of inspection 5
findings and events rely on plant-specific risk information, such as the changes in 6
7 8
Environmental reviews: The licensee prepares an environmental report and submits it 9
to the NRC for independent evaluation as part of an application for license renewal for 10 an existing reactor, a design certification application for a new reactor, and a 11 construction and operating license application for a new reactor. These reports are 12 required to include SAMA or SAMDA evaluations to identify potential features or actions 13 that would prevent or mitigate the consequences of a severe accident. These 14 requirements appear in 10 CFR 51.53(c)(3)(ii)(L) for operating reactor license renewal 15 applicants; 10 CFR 51.55, Environmental Report; Standard Design Certification, for 16 new reactor design certification applicants; and 10 CFR 51.75, Draft Environmental 17 Impact StatementConstruction Permit, Early Site Permit, or Combined License, for 18 new reactor construction permits, early site permits,3 and combined license 19 environmental impact statements. A PRA and offsite consequence analysis would 20 support whether these SAMA are cost-beneficial.
21 22 In addition, the 2011 accident at the Fukushima Dai-ichi NPP in Japan initiated a large-scale 23 effort by the staff to identify potential modifications to equipment and operational requirements 24 to address the lessons learned from this disaster. The NRC undertook a number of major 25 regulatory analyses to inform Commission decisions. Notable examples are listed below, with 26 additional information available in enclosures to this appendix as indicated. The following 27 analyses are regulatory analyses that supported these NRC decisions. The enclosures to this 28 appendix summarize these analyses and highlight the approaches and evaluation criteria that 29 were used, the information that was provided, the results and insights, and the resulting 30 Commission decision, if applicable. These enclosures are intended to provide useful examples 31 for performing these types of analyses.
32 33 SECY-12-0157, Consideration of Additional Requirements for Containment Venting 34 Systems for Boiling Water Reactors with Mark I and Mark II Containments, dated 35 November 26, 2012 (NRC, 2012h) and SRM-SECY-12-0157, Consideration of 36 Additional Requirements for Containment Venting Systems for Boiling Water Reactors 37 with Mark I and Mark II Containments, dated May 19, 2013 (NRC, 2013h). See also 38 Enclosure H-3.
39 40 SECY-15-0085, Evaluation of the Containment Protection and Release Reduction for 41 Mark I and Mark II Boiling-Water Reactor Rulemaking Activities, dated June 18, 2015 42 (NRC, 2015a) and SRM-SECY-15-0085, Evaluation of the Containment Protection and 43 Release Reduction for Mark I and Mark II Boiling-Water Reactor Rulemaking Activities, 44 dated August 19, 2015 (NRC, 2015c). See also Enclosure H-4.
45 46 The spent fuel pool (SFP) study supporting the evaluation of expedited transfer or spent 47 fuel, SECY-13-0112, Consequence Study of a Beyond-Design-Basis Earthquake 48 2
https://www.nrc.gov/reactors/operating/oversight/rop-description.html 3
This applies if a design has been chosen at the early site permit stage.
H-5 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water Reactor, dated 1
October 9, 2013 (NRC, 2013e). See also Enclosure H-5.
2 3
COMSECY-13-0030, Staff Evaluation and Recommendation for Japan 4
Lessons-Learned Tier 3 Issue on Expedited Transfer of Spent Fuel, dated 5
November 12, 2013 (NRC, 2013g) and SRM-COMSECY-13-0030, Staff 6
RequirementsStaff Evaluation and Recommendation for Japan Lessons-Learned Tier 7
3 Issue on Expedited Transfer of Spent Fuel, dated May 23, 2014 (NRC, 2014h). See 8
also Enclosure H-6.
9 10 Mitigation of beyond-design basis events is described in SECY-15-0065, Proposed 11 Rulemaking: Mitigation of Beyond-Design-Basis Events, dated April 30, 2015 12 (NRC, 2015d) and SRM-SECY-15-0065, Staff RequirementsProposed Rulemaking:
13 Mitigation of Beyond-Design-Basis Events, dated August 27, 2015 (NRC, 2015f).
14 15 These activities have resulted in a more consistent and technically justified application of PRA 16 and severe accident consequence analysis in the NRCs regulatory process and serve as the 17 basis for this guidance. The following sections explain the risk information, tools, methods, and 18 approaches that are used to conduct these analyses.
19 20
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-6 H.3 SEVERE REACTOR ACCIDENT RISK INFORMATION USED IN 1
SAFETY GOAL EVALUATION AND COST-BENEFIT ANALYSIS 2
3 The NRC uses a risk analysis framework to determine when a proposed requirement may meet 4
the substantial additional protection standard and to provide some of the metrics needed to 5
weigh the costs against the benefits of a regulatory action. Evaluating the benefits associated 6
with a regulatory action requires the quantification of both the likelihood and the conditional 7
consequences of fission product release for a spectrum of hypothetical severe accident 8
scenarios. The complexity of the risk analysis depends on the type of analysis to be conducted.
9 This appendix should be used with Section 2.1 of this NUREG to understand the level of effort 10 needed for each type of analysis and the factors that should be used to determine which 11 analysis is appropriate.
12 13 14 A basic principle of this NUREG is that each analysis should be adequate for its intended 15 application in terms of the type of information supplied, the level of detail provided, the level of 16 uncertainty, and the availability of design margin. In general, the severe accident risk analysis 17 considers plant systems and operator responses to initiating events leading to core damage 18 (Level 1 PRA) and accident progression to the release of fission products to the environment 19 (Level 2 PRA), while combining estimates of radiological release category frequencies and their 20 associated consequences (Level 3 PRA) to produce risk estimates. This section details the 21 technical approach used to complete each portion of the risk evaluation. These discussions 22 assume familiarity with the concepts of risk as related to the nuclear industry, as well as 23 knowledge of event-and fault-tree terminology. The analyst should consult existing PRAs and 24 standard references4 for further information on these concepts. Sections H.4 through H.6 25 provide specific guidance for performing analyses.
26 27 H.3.1 Probabilistic Risk Assessment Model Selection Guidance 28 29 The purpose of this section is to provide the analyst with guidance on selecting PRA models to 30 perform safety goal screenings and estimate the potential public health benefits (from avoided 31 accidents) associated with a proposed regulatory action. Performing these evaluations requires 32 a PRA model to analyze the effects of the proposed action. The most important considerations 33 for selecting the PRA model are its scope and its level of detail, which together should be 34 sufficient to assess the issues of concern.
35 36 4
For instance, NUREG/CR-2300, PRA Procedures Guide: A Guide to the Performance of Probabilistic Risk Assessments for Nuclear Power Plants, issued January 1983 (NRC, 1983a), and NUREG-0492, Fault Tree Handbook, issued January 1981 (NRC, 1981).
Staff should consult the most current PRA information available when beginning a new analysis.
H-7 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H.3.1.1 Probabilistic Risk Assessment Model Scope 1
2 The NPP PRA models can vary in scope, depending on their intended application or use. As 3
summarized in Table H-1, the scope of a PRA is defined by the extent to which various options 4
for the following five factors are modeled and analyzed:
5 6
(1)
Radiological sources: The NPP sites contain multiple sources that could potentially 7
release radioactive material into the environment under accident conditions. Although 8
most PRA models focus on the reactor core, other important sources that could be 9
modeled in the PRA to estimate the public health accident risk from an NPP site include 10 (1) spent nuclear fuel (both wet and dry storage), (2) fresh nuclear fuel, and 11 (3) radiological waste storage tanks.
12 13 (2)
Exposed population: In estimating the numbers of radiological health effect cases 14 attributable to a postulated nuclear accident, both onsite and offsite populations may be 15 considered. Typical NPP PRA models estimate the radiological health risk to members 16 of the general public located at various distances from the NPP site. Although these 17 PRA models do not consider the risk to onsite workers and first responders to a nuclear 18 accident, the radiological health risks to these groups typically are considered as part of 19 other attributes included in a regulatory analysis (e.g., occupational health (accident)).
20 21 (3)
Initiating event hazard groups: Initiating events cause the plant to deviate from its 22 intended operating state and challenge plant control, safety systems, and operator 23 actions designed to prevent reactor core damage and the release of radioactive material 24 to the environment. These events include failure of equipment from (1) internal causes 25 (e.g., transients, loss-of-coolant accidents, internal floods, internal fires) or (2) external 26 causes (e.g., earthquakes, high winds, tsunamis). In an NPP PRA model, similar 27 causes of initiating events are organized by hazard group and are then assessed using 28 common assumptions, methods, and data to characterize their effects on the plant.
29 30 (4)
Plant operating states: In determining the public risk from NPP operations, it is 31 important to consider not only the response of the plant to initiating events occurring 32 during at-power operation but also its response to initiating events occurring while the 33 plant is in other operating states, such as low-power and shutdown. Plant operating 34 states are used to subdivide the plant operating cycle into unique states defined by 35 various characteristics (e.g., reactor power, coolant temperature, coolant pressure, 36 coolant level, equipment configuration) so that the plant response can be assumed to be 37 the same for all initiating events that occur when a plant is assumed to be in a particular 38 plant operating state.
39 40 (5)
End state (level of risk characterization): The NPP PRA models can be used to 41 calculate risk metrics at different end states. The text below discusses in more detail the 42 three different end states or levels of risk characterization that traditionally have been 43 used in NPP PRA models.
44 45
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-8 Table H-1 Options Defining Scope of Commercial NPP PRAs 1
Factor Scoping Options for Commercial NPP PRAs Radiological sources Reactor core(s)
Spent nuclear fuel (SFP and dry cask storage)
Other radioactive sources (e.g., fresh fuel and radiological wastes)
Exposed population Offsite population Initiating event hazard groups Internal hazards Traditional internal events (transients, loss-of-coolant accidents)
Internal floods Internal fires External hazards Seismic events (earthquakes)
Other site-specific external hazards (e.g., high winds, external flooding)
Plant operating states At-power Low-power Shutdown End state/Level of risk characterization Level 1 PRA: Initiating event to onset of core damage Level 1 plus LERF: Level 1 plus limited scope Level 2, which is sufficient for the purpose of calculating LERF Level 2 PRA: Initiating event to radioactive material release from containment Level 3 PRA: Initiating event to offsite radiological consequences 2
The most important aspects to consider when evaluating the scope of a PRA model is to ensure 3
that it includes significant risk contributors that are relevant to the evaluation of a proposed 4
regulatory action and that the level of detail is appropriate with respect to scope, level of detail, 5
and technical acceptability.
6 7
H.3.1.2 The Structure of Traditional Nuclear Power Plant Probabilistic Risk Assessment 8
Models 9
10 Risk can be characterized in many ways, depending on the end states of interest for a decision 11 or application. To provide some overall logic and structure and to facilitate evaluation of 12 intermediate results, PRAs for NPPs have traditionally been organized into three analysis levels.
13 Three sequential adverse end states that can occur in the progression of postulated NPP 14 accident scenarios define these levels (1) onset of damage to the nuclear fuel in the reactor 15 core (termed core damage), (2) release of radioactive materials from the NPP containment 16 structure to the surrounding environment (termed radiological release), and (3) adverse human 17 health, environmental, and economic consequences that occur beyond the boundary of the NPP 18 site (commonly referred to as offsite radiological consequences).
19 20 Figure H-1 illustrates the overall logic and structure of traditional NPP PRA models, including 21 the types of results that are produced at each level.
22 23
H-9 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 LEVEL 1 PRA MODEL Increasing PRA model scope and complexity LEVEL 2 PRA MODEL LEVEL 3 PRA MODEL Initiating Events & Mitigating Systems Response Logic Models Severe Accident Phenomenological Models
& Containment Systems Conditional Probabilistic Consequence Analysis Models Core Damage
- Total core damage frequency
- Core damage sequence information
- Importance measures Radiological Release
- Radiological release category frequencies
- Representative source term information Offsite Radiological Consequences
- Population dose
- Adverse human health effects
- Contaminated areas
- Economic costs 1
Figure H-1 Overall Logic and Structure of Traditional NPP PRA Models 2
3 In NPP Level 3 PRAs, the output of PRA logic models that estimate the frequencies of a 4
representative set of radiological release categories intended to capture a reasonably complete 5
spectrum of possible accident scenarios is combined with the conditional consequence results 6
for each release category. For each outcome of interest, the consequences are then summed 7
across all radiological release categories to estimate the mean annual risk of that outcome.
8 9
The first step in conducting the analysis is to identify the potential source of risk (e.g., reactor 10 core, spent fuel, dry cask storage), reactor operating states (e.g., at-power, low-power, 11 shutdown), and hazards of concern (e.g., internal events, external events, all hazards) for 12 analysis. The potential source of risk will usually be determined by the objective statement 13 described in Sections 2.3.1 and 2.3.2 of this NUREG, which provide guidance on defining the 14 regulatory problem statement and identifying regulatory alternatives. A complete assessment of 15 alternatives that includes all relevant accident scenarios may require the development of plant-16 specific, full-scope Level 3 PRAs for each plant type of interest. However, this may exceed the 17 required level of detail necessary for a regulatory analysis. For most regulatory analyses, the 18 regulatory problem statement will delineate the accident initiators and sequences to be 19 considered.
20 21 H.3.2 Risk Metrics for Evaluating Substantial Safety Benefit 22 23 For potential backfit considerations, it is useful to have an approximation of the range of the 24 CDFs and LERFs for relevant classes of plants. Section 2.4.1 of this NUREG describes the 25 quantitative risk thresholds for substantial safety benefit. The NRC uses LERF instead of the 26 historical conditional containment failure probability (see for example, Regulatory Guide 1.174).
27 The analyst has access to a current body of CDF and LERF information of operating NPPs from 28 a variety of sources. These sources include the NRCs plant-specific Standardized Plant 29 Analysis Risk (SPAR) models, risk information in SAMA analyses supporting license renewal 30
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-10 applications, and license amendment requests supporting risk-informed regulatory applications 1
such as those for risk-informed in-service inspection (NRC, 2003).
2 3
Figures H-2 (CDF) and H-3 (LERF) show representative distributions of point estimates for CDF 4
and LERF, published in NUREG-2201, Probabilistic Risk Assessment and Regulatory 5
Decisionmaking: Some Frequently Asked Questions, issued September 2016 (NRC, 2016c).
6 The purpose of these figures in this appendix is to provide a general illustration of the 7
distribution of CDFs and LERFs. These figures depict the CDF and LERF for a subset of the 8
U.S. fleet of operating power reactors, based on information readily available through NRC 9
regulatory applications. As noted in NUREG-2201, the CDFs are based on 2016 estimates for 10 61 units from license amendment requests to change requirements or SAMA analyses as part 11 of the environmental evaluation conducted by license renewal applicants. The earliest result is 12 from a 2002 analysis, but over 80 percent of the results are from 2008 or later. The estimates 13 are based on PRAs with different scopes, for example, the majority included internal plus 14 external event initiators while a minority included internal event initiators only.
15 16 The point estimate for CDFs range from about 4x10-6 per reactor-year to approximately 1x10-4 17 per reactor-year, with a mean and median of about 5x10-5 per reactor-year. The point estimates 18 for LERFs range from about 8x10-8 per reactor-year to approximately 3x10-5 per reactor-year, 19 with a mean of approximately 4x10-6 per reactor-year and a median of about 3x10-6 per 20 reactor-year. The source information for these estimates typically do not include uncertainty 21 estimates. NUREG-2201 also notes that it is important to recognize:
22 23
[P]ast PRAs have consistently shown that potential vulnerabilities (and 24 therefore plant risk) are highly plant specific.
25 Design and operational changes addressing lessons identified by PRAs can 26 lead to significant changes in CDF...
27 The above estimates for total CDF are developed by adding the CDFs 28 estimated for different accident scenarios.
29 The CDF contributions from accidents caused by internal hazards (e.g.,
30 floods, fires) and external events (e.g., earthquakes, high winds, and external 31 floods) can be significant.
32 (Source: NUREG-2201, p. 36) 33 34 It is important to note that external events are sometimes out-of-scope or handled much less 35 rigorously than internal events (for example, in SAMA analyses for operating reactors). See 36 additional discussion in Section H.4.2, Sources of Information, and table notes under Tables 37 H-3 and H-4. Similar information is available for new and advanced reactors (see Section 38 H.5.2), with the exception that large release frequency is used instead of LERF.
39 40 As noted above, the analyst should access available risk information that is current at the time 41 of a future regulatory or cost-benefit analysis. Figures H-2 and H-3 provide an example based 42 on 2016 data for a subset of operating reactor units, with the aforementioned limitations.
43 44 45 46
H-11 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-2 Distribution of 2016 Point Estimates for Total CDF, U.S. Plants 2
(Source: NUREG-2201, Figure 4-3) 3 4
5 Figure H-3 Distribution of 2016 Point Estimates for LERF, U.S. Plants 6
(Source: NUREG-2201, Figure 5-2) 7
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-12 1
H.3.3 Common Analysis Elements 2
3 Risk (R) is, summed over the spectrum of potential accidents, the product of (1) the probability 4
(or frequency) (Pi) and (2) associated consequences (Ci) for each potential accident (i) in the 5
spectrum, as shown in the equation below:
6 7
=
8 9
Hence, estimating the public health (accident) risk and offsite economic consequences (offsite 10 property damage) risk in a cost-benefit analysis for a proposed action requires the estimation of 11 both (1) the change in probabilities (frequencies) and (2) the change in consequences 12 associated with accidents in the spectrum of relevant accidents. Therefore, the common 13 analysis elements include the following:
14 15 An accident sequence analysis to identify the relevant accidents 16 17 Quantification of frequencies associated with individual accident sequences for the 18 probability/frequency portion of the risk equation 19 20 Quantification of the public health and offsite economic consequence associated with 21 each accident sequence, for the consequence portion of the risk equation 22 23 The following sections discuss these elements in greater detail.
24 25 H.3.3.1 Accident Sequence Analysis 26 27 An accident sequence analysis systematically identifies risk-significant accident sequences and 28 quantifies their frequency. Logic models provide the probabilistic framework for assessing the 29 change in risk associated with a regulatory analysis alternative. These models consist of event 30 trees to identify the set of possible accident sequences that lead to fission product release and 31 rely on accident progression simulations performed for a specific accident sequence to 32 understand how a combination of successes and failures affects the facility. The following 33 examples are for a nuclear power plant, but the principles apply to all NRC-regulated facilities.
34 35 PRA Logic Model Structure 36 37 One PRA modeling approach is to construct logic models using event trees and fault trees. An 38 event tree represents different plant and operator responses in terms of sequences of undesired 39 system states, such as core damage or fission product release, that could occur following an 40 initiating event. The probabilistic (Level 1 and Level 2 frequency) portions of an accident 41 sequence analysis are assessed using Core Damage Event Trees (CDETs) and Accident 42 Progression Event Trees (APETs). A fault tree identifies different combinations of basic events 43 (e.g., initiating events; failures of systems, structures, and components; and human failure 44 events) that could lead to a system failure. Fault tree models are linked to the event tree 45 sequences and allow for the identification and evaluation of minimal cut setsthe minimum 46 combinations of events needed to result in an adverse end state of interest (e.g., core damage).
47 When linked together, these logic structures provide an integrated perspective that can capture 48 major system dependencies.
49
H-13 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Care should be taken to ensure that the modeling is sufficiently detailed and is technically 2
adequate to provide the needed confidence in the resultsfor its use in the regulatory analysis 3
and for its role in the integrated decision process, which is critical for coherent decision-making.
4 Because the standards and industry PRA programs are not prescriptive, there is some freedom 5
on how to model these logic structures. The choice of specific assumptions, a particular 6
approximation, or a modeling choice or simplification may, however, influence the results.
7 These underlying assumptions and approximations made in the development of the PRA model 8
give rise to uncertainty and should be explicitly identified and quantified to aid the 9
decisionmaker in understanding the results and the potential range of costs and benefits. The 10 treatment of uncertainty and sensitivity analysis are further discussed in Section H.6.
11 12 PRA Logic Model Level of Detail 13 14 Much like the scope, the level of detail of an NPP PRA model can vary, depending on its 15 intended application or use. The level of detail is defined by the degree to which (1) the actual 16 plant is modeled and (2) the unlimited range of potential accident scenarios is simplified.
17 Although the goal of a PRA is to represent the NPP as-designed, as-built, and as-operated as 18 realistically as practicable, some compromises are made to keep the PRA model manageable, 19 considering time and resource constraints.
20 21 For each of the technical elements that comprise a PRA model, the level of detail may vary by 22 the extent to which the following is true:
23 24 Plant systems and operator actions are credited in modeling plant-specific design and 25 operation 26 27 Plant-specific operating experience and data for the plants structures, systems, and 28 components are incorporated into the model 29 30 Realism (as opposed to intentional conservatism) is incorporated into analyses that 31 predict the expected plant and operator responses 32 33 Furthermore, the logic structures (e.g., event trees and fault trees) in the model are simplified 34 representations of the complete range of potential accident scenarios. Simplifications are made 35 through underlying assumptions and approximations such as (1) the consolidation into 36 representative hazard groups of initiating event causes and (2) the screening out of certain 37 equipment failure modes.
38 39 Although the level of detail needed for an NPP PRA model is largely dependent upon the 40 requirements associated with its intended use (e.g., a PRA should meet the relevant American 41 Society of Mechanical Engineers [ASME] and American Nuclear Society [ANS] PRA standards 42 for operating reactor licensing changes), at a minimum, it needs to be detailed enough to model 43 the major system dependencies and to capture the significant risk contributors.
44 45 The level of effort required to construct these logic models depends upon the availability of 46 information and preexisting models developed for the specific site of interest and on the amount 47 of information that is obtainable from the licensee. The NRC has developed SPAR models for 48 all NPPs used to support various risk-informed activities. However, depending upon the scope 49 of the regulatory analysis, these models may need to be expanded to address other hazards or 50 plant conditions. To the extent possible, the analyst should use existing information, in addition 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-14 to related research efforts,5 to complete the regulatory analysis efficiently. Qualitative insights 1
may be needed to supplement incomplete quantitative modeling.
2 3
Assumptions about which systems will be available (or should be probabilistically considered) 4 are dependent upon the type of initiating event being considered. For example, if the initiating 5
event is seismically induced, consideration should be given to whether a given safety system 6
realistically would be available. The assumptions used in developing the event trees should be 7
clearly delineated for the systems that are probabilistically considered. In constructing the event 8
trees, systems or modes of operations for which reliability data are not available should not be 9
credited or probabilistically considered. The analyst should document for reference these 10 assumptions and all hardware-related failure event probabilities that are incorporated in the 11 CDETs and APETs.
12 13 H.3.3.2 Quantification of Change in Accident Frequency 14 15 The change in accident frequency is a key factor for several of the cost-benefit analysis 16 attributes. Estimates of the change in accident frequencies resulting from a proposed NRC 17 action are based on the effects of the action on appropriate parameters in the accident 18 equation. Examples of these parameters might be system or component failure probabilities, 19 including those for the facilitys containment structure. The estimation process involves two 20 steps(1) identification of the parameters affected by a proposed NRC action, and 21 (2) estimation of the values of these affected parameters before and after the action takes 22 place.
23 24 The parameter values are substituted in the accident equation to yield the base-and 25 adjusted-case accident sequence frequencies. The sum of their differences is the reduction in 26 accident frequency caused by the proposed NRC action. The frequency of accident sequence i 27 initiated by event j is 28 29
=
30 31 where = the frequency, F, of minimal cut set k for accident sequence i initiated by event j 32 Source: (NRC, 1997b).
33 34 5
For example, related research efforts include SPAR external events modeling (https://saphire.inl.gov/current_models_public.cfm), fire risk research under National Fire Protection Association (NFPA) 805, Performance-Based Standard for Fire Protection for Light-Water Reactor Electric Generating Plants (current version) (https://www.nrc.gov/reactors/operating/ops-experience/fire-protection/protection-rule/protection-rule-overview.html), and generic issue evaluations (https://www.nrc.gov/about-nrc/regulatory/gen-issues/dashboard.html).
H-15 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 A minimal cut set represents a unique and minimum combination of occurrences at lower levels 1
in a structural hierarchy (e.g., component failures that are typically represented by basic events 2
in PRA model fault trees) needed to produce an overall occurrence (e.g., facility damage) at a 3
higher level. It takes the form of a product of these lower level occurrences. The affected 4
parameters comprise one or more of the multiplicative terms in the minimal cut sets. Thus, the 5
change in accident sequence frequency i, between the base model and the adjusted model that 6
incorporates the proposed action, is 7
8
9 10 Source: (NRC, 1997b) 11 12 The changes in accident frequency for each affected accident sequence are added. Reduction 13 in accident frequency is algebraically positive; increase is negative. This equation assumes that 14 the model structure remains valid for risk evaluations after a proposed action. It is possible for 15 a proposed action to result in a change to the model structure (e.g., by adding or removing top 16 events in an event tree). Therefore, in addition to potentially changing the values of parameters 17 that comprise a base-case set of minimal cut sets, a proposed action can change the structure 18 of the minimal cut sets and create new minimal cut sets that were not included in the base case.
19 This would require an evaluation beyond quantification of the above equation, which only 20 quantifies the change of frequencies of existing minimal cut sets.
21 22 Each accident sequence that ends in core damage is binned for further analysis into a plant 23 damage state with other core damage sequences having plant conditions that are expected to 24 result in similar accident progression behavior. The frequencies of the sequences with a core 25 damage end state are summed to estimate the CDF for an initiating event. The characteristics 26 that define each plant damage state bin comprise the initial conditions for the APET. Similarly, 27 the APETs evaluate the containment response to those sequences that result in core damage 28 and provide the frequencies of sequences with end states of release to the environment.
29 30 Source terms are binned into release categories based on release characteristics such as 31 magnitude and timing of release. Binning both the plant damage states, and source terms 32 reduces the total number of accident progression and consequence simulations that are 33 required. In summing the CDF and LERF/large release frequency, the analyst should consider 34 all significant accident sequences. Significant accident sequences, as defined in Regulatory 35 Guide 1.200, An Approach for Determining the Technical Adequacy of Probabilistic Risk 36 Assessment Results for Risk-Informed Activities (current version), are those that, when ranked, 37 compose 95 percent of the CDF or LERF, or that individually contribute more than 1 percent to 38 the CDF.
39 40 In practice, the computation of change in the frequency of CDF and release categories for both 41 the standard analysis and the major effort uses PRA software, such as Systems Analysis 42 Program for Hands-On Integrated Reliability Evaluations (SAPHIRE), are discussed in 43 Enclosure H-1, Description of Analytical Tools and Capabilities, to this appendix.
44 45 H.3.3.3 Quantification of Change in Consequences 46 47 Many analyses may assume that new consequence evaluations will not be needed. If the 48 change in risk can be captured through a change in accident sequence frequencies only, then 49 the overall risk equation can use the existing public health and economic consequence 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-16 assessments associated with those accident sequences. This assumption is embedded when 1
existing population dose and offsite economic consequence multipliers (e.g., population dose 2
factors in Section 5.3.2.1 of this NUREG) are used for severe accident sequences. However, if 3
a proposed action affects an accidents conditional consequences, then the risk quantification 4
approach should explicitly account for the change in conditional consequences, as noted at the 5
end of Section 5.3.2.1.1 of this NUREG. If the existing PRA model does not adequately capture 6
the change in risk associated with the proposed change, then the PRA model should be revised 7
to support the analysis.
8 9
Regulatory analyses involving large light-water reactors historically have been estimated using a 10 50-mile radius from the site (see Section 5.2.1 of this NUREG). The analyst chooses the 11 distance based on the potentially affected area (e.g., where offsite population dose and offsite 12 property damage is incurred). Offsite consequences for other distances6 have been considered 13 in recent detailed analyses where individual plants with site-specific information were evaluated.
14 Section H.5 and Enclosures H-4 through H-6 to this appendix discuss examples. For small 15 modular reactors and advanced reactors, the radius should be chosen based on design-specific 16 details, site characteristics, and precedents.
17 18 H.3.3.4 Identification and Estimation of Affected Parameters 19 20 An action may affect accident frequencies only, accident consequences only, or both accident 21 frequencies and consequences. Actions that may change existing PRA model structures 22 (e.g., by adding or removing events in an event tree or changing consequences of existing 23 accident sequences) will require additional analysis steps compared to actions that affect only 24 the relative frequencies of existing accident sequences and associated consequences.
25 26 If appropriate PRA models are available, these can be used to identify the affected parameters.
27 For example, all NPP PRA studies include accident sequences involving loss of emergency 28 alternating current power. If the minimal cut sets used in the analytical modeling of these 29 sequences contain parameters appropriate to an action related to loss of emergency alternating 30 current power, then these PRA studies would be appropriate for use in the analysis. In this 31 case, the analyst can readily identify the affected parameters and their estimated values.
32 33 Within the scope of an analysis, the identification of affected parameters may require more than 34 the direct use of existing PRA models. Existing studies may need to be modified. The effort 35 may involve (1) performing an expanded or independent analysis of the accident sequences 36 associated with an action, using previous studies only as a guideline, or (2) combining several 37 existing PRA studies to form a composite study more applicable to a generic action. Care 38 should be taken to ensure that assumptions, modeling, and uncertainty characterization are 39 appropriate and valid to support decisionmaking.
40 41 Assuming the analyst has identified affected parameters, the next step is to estimate the 42 base-and adjusted-case values of the affected parameters, which are then used to estimate the 43 base-and adjusted-case total accident sequence frequencies and associated consequences.
44 The sum of the differences between the base-and adjusted-cases is the change in accident 45 frequency, the consequence resulting from the action, or both.
46 47 In some cases, additional modeling is required, where identification of affected parameters 48 6
The analyst should also consider the capabilities and range of validity of analytical tools when selecting these distances.
H-17 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 requires the type of analysis associated with a much greater level of detail and, most likely, a 1
significantly expanded scope. NRC programs related to unresolved generic safety issues for 2
power reactors offer examples of where major efforts were required in the past. Such programs 3
tend to be multiyear tasks. The expected level of detail and quality of analysis should be 4
consistent with current standard practice and may entail peer review.
5
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-18 H.4 GRADED APPROACH TO ANALYSIS 1
2 As with most areas of NRCs regulation (e.g., NRCs Strategic Plan: Fiscal Years 2018-2022 3
[NRC, 2018a]), staff are expected to take a risk-informed approach to severe accident risk 4
analyses supporting regulatory analyses. NRCs Office of Nuclear Reactor Regulation Office 5
Instruction LIC-504, Integrated Risk-Informed Decision-Making Process for Emergent Issues 6
(NRC, 2014i) describes different levels of approach, namely a graded approach, to using risk 7
information that, while tailored to decision-making for emergent issues, is conceptually 8
appropriate to the use of risk information in regulatory analyses too. A graded approach is one 9
where the level of rigor applied depends on the importance, e.g., risk significance and 10 applicability (see for example, discussion in Management Directive 6.4, Generic Issues 11 Program [NRC, 2015g]). As noted in LIC-504, Regulatory Guide 1.174, and NUREG-1855, 12 Guidance on the Treatment of Uncertainties Associated with PRAs in Risk-Informed Decision 13 Making (NRC, 2017a), it is particularly important to assess uncertainties in the risk analyses 14 and understand how uncertainties may affect the comparison of risk measures with decision 15 criteria.
16 17 In some cases, an initial screening-type analysis may be sufficient to disposition the evaluation 18 of a potential regulatory action. For example, if it is necessary to show a substantial safety 19 benefit and possibly to get an initial assessment of whether a potential regulatory change may 20 be cost-beneficial, existing compilations of risk information may be sufficient to make the 21 determination (this would be analogous to answering yes to the question in NRCs LIC-504 22 Section 4.2.2, Is the Issue Clearly of Low Safety Significance? [NRC.2014i]). For such an 23 approach, the potential benefits should be maximized, and (if pursuing an initial cost-benefit 24 assessment) the potential costs minimized, to ensure that a potentially warranted action is not 25 unduly screened out. Furthermore, uncertainty in these screening or bounding-type analyses 26 and its potential impact should be considered.
27 28 In the absence of a new major-effort analysis, existing risk information would be used, e.g., by 29 selecting the maximum CDF for the class of affected plants and the highest known conditional 30 consequences within the class of affected plants. Current CDFs at the time of an analysis are 31 available, such as in the information sets used to create Figures H-2 and H-3 above. While the 32 conditional consequences may be harder to find, several sources of information (discussed in 33 Section H.5.2) exist and could provide the needed estimates. The highest conditional 34 consequences for a class of plants typically will be tied to the highest population sites. Both 35 10-mile-and 50-mile-radius populations should be considered for large light-water reactors; for 36 small modular reactors and advanced reactors, the radius could be chosen based on 37 design-specific details and precedence (such as EPZ and Protective Action Guides [PAGs]).
38 The joint consideration of a sites meteorological profile, population distribution, and licensed 39 thermal power (since total radiological releases for a given accident are expected to scale with 40 core power) is important. The offsite populations residing within 50 miles of the operating NPPs 41 in the United States varied from 180,000 to 17 million, according to the 2000 and 2010 42 censuses (NRC, 1996 and supplements). As of 2019, the licensed thermal power for individual 43 large light-water reactors in the United States varied from 1,700 megawatts thermal (MWt) to 44 4,400 MWt (NRC, 2019b).
45 46 As discussed in Section 5.3.2 of this NUREG, the estimation of the avoided public health effects 47 and avoided offsite economic consequences is calculated from current risk information from 48 existing studies. The avoided consequences are computed by multiplying the change in 49 frequency of each significant release category by its consequence metrics and then applying a 50
H-19 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 summation over all affected release categories. This approach should only be used if the staff 1
deems that existing risk studies adequately capture the accident scenarios, associated 2
frequencies and consequences, for the issue under consideration.
3 4
At the simplest level, the analysis assumes values of affected parameters are readily available 5
or can be derived easily. Sources of data that are readily accessible include existing PRA 6
studies, which provide parameter values in forms appropriate for accident frequency 7
calculations (e.g., frequencies for initiators and unavailability or demand failure probabilities for 8
subsequent failures of systems, structures, and components).
9 10 After identifying base and adjusted-case values for the parameters in the plant-risk equation 11 that are affected by the proposed regulatory action (see Section 5.3.2 of this NUREG), the 12 analyst calculates the change in accident frequency as the sum of the differences between the 13 base-and adjusted-case values for all affected accident sequences.
14 15 Uncertainties are prevalent in any risk assessment and should be addressed (see Section 16 H.6.3.1 for a discussion on different kinds of uncertainties). For example, an error factor on the 17 best estimate of the reduction in total accident frequency may be used to estimate high and low 18 values for the sensitivity calculations in the analysis for power reactor facilities. Past analyses 19 have used error factors of 5-10 or more, depending on the events analyzed7. Error factors from 20 the specific risk assessment being used, if available, or knowledge of typical error factors from 21 current analogous risk assessments, should be employed.
22 23 An analyst who is unable to identify affected parameters for an action can estimate changes in 24 accident frequency using professional judgment. Expert opinion also plays a prime role in 25 estimating adjusted-case parameter values. Typically, existing data are applied to yield 26 base-case values, leaving only engineering judgment for arriving at adjusted-case values.
27 Reaching consensus among multiple experts can increase confidence, and the magnitudes of 28 parameter values normally encountered in PRA studies can serve as rough guidelines.
29 30 At a more detailed level, but still within the scope of a standard analysis, the analyst may 31 conduct reasonably detailed statistical modeling or extensive data compilation when values of 32 affected parameters are not readily available. While existing PRA studies may provide some 33 data for use in statistical modeling, the level of detail required normally would be greater than 34 they could provide. Statistical modeling may use stochastic simulation methods and involve 35 statistical analysis techniques using extensive data.
36 37 NUREG/CR-2800, Guidelines for Nuclear Power Plant Safety Issue Prioritization Information 38 Development, issued September 1983 (NRC, 1983b), discusses the calculation of change in 39 core melt accident frequency for power reactors, and provides examples. Such calculations are 40 typical for a standard cost-benefit analysis. A useful reference is Nuclear Energy Institute 41 (NEI)-05-01, Revision A, Severe Accident Mitigation Alternatives (SAMA) Analysis Guidance 42 Document, issued November 2005 (NEI, 2005), because SAMA analyses follow a similar 43 process to that of regulatory and cost-benefit analyses. A SAMA analysis includes searches for 44 potential generic industry and plant-specific improvements to address important risk 45 contributors, and cost-benefit analyses to evaluate these potential improvements.
46 47 7 See for example: https://nrcoe.inl.gov/resultsdb/publicdocs/AvgPerf/ComponentUR2015.pdf
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-20 H.4.1. Example of Approach 1
2 The staff analysis summarized in Enclosure H-3, Summary of Detailed Analyses for 3
SECY-12-0157, Consideration of Additional Requirements for Containment Venting Systems 4
for Boiling Water Reactors with Mark I and Mark II Containments, provides an example of a 5
practical modern approach to what was historically called a standard analysis. To evaluate 6
the potential risk reduction benefit of the proposed action, the staff first reviewed insights from 7
available risk studies. These sources of risk information included (1) the IPEs completed in 8
response to Generic Letter 88-20 (NRC, 1988a, NRC, 1997a), (2) applicable risk-informed 9
license amendment requests, which in this case were the requests for integrated leak rate 10 testing (ILRT) (see Table 2 of NRC, 2012h), and (3) SAMA analyses submitted with license 11 renewal applications for operating NPPs (NRC, 1996, and supplements). The ILRT license 12 amendment requests were considered because they estimated post-core-damage containment-13 related risk benefits that informed the evaluation of potential benefits of installing containment 14 venting systems. The staff collected the following information from these sources:
15 16 Identification of the conditional containment failure probabilities from the class of plants 17 under consideration (e.g., boiling-water reactors [BWRs] with Mark I and Mark II 18 containments), for base-case conditions in the IPEs and ILRTs, as well as sensitivity to 19 extended ILRT intervals 20 21 Identification of dominant contributors to early containment failure 22 23 Evaluation of whether past SAMA analyses considered filtered severe accident venting, 24 and if so, whether they found it to be a potentially cost-beneficial plant improvement at 25 the time of the license renewal application 26 27 This evaluation of available risk insights contributed to the technical approach for evaluating 28 potential benefits by helping the staff to develop the branches on the event tree for sequence 29 evaluation and benefit quantification (see Enclosure H-3 to this NUREG for more details of this 30 analysis).
31 32 A safety goal evaluation is required as part of a regulatory analysis in which regulatory 33 alternatives are analyzed to determine whether they are generic safety enhancement backfits 34 subject to the substantial additional protection standard. To perform the safety goal evaluation, 35 the staff should analyze the regulatory alternatives to directly compare the potential safety 36 benefits to the QHOs for average individual early fatality risk and average individual latent 37 cancer fatality risk described in the Commissions Safety Goal Policy Statement8 (NRC, 1986).
38 To determine the relative costs and benefits, the analyst should compare each of the 39 alternatives to the regulatory baseline.
40 8
In 1986, the NRC published the Safety Goal Policy Statement, whose objective was to, establish goals that broadly define acceptable level of radiological risk to the public from nuclear power plant operation (NRC, 1986).
This policy stated two qualitative safety goals, supported by two quantitative objectives which are commonly called QHOs: (1) the risk to an average individual in the vicinity (1 mile) of a nuclear power plant of prompt fatalities that might result from reactor accidents should not exceed one-tenth of one percent (0.1 percent) of the sum of prompt fatality risks resulting from other accidents to which members of the U.S. population are generally exposed; and (2) the risk to the population in the area (within 10 miles) near a nuclear power plant of cancer fatalities that might result from nuclear power plant operation should not exceed one-tenth of one percent (0.1 percent) of the sum of cancer fatality risks resulting from all other causes. Since the QHOs are tied to the prompt fatality risks and cancer fatality risks from all other causes in the U.S., the actual QHOs can change over time.
H-21 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
A successful strategy used in the past for the safety goal evaluation is to employ a high-level 2
and conservatively high estimate to maximize the potential benefit of a regulatory alternative for 3
comparison to the regulatory baseline, to determine whether an alternative may meet the 4
substantial safety benefit threshold. For example, in the Containment Protection and Release 5
Reduction (CPRR) regulatory analysis described in Enclosure H-4 to this appendix, the staff 6
performed a screening analysis for the average individual latent cancer fatality risk QHO for the 7
relevant plantsall U.S. BWRs with Mark I containments (a total of 22 units at 15 sites) and 8
Mark II containments (a total of eight units at five sites). For this screening analysis, the staff 9
developed a conservatively high estimate of the frequency-weighted average of an individual 10 latent cancer fatality risk within 10 miles of the plant using the following parameter values:
11 12 An extended loss of alternating current power (ELAP)9 frequency value of 7x10-5 per 13 reactor-yearwhich represented the highest value among all BWRs with Mark I and 14 Mark II containments 15 16 A success probability for flexible coping strategies (FLEX) equipment of 0.6 per 17 demandwhich assumed the implementation of FLEX will successfully mitigate an 18 accident involving an ELAP 6 out of 10 times 19 20 A conditional average individual latent cancer fatality risk of 2x10-3 per eventwhich 21 represented the highest value among all BWRs with Mark I and Mark II containments 22 from the detailed analyses 23 24 These assumed parameter values resulted in a conservatively high estimate of a 25 frequency-weighted individual latent cancer fatality risk within 10 miles of approximately 26 7x10-8 per reactor-year (labelled as High-Level Conservative Estimate in Figure H-4), which is 27 greater than an order of magnitude less than the QHO for an average individual latent cancer 28 fatality risk of approximately 2x10-6 per reactor-year. This conservatively high estimate did not 29 take credit for any of the accident strategies and capabilities described in the 20 CPRR 30 alternatives and subalternatives. Figure H-4 shows the incremental benefit (in terms of 31 individual latent cancer fatality risk on the y-axis) for each alternative on the x-axis-32 subalternatives within Alternatives 2 to 4 compared to the status quo, Alternative 1.
33 34 Because the conditional early fatality risk was essentially zero, a comparable analysis for the 35 early fatality QHO was not needed.
36 37 9
An ELAP is defined as an SBO that lasts longer than the SBO coping duration specified in 10 CFR 50.63, Loss of all alternating current power.
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-22 1
Figure H-4 Uncertainty in Average Individual Latent Cancer Fatality Risk (0-10 miles) in 2
the 2015 Containment Protection and Release Reduction Regulatory 3
Analysis 4
(Source: SECY-15-0085, Enclosure, Figure 3-3) 5 6
H.4.2. Sources of Information 7
8 As noted in the Background section above, historically, NUREG-1150, Severe Accident Risks:
9 An Assessment for Five U.S. Nuclear Power Plants, issued December 1990 (NRC, 1990b),
10 and supplementary studies based on NUREG-1150, were the main sources of information for 11 the NRCs typical regulatory analyses. The analyst should consult the SPAR Program owner to 12 collect the most current risk information and insights at the time of a new analysis. For 13 example, the NRC maintains SPAR models for use in the Reactor Oversight Process and other 14 risk-informed regulatory activities, as noted in Section H.3.3.1 and discussed further in 15 Enclosure H-1. Risk-informed applications and SAMA analyses are other examples of sources 16 of information, as discussed further below.
17 18
H-23 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Risk-informed license amendment requests10 cover a range of plant and risk scenarios that 1
should be consulted according to the risk scope under consideration. The 10 CFR 50.54(f) 2 letter responses are another source of information for a variety of plant and accident types. For 3
example, in response to the lessons learned from the Fukushima Dai-ichi accident, the NRC 4
issued a 10 CFR 50.54(f) letter (NRC, 2012i) to all operating NPP licensees to reevaluate the 5
seismic and flooding hazards at their sites using updated seismic and flood hazard information 6
and present-day regulatory guidance and methodologies and, if necessary, to request that they 7
perform a risk evaluation. The responses to the letter provide post-2012 seismic CDF and 8
seismic LERF information for operating NPPs.11 9
10 The SAMA analyses may provide useful information since SAMA analyses (1) cover all nuclear 11 steam supply systems (NSSS) and containment types for the operating fleet of NPPs (see 12 Table H-2), as well as new reactors under construction (e.g., SAMA and SAMDA analyses for 13 the advanced passive 1000 [AP1000]), and (2) have been evaluated for the known risk profile 14 (e.g., different accident initiators and scenarios) for each subject plant at the time of analysis.
15 The SAMA analyses report on the rank of contributors to CDF (see the example in Table H-3),
16 the rank of contributors to LERF (occasionally), the rank of contributors of different release 17 categories or containment release modes to population dose (see example in Table H-4), and 18 the maximum attainable benefit in terms of the offsite dose and offsite economic cost risks 19 (within a 50-mile radius from the plant) that would be saved if all potential accidents could be 20 eliminated at the plant. These analyses12 are documented in license applications and in the 21 staffs environmental evaluations.13 As noted in the main body Section 2, the SAMA analyses 22 documented in the NUREG-1437 supplements report quantitative internal events CDFs, and 23 external events multipliers in the range of 1.2 to 12, with an average value of 3.2 (based on 24 51 of the 57 supplements published between 1999 and 2016 that reported external events 25 multipliers for 82 individual reactors). This means that the total CDF was estimated to be 1.2 to 26 12 times the internal events CDF, with an average value of 3.2 times the internal events CDF.
27 Additional SAMA analyses have been performed for design certifications and combined license 28 new reactor reviews.14 When using data from SAMA analyses, the analyst should be aware 29 that the agency undertakes SAMA analyses to meet NEPAs hard look requirement; as a 30 result, some aspects of SAMA analyses may require further consideration before the agency 31 relies on them to meet its obligations under the Atomic Energy Act of 1954, as amended.
32 33 Table H-2 Reactors with Published SAMA Analyses 34 Containment Type NSSS Type Plant Name Licensed Thermal Power (MWt)
NUREG-1437a, b Supplement Number (unless noted otherwise)
Dry, Ambient B&W Lowered Loop Arkansas 1 2568 3
Oconee 1 2568 2
Oconee 2 2568 2
Oconee 3 2568 2
B&W Raised Loop Davis-Besse 2817 52 CE Arkansas 2 3026 19 10 For example, see risk-informed technical specification changes discussed here:
https://www.nrc.gov/reactors/operating/licensing/techspecs/risk-management-tech-specifications.html 11 https://www.nrc.gov/reactors/operating/ops-experience/japan-dashboard/seismic-reevaluations.html 12 https://www.nrc.gov/reactors/operating/licensing/renewal/applications.html contains links to all NPP license renewal applications and the NRCs reviews.
13 https://www.nrc.gov/reading-rm/doc-collections/nuregs/staff/sr1437/
14 https://www.nrc.gov/reactors/new-reactors.html
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-24 Containment Type NSSS Type Plant Name Licensed Thermal Power (MWt)
NUREG-1437a, b Supplement Number (unless noted otherwise)
Calvert Cliffs 1 2737 1
Calvert Cliffs 2 2737 1
Millstone 2 2700 22 Palisades 2565 27 Saint Lucie 1 3020 11 Saint Lucie 2 3020 11 Waterford 3 3716 59 Large Dry, Ambient CE 80 Palo Verde 1 3990 43 Palo Verde 2 3990 43 Palo Verde 3 3990 43 Mark I GE 2 Nine Mile Point 1 1850 24 GE 3 Dresden 2 2957 17 Dresden 3 2957 17 Monticello 2004 26 Quad Cities 1 2957 16 Quad Cities 2 2957 16 GE 4 Browns Ferry 1 3952 21 Browns Ferry 2 3952 21 Browns Ferry 3 3952 21 Brunswick 1 2923 25 Brunswick 2 2923 25 Cooper 2419 41 Duane Arnold 1912 42 Fermi 2 3486 56 FitzPatrick 2536 31 Hatch 1 2804 4
Hatch 2 2804 4
Hope Creek 1 2902 45 Peach Bottom 2 4016 10 Peach Bottom 3 4016 10 Mark II GE 4 Limerick 1 3515 49 Limerick 2 3515 49 Susquehanna 1 3952 35 Susquehanna 2 3952 35 GE 5 Columbia 3544 47 La Salle 1 3546 57 La Salle 2 3546 57 Nine Mile Point 2 3988 24 Mark III GE 6 Grand Gulf 1 4408 50 River Bend 1 3091 58 Dry, Ambient Westinghouse 2-loop Ginna 1775 14 Point Beach 1 1800 23
H-25 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Containment Type NSSS Type Plant Name Licensed Thermal Power (MWt)
NUREG-1437a, b Supplement Number (unless noted otherwise)
Point Beach 2 1800 23 Prairie Island 1 1677 39 Prairie Island 2 1677 39
- Dry, Subatmospheric Westinghouse 3-loop Beaver Valley 1 2900 36 Beaver Valley 2 2900 36 North Anna 1 2940 7
North Anna 2 2940 7
Surry 1 2587 6
Surry 2 2587 6
Dry, Ambient Westinghouse 3-loop Farley 1 2775 18 Farley 2 2775 18 Harris 1 2948 33 Robinson 2 2339 13 Summer 2900 15 Turkey Point 3 2644 5
Turkey Point 4 2644 5
Dry, Ambient Westinghouse 4-Loop Braidwood 1 3645 55 Braidwood 2 3645 55 Byron 1 3645 54 Byron 2 3645 54 Callaway 3565 51 Indian Point 2 3216 38 Indian Point 3 3216 38 Millstone 3 3650 22 Salem 1 3459 45 Salem 2 3459 45 Seabrook 1 3648 46 South Texas 1 3853 48 South Texas 2 3853 48 Vogtle 1 3626 34 Vogtle 2 3626 34 Wolf Creek 1 3565 32 Ice Condenser Westinghouse 4-Loop Catawba 1 3469 9
Catawba 2 3411 9
D.C. Cook 1 3304 20 D.C. Cook 2 3468 20 McGuire 1 3411 8
McGuire 2 3411 8
Sequoyah 1 3455 53 Sequoyah 2 3455 53 Watts Bar 2 3411 NUREG-0498, Supp. 2c
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-26 Containment Type NSSS Type Plant Name Licensed Thermal Power (MWt)
NUREG-1437a, b Supplement Number (unless noted otherwise)
AP1000 Westinghouse 2-Loop Vogtle 3d NUREG-1872d Vogtle 4d NUREG-1872d a Information current as of 2019 1
b NUREG-1437 and supplements are available at: https://www.nrc.gov/reading-rm/doc-2 collections/nuregs/staff/sr1437/
3 c NRC, 2013i.
4 d Under construction; NUREG-1872, Final Environmental Impact Statement for an Early Site Permit (ESP) at the 5
Vogtle ESP Electric Generating Plant Site, issued August 2008 (NRC, 2008).
6 7
Table H-3 Salem Nuclear Generating Station Core Damage Frequency for Internal 8
Events at Power 9
Initiating Event CDF1 (per year)
% Contribution to CDF2 Loss of Control Area Ventilation 1.8 x 10-5 37 Loss of Offsite Power (LOOP) 8.1 x 10-6 17 Loss of Service Water 6.6 x 10-6 14 Internal Floods 4.5 x 10-6 9
Transients 4.0 x 10-6 8
Steam Generator Tube Rupture (SGTR) 2.7 x 10-6 6
Loss of Component Cooling Water (CCW) 1.0 x 10-6 2
Anticipated Transient Without Scram (ATWS) 7.4 x 10-7 2
Loss of 125V DC Bus A 6.9 x 10-7 2
Others (less than 1 percent each)3 1.8 x 10-6 4
Total CDF (internal events at power)4 4.8 x 10-5 100 1 Calculated from Fussel-Vesely risk reduction worth (RRW) provided in response to NRC staff RAI 1.e 10 (PSEG, 2010a).
11 2 Based on internal events CDF contribution and total internal events CDF.
12 3 CDF value derived as the difference between the total Internal Events CDF and the sum of the individual internal 13 events CDFs calculated from RRW.
14 4 The results only covers a fraction of the total plant risk profile, so their usefulness for regulatory decision-making 15 may be limited for situations where the analysis is evaluating changes involving not at power or external events.
16 (Source: NUREG-1437, Supplement 45, Table F-1) 17 18 19
H-27 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-4 Salem Nuclear Generating Station Breakdown of Population Dose by 1
Containment Release Mode 2
Containment Release Mode Population Dose (Person-Rem1 Per Year)
Percent Contribution2 Containment overpressure (Late) 42.9 55 Steam generator rupture 31.9 41 Containment isolation failure 2.3 3
Containment intact 0.2
<1 Interfacing system Loss-of-Coolant Accident (LOCA) 0.6
<1 Catastrophic isolation failure 0.4
<1 Basemat melt-through (late)
Negligible Negligible Total3,4 78.2 100 1 One person-rem = 0.01 person-Sv 3
2 Derived from Table E.3-7 of the ER (PSEG 2009).
4 3 Column totals may be different due to rounding.
5 4 The results only covers a fraction of the total plant risk profile, so their usefulness for regulatory decision making 6
may be limited for situations where the analysis is evaluating changes involving not at power or external events.
7 (Source: NUREG-1437, Supplement 45, Table F-2) 8 9
The State-of-the-Art Reactor Consequence Analyses (SOARCA), (see Enclosure H-2 to this 10 appendix) is another source of information for potential offsite public health consequences 11 within the scope of the severe accident scenarios studied for three operating reactor types in 12 the United States.15 SOARCA analyses, including uncertainty analyses, were conducted for 13 short-term and long-term SBO accidents at a BWR with a Mark I containment in Pennsylvania; 14 a three-loop Westinghouse NSSS pressurized-water reactor (PWR) with a subatmospheric 15 large, dry containment in Virginia; and a four-loop Westinghouse NSSS PWR with an ice 16 condenser containment in Tennessee. Deterministic analyses were also conducted for an 17 interfacing systems loss-of-coolant accident at the PWR with a large, dry containment.
18 Consequence results were reported as individual latent cancer risks and individual early fatality 19 risks for different radial rings out to 50 miles from the site. The SOARCA studies focused on 20 accident progression, source term, and conditional consequences should the postulated 21 accidents occur. The project did not include within its scope new work to calculate the 22 frequencies associated with the postulated severe accidents. And just like information from 23 modern plant-specific risk-informed license amendment requests, or plant-specific SAMA 24 analyses, the SOARCA studies were conducted for specific reactor types and sites.
25 26 15 The SOARCA analyses are documented in a series of NUREG and NUREG/CR reports (NRC, 2012a; NRC, 2012j; NRC, 2013a; NRC, 2013b; NRC, 2014a; NRC, 2014b; NRC, 2016b; NRC, 2019a; NRC, 2020).
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-28 H.5 MAJOR-EFFORT ANALYSIS 1
2 When additional rigor is required, a major-effort analysis is performed. Enclosures H-4 3
through H-6 to this appendix summarize the major-effort regulatory analyses that the staff 4
completed in the 2013 to 2015 timeframe. This section summarizes approaches and 5
considerations for the common technical elements in a major-effort regulatory analysis: accident 6
sequence analysis, accident progression (Level 2 PRA) analysis, and offsite consequence 7
(Level 3 PRA) analysis.
8 9
H.5.1 Accident Sequence Analysis 10 11 A major-effort analysis should begin with an accident sequence analysis. The analyst should 12 consider the following factors during the development of the technical approach for selecting the 13 relevant set of accident sequences:
14 15 The risk evaluation should provide risk metrics for all regulatory analysis subalternatives 16 and do so according to the approved scope, schedule, and allocated resources.
17 18 Consistent with the NRCs regulatory analysis guidelines, the risk evaluation should 19 provide fleet-average risk estimates. Therefore, the technical approach should consider 20 the impacts of plant-to-plant variability (for example, see Section H.6.2.2).
21 22 The staff should leverage existing relevant sources of accident sequence information 23 and develop new information where required.
24 25 The analyst should develop CDETs to (1) model the impact of equipment failures and 26 operator actions occurring before core damage that affect severe accident progression 27 and the probability that regulatory alternatives are successfully implemented, (2) match 28 the initial and boundary conditions used in the thermal-hydraulic simulation of severe 29 accidents in MELCOR, and (3) consider mitigating strategies for beyond-design-basis 30 external events, as applicable.
31 32 The analyst should develop APETs to model regulatory alternatives.
33 34 Enclosures H-3 through H-6 to this appendix include discussions of the accident sequence 35 analyses for three detailed regulatory analyses. As discussed in Enclosure H-4 to this 36 appendix, analysts successfully used a modular approach to develop the CDETs and APETs, 37 as shown in Figure H-5. This modeling approach streamlined the development of risk estimates 38 for the CPRR technical basis rulemaking and provides a good example for future detailed 39 analyses. Enclosure H-1 to this appendix describes the NRC-sponsored software, SAPHIRE.
40 SAPHIRE can be used for accident sequence modeling with CDETs and APETs and frequency 41 analysis.
42
H-29 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-5 Modular Approach to Event Tree Development in CPRR Analysis 2
(Source: NUREG-2206, issued March 2018, Figure 2-1) 3 4
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-30 H.5.2 Severe Accident Progression Analysis 1
2 The next step of a major-effort analysis is to complete a severe accident progression and 3
source term analysis, analogous to a Level 2 PRA. The objective of the severe accident 4
progression analysis is to generate a technical basis quantitatively characterizing thermal and 5
mechanical challenges to engineered barriers to fission product release to the environment.
6 This analysis provides a chronology of postulated accidents resulting in significant damage to 7
reactor fuel and generates quantitative estimates of a radioactive material release to the 8
environment. The staff has used the MELCOR code16 (Humphries et al., 2015), described in 9
Enclosure H-1 to this appendix, to model accident progression and fission product release 10 estimates for each of the selected accident scenarios in the detailed analyses.
11 12 The two broad purposes for conducting MELCOR calculations are: (1) to evaluate reactor 13 systems and containment thermal-hydraulics under severe accident conditions, and (2) to 14 assess the timing and magnitude of fission products released to the environment. Three 15 outputsthe containment temperature and pressure signatures, along with hydrogen 16 distribution through the containment and reactor buildingprovide information to assess the 17 status of reactor plant and containment integrity under varying postulated conditions. This 18 information may provide the basis for investigating other regulatory subalternatives. Analysts 19 use the timing and magnitude of fission product release information to characterize the source 20 terms in the consequence analysis described in Section H.5.3.
21 22 The MELCOR calculations are deterministic in nature and simulate different possible outcomes 23 or plant damage states, given the initial conditions that are specified in the accident sequence 24 analysis. The analyst should choose representative plant models based on the requirements of 25 the regulatory analysis (e.g., reflective of the relevant class(es) of NSSSs, containments, and 26 operational features). For efficiency, the representative MELCOR plant models can use existing 27 input decks developed for recent studies when available and relevant. For example, the 28 regulatory analyses discussed in Enclosures H-3 and H-4 to this appendix started with the 29 SOARCA Peach Bottom Atomic Power Station input deck for Mark I containments.
30 31 H.5.2.1 Sources of Information 32 33 NUREG/CR-7008, MELCOR Best Practices as Applied in the SOARCA Project, issued 34 August 2014 (NRC, 2014a), describes the best practices in modeling approach and parameter 35 selections that support the best estimate analyses in the 2012 SOARCA project, for a General 36 Electric BWR with a Mark I containment and a Westinghouse 3-loop PWR with a large, dry, 37 subatmospheric containment. The input models should follow the guidance of 38 NUREG/CR-7008, supplemented with updates and insights from the most recent MELCOR 39 analyses available (e.g., later SOARCA studies, such as NUREG/CR-7245, State-of-the-Art 40 Reactor Consequence Analyses (SOARCA) Project: Sequoyah Integrated Deterministic and 41 Uncertainty Analyses, issued 2019 (NRC, 2019a), for a Westinghouse 4-loop PWR with an ice 42 condenser containment, and NUREG/CR-7155, State-of-the-Art Reactor Consequence 43 Analyses Project: Uncertainty Analysis of the Unmitigated Long-Term Station Blackout of the 44 Peach Bottom Atomic Power Station, issued May 2016 (NRC, 2016b), and future studies, such 45 as the NRCs Site Level 3 PRA,17 for a Westinghouse 4-loop PWR with a large, dry 46 containment).
47 48 16 http://melcor.sandia.gov/
17 https://www.nrc.gov/about-nrc/regulatory/research/level3-pra-project.html
H-31 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Each operating NPP has an updated final safety analysis report that describes the facilitys 1
design bases and technical specifications and provides a safety analysis of each plant system 2
(10 CFR 50.34(b)). The updated final safety analysis report describes plant components and 3
containment features. The analyst can use this information to construct the MELCOR model.
4 5
IPEs provide information on the types of accidents that have a potential for occurring and the 6
location of failures. As previously discussed, each operating plant has one of these risk 7
analyses for internal events and many have IPEEEs.
8 9
Severe accident management guidelines are a source of information for characterizing operator 10 and plant response to severe accidents. These guidelines are developed by the utility and 11 provide guidance for operator actions in the event of a severe accident. These guidelines 12 contain strategies to stop or slow the progression of fuel damage, maintain containment, and 13 mitigate radiological releases.
14 15 H.5.2.2 MELCOR Modeling Approach 16 17 An accident progression analysis should be a collection of simulations of specific accident 18 sequences that is conducted to understand how a regulatory alternative affects the plant and 19 estimate the fission product release (source term) resulting from the accident sequence.
20 21 A MELCOR calculation matrix is developed to delineate runs evaluating each regulatory 22 analysis alternative, the various potential plant lineups, and the sensitivity analyses performed 23 for pre-and post-core damage mitigation measures. The calculations should clearly state the 24 initial and boundary conditions for the analysis and base the model nodalization on the specific 25 events that are being examined. The calculations should line up with APET and CDET 26 sequences in the accident sequence analysis.
27 28 Each accident sequence is binned into a release category that is represented by a MELCOR 29 source term. MelMACCS, which provides an interface between MELCOR and MACCS, can 30 read a MELCOR source term and provide the following data for each source term:
31 32 Time-dependent release fraction of chemical groups18 33 34 Time-independent distribution by particle size diameter for 10 aerosol size bins 35 characterized by geometric mean diameters 36 37 Height of each MELCOR release pathway 38 39 Time-dependent data needed to estimate buoyant plume rise, including rate of release 40 of sensible heat (W), mass flow (kg/s), and gas density (kg/m3) 41 42 The MELCOR source terms become input for the next step of the analysis, which are used to 43 estimate the offsite consequences using the MELCOR Accident Consequence Code System 44 (MACCS) suite of codes.
45 46 18 For example, Noble Gases (Xe), Alkali Metals (Cs), Alkali Earths (Ba), Halogens (I), Chalcogens (Te), Platinoids (Ru), Early Transition Elements (Mo), Tetravalents (Ce), and Trivalents (La)) for each MELCOR release pathway
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-32 H.5.3 Offsite Consequence Analysis 1
2 Similar to the MELCOR analysis, the consequences discussed here are conditional and do not 3
factor in the probability of release. The MACCS suite of codes19 is the NRCs code system for 4
performing offsite consequence analyses for severe accident risk assessments. The NRC uses 5
MACCS to analyze hypothetical accident scenarios, and almost all parameters in the code may 6
be modified. This functionality provides substantial flexibility and allows for the characterization 7
of uncertainties. Enclosure H-1 to this appendix provides more details on the MACCS code and 8
its capabilities.
9 10 H.5.3.1 Sources of Information 11 12 Similar to the MELCOR SOARCA best practices, NUREG/CR-7009, MACCS Best Practices as 13 Applied in the State-of-the-Art Reactor Consequence Analyses (SOARCA) Project, issued 14 August 2014 (NRC, 2014b), describes the parameter selections that supported the 15 best-estimate MACCS analyses in the 2012 SOARCA study. The MACCS input models should 16 follow the guidance of NUREG/CR-7009, supplemented with updates and insights from the 17 most recent MACCS analyses (e.g., later SOARCA studies, such as NUREG/CR-7245 and 18 NUREG/CR-7155) and guidance. NUREG/CR-4551, Volume 2, Revision 1, Part 7, Evaluation 19 of Severe Accident Risks: Quantification of Major Input Parameters: MACCS Input, issued 20 December 1990 (NRC, 1990c), describes the development of shielding parameters for 21 NUREG-1150 is in greater detail.
22 23 H.5.3.2 MACCS Modeling Approach 24 25 There is considerable variation in site characteristics, such as population size and distribution, 26 land use, economic values, weather, and emergency response characteristics (e.g., road 27 networks, use of potassium iodide). Site-specific models historically have been developed for 28 plant and containment types and then adapted using a series of sensitivity calculations to 29 assess the potential impact of the site-specific parameters on the results. For efficiency, the 30 analyst can use existing MACCS input decks developed for recent studies when available and 31 relevant. For example, the regulatory analyses discussed in Enclosures H-3 and H-4 to this 32 appendix started with the SOARCA Peach Bottom MACCS input deck.
33 34 Source Term Characterization 35 36 The source terms developed from the severe accident progression analysis with similar release 37 fractions and release timing characteristics may be binned to reduce the number of MACCS 38 cases that must be run. The binning should be based, at a minimum, on cumulative cesium and 39 iodine release fractions and the warning times associated with each source term. Historically, 40 the cesium group has been the most important for long-term offsite consequences (e.g., latent 41 cancer fatality risk), and the iodine group has been the most important for early offsite 42 consequences (e.g., early fatality risk).
43 44 The MelMACCS code20 in the MACCS suite of codes is used to create a MACCS input file to 45 represent the radiological source term developed using MELCOR. MelMACCS allows the user 46 47 19 https://maccs.sandia.gov/
20 https://maccs.sandia.gov/melmaccs.aspx
H-33 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 to associate the MELCOR mass values with an ORIGEN output to convert masses of chemical 1
classes to activities of individual radionuclides. In addition, the code needs the following data to 2
characterize each source term:
3 4
Radionuclide releases are divided into hourly segments to be consistent with the hourly 5
meteorological observations. If meteorological sampling is being used, the most 6
risk-significant plume should be identified to align the release with the weather data for 7
each weather bin. This is often taken to be the plume segment with the highest iodine 8
chemical group release fraction.
9 10 Building height and width are used to estimate the initial horizontal and vertical plume 11 dispersion caused by building wake effects.
12 13 Ground height in the MELCOR reference frame is used to adjust the MELCOR release 14 heights relative to grade.
15 16 Reference time, which is the difference between accident initiation time in MELCOR and 17 scram time. This value, which is used to properly account for decay and ingrowth of 18 radioactivity within MACCS, is usually zero but may be non-zero for some MELCOR 19 simulations.
20 21 Site and Meteorological Data 22 23 MACCS uses a polar grid to model the exposures to people, land contamination, and protective 24 actions of people and land. MACCS allows the user to choose 16, 32, 48, or 64 angular sectors 25 for grid division. The analyst should choose 64 angular sectors to provide the greatest 26 resolution. MACCS allows the user to divide the grid into a maximum of 35 radial rings, at 27 specified radii from the plant. The boundaries are selected to be consistent with certain areas of 28 interest. For example, for large LWR accidents, a radial boundary should be set at roughly 29 1 mile from the approximated site boundary to evaluate individual early fatalities for which the 30 NRCs early fatality QHO applies (NRC, 1986). This boundary is set at 10 miles to approximate 31 the plume exposure EPZ and latent fatality QHO, and at 50 miles to capture the majority of 32 radiological and economic consequences.
33 34 The SecPop preprocessor code in the MACCS suite of codes is typically used to generate 35 site-specific population and the economic data required for consequence calculations.
36 Population data should be scaled forward to the year of interest from the year of the census 37 data contained in SecPop using population growth data from the U.S. Census Bureau.
38 Additionally, the economic values contained in SecPop are from the U.S. Department of 39 Agriculture and U.S. Department of Commerce and should be scaled forward from the base 40 year data to the year of interest, using the consumer price index for all urban consumers.
41 42 The analyst should obtain raw weather data for the representative site from the site 43 meteorological towers for at least 2 full calendar years. Even though only 1 year of weather 44 data is necessary to complete the calculation, multiple years are beneficial for comparison to 45 ensure that the year selected is not anomalous (e.g., an abnormally dry or rainy year). The 46 inherent assumption in using historical data to quantify the consequences of a future event is 47 that future weather data will be statistically similar to historical data. The most complete year of 48 data should be chosen, and any missing data filled in by NRC meteorologists in accordance 49 with the U.S. Environmental Protection Agencys (EPAs) EPA-454/R-99-005, Meteorological 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-34 Monitoring Guidance for Regulatory Applications, issued February 2000 (EPA, 2000). The 1
methodology described in NUREG-0917, Nuclear Regulatory Commission Staff Computer 2
Programs for Use with Meteorological Data, issued July 1982 (NRC, 1982b), is used to perform 3
quality assurance evaluations of all meteorological data. In accordance with Regulatory 4
Guide 1.23, Meteorological Monitoring Programs for Nuclear Power Plants (current version),
5 the completeness of the recorded data (the data recovery rate) should be greater than 6
90 percent for the wind speed, wind direction, and atmospheric stability parameters. The 7
nonuniform bin sampling approach may be used to capture the effects of variable weather, 8
consistent with modeling best practices and recent consequence analyses.
9 10 Protective Action Modeling 11 12 EPA-400/R-17/001, PAG Manual: Protective Action Guides and Planning Guidance for 13 Radiological Incidents, issued January 2017, describes the emergency phase as the beginning 14 of a radiological incident when immediate decisions for effective use of protective actions are 15 required and must therefore be based primarily on the status of the radiological incident and the 16 prognosis for worsening conditions (EPA, 2017). Offsite response organization emergency 17 plans are required to include detailed evacuation plans for the plume exposure EPZ (NRC and 18 FEMA, 1980). Site-specific information should be obtained from offsite response organization 19 emergency response plans and the licensees evacuation time estimate (ETE) reports to 20 support the development of timelines for protective action implementation. The protective action 21 modeling assumptions have an important impact on offsite consequences.
22 23 MACCS input parameters related to evacuation modeling are taken primarily from the 24 site-specific ETE reports, which the licensee develops and updates under 10 CFR 50.47 (b)(10).
25 ETEs provide the time required to evacuate various sectors and distances within the EPZ for 26 transient and permanent residents, and these times are used to develop response timing and 27 travel speeds for evacuating cohorts21 in MACCS.
28 29 Important information in an ETE report includes demographic and response data for four 30 population segments, which may be readily converted into cohorts, if appropriate. These 31 population segments are (1) permanent residents and transient population, 32 (2) transit-dependent permanent residents (e.g., people who do not have access to a vehicle or 33 are dependent upon help from outside the home to evacuate), (3) special facility residents 34 (e.g., people in nursing homes, assisted living centers, hospitals, jails, prisons), and (4) schools, 35 including all public and private educational facilities within the EPZ. In general, delineating the 36 population into more cohorts (beyond these four) allows greater fidelity in modeling the 37 emergency response of the public. In recent practice, the staff has further divided the ETE 38 cohorts into additional groups (e.g., in order to separate the 10 percent of the permanent 39 general population who may evacuate later than the other 90 percent of the general population).
40 41 The licensees ETE report typically includes about 10 scenarios that vary by season, day of the 42 week, time of day, and weather conditions, as well as other EPZ-specific situations such as 43 special events. The ETEs do not consider most external events and their impact on road 44 infrastructure, and it is important for the analyst to account for these impacts in the model. The 45 Sequoyah SOARCA analysis provides an example of how the impact of seismic events may be 46 considered in MACCS modeling (NRC, 2019a), if seismic events are important for the scope of 47 accidents under consideration.
48 21 As explained in more detail in Enclosure H-1 to this appendix, a cohort in MACCS is a group that is modeled as behaving similarly (e.g., evacuating at the same time and speed).
H-35 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
In modeling the early phase relocation actions, the dose criteria to trigger the actions should be 2
consistent with the current EPA PAGs. In MACCS, emergency phase relocation is modeled 3
with two user-specified dose criteria to trigger the action and a relocation time for the population 4
affected by each dose. This modeling should consider site-specific features such as source 5
term, site information, and local demographics.
6 7
Although decisions about cleanup and reoccupation of affected areas would involve both 8
radiological and non-radiological considerations, it is customary in MACCS to use the dose 9
criteria for intermediate phase relocation as a surrogate for decisions about long-term 10 habitability. In determining the relocation and habitability dose criteria for the intermediate and 11 long-term phases, state-specific guidance for relocation following the early phase (as a 12 surrogate for decisions regarding habitability) should be followed when available. Absent 13 state-specific guidance, the analyst should use the EPA relocation PAGs.
14 15
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-36 H.6 SUPPLEMENTAL ANALYSES 1
2 Much like other parts of the regulatory analysis, the extent of supplemental analyses should be 3
commensurate with the complexity of the problem and associated uncertainties. At a minimum, 4
the analyst should identify important sources of uncertainty and influential assumptions and 5
evaluate their impacts on analysis outcomes. The results of these investigations should be 6
summarized in the report provided to decision makers, as discussed in Section 7.4, Risk 7
Integration Results and Key Insights.
8 9
H.6.1 Uncertainty Analyses 10 11 Appendix C, Treatment of Uncertainty, to this NUREG contains a general discussion of 12 uncertainties. The discussion below focuses on PRA uncertainties relevant to major-effort 13 analyses.
14 15 H.6.1.1 Uncertainties in PRA Models 16 17 When using PRA results as part of any regulatory decisionmaking process, it is important to 18 understand the types, sources, and potential impact of uncertainties associated with PRA 19 models and how to treat them in the decisionmaking process. Using PRA for regulatory 20 decisionmaking requires that the associated uncertainties and their implications be 21 characterized. For a major-effort analysis, the models and available information for projecting 22 severe accident consequences contain large uncertainties. The explicit identification and 23 quantification of sources of uncertainty of a consequence analysis are necessary to aid the 24 decisionmaker in understanding the results and the potential range of costs and benefits.
25 26 Although PRA models have several different sources of uncertainty, there are two principal 27 categories: aleatory and epistemic. Aleatory uncertainty arises from the random nature of the 28 basic events and phenomena (e.g., weather) modeled in PRAs. Because PRAs use 29 probabilistic distributions to estimate the frequencies or probabilities of these basic events, the 30 PRA model itself is an explicit model of the aleatory uncertainty. Similarly, the explicit modeling 31 of different weather conditions in the Level 3 portion of a PRA is a treatment of aleatory 32 uncertainty.
33 34 Epistemic uncertainties arise from incompleteness in the collective state of knowledge about 35 how to represent plant behavior in PRA models. These uncertainties relate to how well the PRA 36 model reflects the as-designed, as-built, as-operated plant and to how well it predicts the 37 response of the plant to various scenarios. Since these uncertainties can have a significant 38 impact on the interpretation and use of PRA results, it is important that they be appropriately 39 identified and characterized and that the analysis address important uncertainties. The 40 following three types of epistemic uncertainty are associated with PRA models:
41 42 Parameter Uncertainty: Parameter uncertainty relates to the uncertainty of input 43 parameter values. Probability distributions for the input parameters quantify the 44 frequencies or probabilities of basic events in the PRA logic model. Importantly, this 45 assumes that the selection of the probability distribution to model the likelihood of the 46 basic event is agreed upon; if uncertainty exists about this selection, it is more 47 appropriately considered model uncertainty.
48 49
H-37 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Model Uncertainty: Model uncertainty arises from a lack of knowledge of physical 1
phenomena; failure modes related to the behavior of systems, structures, and 2
components under various conditions; or other phenomena modeled in a PRA (e.g., the 3
location and habits of members of the public in different exposure scenarios). This can 4
result in the use of different approaches to modeling certain aspects of the plant and 5
public response that can significantly impact the overall PRA model. Since uncertainty 6
exists about which approach is most appropriate, this leads to uncertainty in the PRA 7
results. Model uncertainty can also arise from uncertainty in the logic structure of the 8
PRA model or in the selection of the probability distribution used to model the likelihood 9
of the basic events in the PRA model. Sensitivity analyses typically address model 10 uncertainties to determine the sensitivity of the PRA results to alternative modeling 11 approaches. The ASME/ANS PRA standards (ASME/ANS, 2009, 2014, 2017) treat 12 Level 2 and Level 3 deterministic analysis uncertainties as model uncertainty, even 13 those that relate to input parameters in the MELCOR and MACCS consequence models.
14 15 Completeness Uncertainty: Completeness uncertainty arises from limitations in the 16 scope and completeness of the PRA model. These uncertainties can be addressed by 17 supplementing the PRA with additional analyses to demonstrate their impact is not 18 significant. The PRA model may have additional uncertainties from unknown risk 19 contributors, and defense-in-depth principles typically address them. See for example, 20 the discussion in NUREG/KM-0009, Historical Review and Observations of 21 Defense-in-Depth (NRC, 2016d). Section 3.1 of NUREG/KM-0009 notes the role of 22 defense-in-depth in a risk-informed regulatory framework to compensate for 23 uncertainties, in particular unquantified and unquantifiable uncertainties. Similar to the 24 framework laid out in Regulatory Guide 1.174 for risk-informed plant-specific changes to 25 licensing bases, consideration of completeness uncertainty means that a regulatory 26 analysis should not be overly reliant on precise risk quantification alone.
27 28 Although PRA cannot account for the unknown and identify all unexpected event scenarios, it 29 can (1) identify some originally unforeseen scenarios, (2) identify where some of the 30 uncertainties exist in plant design and operation, and (3) for some uncertainties, quantify the 31 extent of the uncertainty.
32 33 NUREG-1855, Guidance on the Treatment of Uncertainties Associated with PRAs in 34 Risk-Informed Decision Making, issued March 2017 (NRC, 2017a), contains useful general 35 guidance. NUREG-1855 focuses on sources of uncertainty associated with PRAs used to 36 estimate CDF and LERF, since these are the metrics for current risk-informed regulatory 37 decisions, such as risk-informed changes in the licensing basis. However, the principles and 38 broad guidance are more generally applicable to analyses that encompass additional Level 2 39 (accident progression and source terms) and Level 3 PRA (offsite consequences) information.
40 41 Several reference documents contain useful compendiums of sources of uncertainties in Level 2 42 and Level 3 PRA analyses. An Electrical Power Research Institute (EPRI) companion 43 document to NUREG-1855 lists sources of Level 2 analysis uncertainties identified at a 44 workshop of practitioners (EPRI, 2012). A joint Commission of European Communities expert 45 elicitation conducted in the 1990s identified sources of Level 3 analysis uncertainties (NRC and 46 Commission of European Communities, 1995). The uncertainties for non-site-specific 47 parameters from this expert elicitation were further mapped on to MACCS code input 48 parameters and documented for use in MACCS analyses in NUREG/CR-7161, Synthesis of 49 Distributions Representing Important Non-Site-Specific Parameters in Off-Site Consequence 50 Analyses, issued April 2013 (NRC, 2013c). The NRCs Site Level 3 PRA will have companion 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-38 uncertainty documents for the Level 2 and Level 3 analyses. SOARCA uncertainty analyses are 1
documented for specific SBO scenarios at three NPPs (NRC, 2016b; NRC, 2019a; NRC, 2020).
2 The SOARCA analyses identified and propagated input parameter uncertainties through the 3
MELCOR and MACCS analyses and showed the effects of MELCOR uncertainties on accident 4
progression and radionuclide release metrics, as well as the combined effects of MELCOR and 5
MACCS uncertainties on offsite consequence metrics.
6 7
As noted above, NUREG-1855 and the ASME/ANS PRA standard categorize most uncertainties 8
embodied in the Level 2 and Level 3 portions of the PRA as model uncertainties. For the 9
purposes of consequence analyses supporting regulatory analysis, the outputs from MELCOR 10 and MACCS analyses become inputs to the regulatory and cost-benefit analyses as, for 11 example, individual early and latent cancer fatality risk (for QHO comparisons) and averted 12 population dose and offsite economic cost risks (for quantification of benefits to be compared 13 against implementation costs).
14 15 It is practical to treat the relevant PRA outputs as parameter uncertainties for cost-benefit 16 analysis. The regulatory bases documents for CPRR (NRC, 2018b) and filtered vents 17 (NRC, 2012h) contain examples of how to characterize and propagate uncertainties. Table 12 of 18 to the filtered vents analysis (NRC, 2012h) shows how the uncertainty was 19 described for all relevant inputs to the offsite risk analysis. The point estimates of the base-case 20 inputs such as CDF and MACCS consequences were specified to be the arithmetic means of 21 their respective distributions, and the distribution type and shape factors (such as the and 22 parameters for the beta distribution, or the error factor for the lognormal distribution), were 23 specified as well. The staff used a Monte Carlo process to propagate the uncertainty in each of 24 these inputs, as well as the uncertainty in the onsite cost elements. The results are shown for 25 each proposed modification and are presented as the distributions of averted cost (benefit) 26 elements for (1) public dose risk, (2) offsite economic cost risk, (3) onsite worker dose risk, and 27 (4) onsite cost risk. The CPRR risk analysis similarly assigned uncertainty distributions to the 28 following important inputs: the frequency of extended loss of alternating current power events, 29 the seismic hazard curves, the seismic fragility curves, random equipment failures, operator 30 actions, and consequences. The staff used a Monte Carlo process to propagate these 31 uncertainties and show the resulting distribution of individual latent cancer risk for the different 32 regulatory alternatives under consideration (NRC, 2015a, Figure 4-5), which is reproduced as 33 Figure H-6 as an illustrative example.
34 35
H-39 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-6 Parametric Uncertainty Analysis Results for Individual Latent Cancer Fatality 2
Risk 3
4 H.6.2 Sensitivity Analyses and Plant-to-Plant Variability Analyses 5
6 Sensitivity analysis refers to studying the impact of one uncertain input on the analysis output, 7
without regard to relative probabilities. Uncertainty analysis typically evaluates the integrated 8
impact on the output of a collection of uncertain inputs that are assigned distributions of values, 9
resulting in a distribution of output results. In contrast, sensitivity analysis typically evaluates the 10 impact of one input on the output, and without consideration of the probability of different 11 outcomes. Two-way or joint sensitivity analyses similarly can study the impact of two or more 12 uncertain inputs on the outputs of interest.
13 14 Sensitivity analyses are typically used for particular categories of inputs. It is more appropriate 15 to use sensitivity, rather than uncertainty, analysis for input values subject to the 16 decisionmakers value choices; the dollar per person-rem conversion factor used in cost-benefit 17 analysis is one example. Inputs that depend on variability within the population of affected 18 plants is another example where sensitivity analysis is more appropriate.
19 20
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-40 H.6.2.1 Sensitivity Analyses 1
2 The regulatory analyses discussed in Enclosures H-3 through H-6 of this appendix used 3
sensitivity analyses to address the impact of different values for various inputs. For example, at 4
the time of the filtered vents analysis (Enclosure H-3), CPRR analysis (Enclosure H-4), and 5
expedited spent fuel transfer analysis (Enclosure H-6), the staff was in the process of updating 6
the dollar per person-rem conversion factor. The staff thus performed sensitivity analyses to 7
evaluate the impact on the results of increasing the dollar per person-rem conversion factor 8
from the 1995 value of $2,000 per person-rem to $4,000 per person-rem.
9 10 H.6.2.2 Plant-to-Plant Variability Analyses 11 12 Variability refers to the inherent heterogeneity of data in an assessment because of the diversity 13 of the regulated facilities. When conducting an analysis for a generic requirement that would 14 apply to a number of different plants, the staff usually chooses a representative plant and site 15 for the base-case analysis. To assess the potential difference in analysis outcomes for the 16 affected variable population of sites and facilities, the staff should complete a plant-to-plant 17 variability analysis. For example, the expedited spent fuel transfer regulatory analysis 18 (NRC, 2013g) and technical basis (NRC, 2014d), as well as the CPRR analysis (NRC, 2015a; 19 NRC, 2018b), included sensitivity analyses that showed the effect of the same accident 20 occurring at different sites.
21 22 For the CPRR analysis, the staff performed MACCS sensitivity calculations to analyze the 23 influence of site-to-site variations and protective action variations on the offsite consequences.
24 The staff conducted the following sensitivity calculations:
25 26 population (low, medium, high) 27 evacuation delay (1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />, 3 hour3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br />, 6 hour6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br />, no evacuation) 28 nonevacuating cohort size (5 percent of EPZ population) 29 intermediate phase duration (0, 3 months, and 1 year) 30 long-term habitability criterion (500 millirem per year and 2 rem per year), which can vary 31 among states in the United States 32 33 Table H-5 shows one example of results from this set of sensitivity calculations. This table 34 shows the ratio of results if the intermediate phase duration were 1 year instead of the baseline 35 duration of 3 months. The color coding visually shows the significance to various metrics.
36 Yellow indicates a ratio of near 1, meaning there was no significant difference, while colors 37 closer to red or green indicate a larger influence on results. Results are reported for three sites 38 with representative low, medium, and high populations, coupled with low, medium, and high 39 source terms for Mark I and Mark II containments. Table H-5 shows that the conditional offsite 40 costs for the high source terms at all six sites evaluated are approximately 1.6 times higher 41 when the intermediate phase is assumed to last for 1 year versus 3 months.
42
H-41 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-5 Ratio of Consequences for 1-Year Intermediate Phase Duration Sensitivity 1
Cases to Baseline Cases in the Containment Protection and Release 2
Reduction Analysis 3
4
- An asterisk indicates that the values of both the numerator and denominator in the ratio are zero.
5 (Source: NUREG-2206, Table 4-33) 6 7
Individual Early Fatality Risk 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi Mark I - Low (Bin 3) 0.88 0.89 0.88 0.98 0.99 0.98 0.98 1.00 1.00 0.00 0.00 Mark I - Med (Bin 10) 1.07 0.93 0.91 0.97 0.97 1.38 1.18 0.86 0.92 0.48 0.48 Mark I - High (Bin 17) 1.04 0.98 0.93 0.98 0.96 1.61 1.39 0.80 0.87 0.60 0.53 Mark I - Low (Bin 3) 0.88 0.88 0.88 0.94 0.95 0.96 0.96 1.00 1.00 0.14 0.14 Mark I - Med (Bin 10) 1.06 0.92 0.89 0.93 0.92 1.39 1.04 0.73 0.86 0.57 0.57 Mark I - High (Bin 17) 1.02 0.97 0.91 0.97 0.92 1.58 1.33 0.71 0.82 0.59 0.46 Mark I - Low (Bin 3) 0.88 0.89 0.88 0.95 0.95 0.97 0.97 1.00 1.00 0.16 0.16 Mark I - Med (Bin 10) 1.07 0.92 0.90 0.93 0.92 1.31 1.16 0.91 0.94 0.39 0.39 Mark I - High (Bin 17) 1.04 0.97 0.93 0.97 0.94 1.60 1.46 0.86 0.89 0.55 0.51 Mark II - Low (Bin 2) 0.90 0.93 0.93 0.99 0.99 1.00 1.00 1.00 1.00 Mark II - Med (Bin 5) 0.96 0.92 0.92 0.98 0.98 1.00 1.00 0.99 1.00 0.29 0.29 Mark II - High (Bin 8) 1.18 0.98 0.98 0.98 0.98 1.50 1.49 0.86 0.90 0.20 0.19 Mark II - Low (Bin 2) 0.90 0.93 0.93 0.96 0.96 1.00 1.00 1.00 1.00 Mark II - Med (Bin 5) 0.98 0.93 0.90 0.95 0.93 1.18 1.11 0.94 0.97 0.44 0.44 Mark II - High (Bin 8) 1.18 0.98 0.98 0.97 0.97 1.63 1.49 0.62 0.81 0.26 0.21 Mark II - Low (Bin 2) 0.90 0.93 0.93 0.93 0.94 1.00 1.00 1.00 1.00 Mark II - Med (Bin 5) 1.00 0.92 0.91 0.94 0.93 1.08 1.06 0.96 0.97 0.45 0.45 Mark II - High (Bin 8) 1.17 0.97 0.98 0.95 0.96 1.57 1.48 0.68 0.81 0.21 0.20 Individual early fatality risk is zero for all baseline and sensitivity cases.
Land (sq mi)
Exceeding Long-Term Habitability Criterion Mark II - Limerick Low -
Columbia Medium -
Susquehanna High -
Limerick High - Peach Bottom Offsite Cost
($ 2013)
Population Subject to Long-Term Protective Actions Mark I - Peach Bottom Low - Hatch Medium -
Vermont Yankee Individual Latent Cancer Fatality Risk Population Dose (person-rem)
Base Model Site Source Term
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-42 H.7 PRESENTATION OF RESULTSINPUTS TO REGULATORY 1
ANALYSIS 2
3 H.7.1 Aggregating Probabilistic Risk Assessment Results from Different Hazards 4
5 For many regulatory applications, it is necessary to consider the contributions from several 6
hazards to a specific risk metric. When considering multiple hazards, a PRA model can be a 7
fully integrated model in which all hazards are combined into a single logic structure, a set of 8
individual PRA models for each hazard, or a mixture of the two. When combining the results of 9
PRA models for several hazards, the levels of detail and approximation included in the PRA 10 model may differ from one hazard to the next. Because of the methods and data used, a high 11 level of uncertainty can exist in PRAs for internal fires, external events (seismic, high wind, and 12 others), and low-power/shutdown conditions. In principle, this uncertainty could be reduced by 13 developing models to the same level of detail and rigor associated with internal events, at-power 14 PRAs. A larger uncertainty in a subset of the total PRA analyses can result in greater 15 uncertainty. The analyst needs to understand the main sources of conservatism in the PRA 16 associated with any of the hazards that can potentially impact the regulatory application. When 17 interpreting the results of the comparison of risk metrics to acceptance criteria or guidelines, it is 18 important to focus not only on the aggregated numerical result but also on the relative 19 importance and uncertainty of the main contributors to the risk metric.
20 21 H.7.2 Offsite Consequence Measures 22 23 An analyst uses several offsite consequence measures to characterize the impacts resulting 24 from a severe accident. For the purposes of a regulatory analysis, the individual early fatality 25 risk, latent cancer fatality risk, population dose, and offsite economic costs should all be 26 presented. The first two enable comparisons with the NRCs QHOs, and the latter two are 27 needed to quantify the affected parameters (accident offsite consequences) in the cost-benefit 28 equation.
29 30 H.7.2.1 Conditional Consequence Measures 31 32 Conditional offsite consequence results should be presented, first, for each source term bin. In 33 other words, given that an accident occurs and results in a particular source term bin, the offsite 34 consequences should be presented. The next step is to map the source term bins onto the 35 release categories developed in the accident sequence analysis, for the purposes of risk 36 integration.
37 38 Early Fatality Risk 39 40 Individual early fatality risk for the area within approximately 1 mile of the site boundary is 41 provided as an input for the evaluation of the NRCs early fatality QHO (NRC, 2015a).22 42 43 Latent Cancer Fatality Risk 44 45 The individual latent cancer fatality risk is the risk of an average individual within the specified 46 spatial element contracting a fatal cancer caused by early, intermediate, and long-term radiation 47 22 If no one resides within 1 mile of the site boundary an individual should be assumed to reside within 1 mile for evaluation purposes.
H-43 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 exposures. The analyst calculates this population-weighted metric by dividing the expected 1
number of fatal cancers in a spatial element by the population residing in that element. The 2
analysis should show the individual latent cancer fatality risk for the areas within 10- and 3
50-miles from the reactor site. The 10-mile area corresponds to the QHO for cancer fatality risk 4
(NRC, 2015a) and to the plume exposure EPZ. The analysis also should display the results for 5
the 50-mile area, as the NRCs regulatory analyses use this distance (other distances may be 6
appropriate, depending on facility type, as discussed in Section H.3.3.3).
7 8
Population Dose Risk 9
10 The offsite population dose, measured in person-rem, represents the sum of the doses from all 11 exposure pathways multiplied by the size of the population within a specified area. This metric 12 quantifies the public health (accident) attribute, as discussed in Sections 5.2.1 and 5.3.2.1 of 13 this NUREG. The dose to the population within a 50-mile radius (or other appropriate distance, 14 as discussed in Section H.3.3.3) from the reactor facility is reported for each source term bin.
15 MACCS reports the population dose per event (i.e., the conditional dose, given a particular 16 accident), and this value needs to be converted to the population dose per reactor-year by 17 multiplying by the event frequency.
18 19 Offsite Economic Cost Risk 20 21 The offsite economic costs resulting from an accident scenario correspond to the economic 22 consequences (offsite property) attribute described in Sections 5.2.5 and 5.3.2.5 of this 23 NUREG. This metric sums the costs of the protective actions taken to reduce offsite exposure 24 and restore land to usability and habitability. The offsite economic costs are computed directly 25 by MACCS and should be reported for the area within a 50-mile radius (or other appropriate 26 distance, as discussed in Section H.3.3.3) of the reactor facility for each source term bin.
27 28 Other Results 29 30 In addition to risk estimates, other consequence results provide risk insights about the various 31 alternatives. Some examples include the number of displaced individuals, land contamination, 32 and the extent over which protective actions may be needed. Discussion of these other results 33 may provide a better understanding of the extent and severity of the accident scenarios.
34 35 Table H-6 gives one example of how this information might be tabulated. This table is taken 36 from the CPRR analysis (NRC, 2015a; NRC, 2018b) and shows each of these consequence 37 results and their corresponding source term bins. This CPRR analysis (similar to the SFP study 38
[NRC, 2014d]) reported other results, such as land contamination and size of the population 39 affected by long-term protective actions, at radii of 50 miles and 100 miles from the reactor site.
40 41
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-44 Table H-6 Severe Accident Consequence Analysis ResultsExample 1
2 (Source: SECY-15-0085, Enclosure, Table 4-22) 3 4
The consequence results presented in Table H-6 do not account for the event frequency, 5
(e.g., they are conditional on the occurrence of the postulated accident). Also, it is important to 6
note that these results are strongly dependent on the assumed (modeled) protective actions.
7 8
H.7.3 Evaluation of Regulatory Alternatives 9
10 H.7.3.1 Results from the Core Damage Event Tree Quantification 11 12 The analysis should tabulate the point estimates for relevant initiating event frequency, CDF, 13 and conditional core damage probability by site for each regulatory alternative. These tables 14 provide insight into the efficacy of the different strategies and present fleet averages for CDF 15 and conditional core damage probability for comparison.
16 17 Basic events, such as equipment and human failure events, should be tabulated with 18 importance measures (Risk Achievement Worth and Fussel-Vesely) with respect to CDF. A 19 table should show plant damage state frequencies for each regulatory alternative.
20 21 H.7.3.2 Results from the Accident Progression Event Tree Quantification 22 23 The analysis should tabulate the conditional containment failure probability for each APET to 24 demonstrate the efficacy of different mitigation alternatives. It should also tabulate the 25 frequencies of significant release categories for each APET.
26 27 The accident sequence analysis results show the CDF frequency from the initiating event and 28 provide insights into the relative contributions of various factors (e.g., external hazards, 29 equipment failures, human errors) to overall CDF. Figure H-7 shows an example of accident 30 sequence analysis and radioactive release summary results from the SFP study (NRC, 2014d).
31 32
H-45 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-7 Likelihood of a Leak and Magnitude of Releases from Beyond-Design-Basis 2
(Source: NUREG-2161, Figure ES-1) 4 5
H.7.3.3 Results from MELCOR Analysis 6
7 The MELCOR results are classified into two broad categories: (1) thermal-hydraulic output and 8
(2) source term output. The timing of key events for the accident progression should be 9
presented and discussed for select MELCOR cases. In addition, time plots should be provided 10 for some important thermal-hydraulic outputs. Some examples include the following:
11 12 Reactor pressure vessel pressure, temperature, and water level 13 14 Containment pressure and temperature, to determine the likelihood of failure of 15 containment and various components by overpressure, overtemperature, or both 16 17 Hydrogen and other noncondensable gas generation and migration, to contribute to 18 containment overpressurization; also, to determine the potential for combustion in, for 19 example, the reactor building or the vent line 20 21
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-46 These discussions assist the analyst in assessing how each regulatory alternative would impact 1
the accident progression and the state of containment vulnerability under severe accident 2
conditions. They also provide the decisionmaker with qualitative information and a technical 3
basis for developing potential staff guidance for implementing a regulatory alternative.
4 5
H.7.4 Risk Integration Results and Key Insights 6
7 The final step is to present the results as integrated risk measures, which multiplies the 8
frequencies of different accident sequences with their conditional consequences. For example, 9
for each regulatory alternative (or subalternative), the population dose risk and offsite economic 10 cost risks should be presented on a per-reactor-year basis. Table H-7 and Figure H-8 show 11 example presentations of results, taken from the CPRR analysis (NRC, 2015a; NRC, 2018b).
12 The affected parameters that are quantified in the cost-benefit equation, population dose risk, 13 and economic cost risk, associated with each regulatory analysis subalternative are presented 14 for 50-mile and 100-mile radial distances. Additional measures are also presented, such as 15 land exceeding habitability criterion. Figures H-9 and H-10 show another example, taken from 16 the filtered vents analysis (NRC, 2012h), which presents the change (compared to the status 17 quo) in offsite economic cost risk per year for each regulatory alternative, called a Mod 18 (Figure H-9). Furthermore, the results of the uncertainty quantification are shown for those 19 alternatives (Figure H-10) with a positive change.
20 21 In addition to quantitative risk results, important qualitative insights and assumptions should also 22 be presented, on the most important contributors to risk and uncertainty. The supplementary 23 analyses discussed in Section H.6 make an essential contribution to this summary discussion 24 for decision makers, since those investigations help identify the impact of uncertainties and the 25 sensitivity of results to different assumptions. For example, the Technical Evaluation Summary 26 of the CPRR analysis (NRC, 2015a, Section 4.6 of Enclosure) presented the key insights from 27 the risk evaluation, MELCOR analysis, and MACCS analysis. These insights included the 28 following:
29 30 A discussion of the most important contributors to accident frequency (e.g., the major 31 contribution to seismically induced ELAP is from earthquakes that cause site peak 32 ground accelerations in the range of 0.3 to 0.75g) 33 34 A discussion of important assumptions (e.g., the evaluation assumed that 60 percent of 35 the time, the pre-core-damage water addition [FLEX] will be successful in preventing 36 core damage) 37 38 A discussion of accident progression and source term insights (e.g., the highest 39 calculated release to the environment results from a main steam line creep rupture 40 scenario, which is one of the least likely scenarios) 41 42 A discussion of offsite consequence insights (e.g., that, for all Mark I and Mark II source 43 terms, there is zero early fatality risk because the source terms are not large enough to 44 exceed the threshold for the acute dose to the red bone marrow, which is typically the 45 most sensitive tissue for early fatalities) 46 47 A discussion of important uncertainties and their key drivers (e.g., that the 48 5 percent/95 percent parametric uncertainty interval of the estimated risks is more than 49 1 order of magnitude and is largely driven by uncertainty in the seismic hazard curves) 50
H-47 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-7 Risk Estimates by Regulatory Analysis Subalternative 1
2 (Source: NUREG-2206, Table 5-1) 3 Index Regulatory Analysis Sub-Alternative Fraction of Core-Damage Frequency Individual Early Fatality Risk (/y)
Individual Latent Cancer Fatality Risk (/y)
Population Dose (person-rem/y)
Offsite Cost
($ 2013/y)
Land Exceeding Long-Term Habitability Criterion (square miles/y)
Population Subject to Long-Term Protective Actions (persons/y)
Vented Uncontrolled Release 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
1 0%
100%
0.0E+00 3.0E-09 8.6E-10 4.2E-10 1.3E+01 2.3E+01 9.9E+04 1.3E+05 4.4E-03 7.6E-03 5.1E-01 5.8E-01 2
2A 0%
100%
0.0E+00 3.0E-09 8.6E-10 4.2E-10 1.3E+01 2.3E+01 9.9E+04 1.3E+05 4.4E-03 7.6E-03 5.1E-01 5.8E-01 3
3A 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 4
3B 42%
58%
0.0E+00 2.1E-09 6.7E-10 3.4E-10 1.1E+01 1.9E+01 7.4E+04 1.0E+05 3.4E-03 6.4E-03 4.1E-01 4.9E-01 5
4Ai(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 6
4Ai(2) 42%
58%
0.0E+00 2.1E-09 6.1E-10 3.1E-10 9.5E+00 1.7E+01 6.8E+04 9.0E+04 3.2E-03 5.8E-03 3.6E-01 4.1E-01 7
4Aii(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 8
4Aii(2) 42%
58%
0.0E+00 2.4E-09 7.7E-10 3.9E-10 1.2E+01 2.2E+01 8.9E+04 1.2E+05 3.9E-03 7.3E-03 4.8E-01 5.8E-01 9
4Aiii(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 10 4Aiii(2) 42%
58%
0.0E+00 2.0E-09 5.6E-10 2.7E-10 8.7E+00 1.5E+01 6.2E+04 7.9E+04 3.0E-03 5.1E-03 3.1E-01 3.4E-01 11 4Bi(1) 58%
42%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.5E+00 7.8E+00 2.9E+04 3.7E+04 1.6E-03 2.5E-03 1.5E-01 1.6E-01 12 4Bi(2) 42%
58%
0.0E+00 1.4E-09 3.3E-10 1.5E-10 4.8E+00 8.2E+00 3.1E+04 3.8E+04 1.8E-03 2.7E-03 1.6E-01 1.6E-01 13 4Bii 42%
58%
0.0E+00 1.4E-09 3.2E-10 1.5E-10 4.6E+00 7.9E+00 3.0E+04 3.7E+04 1.7E-03 2.6E-03 1.5E-01 1.5E-01 14 4Biii 42%
58%
0.0E+00 1.4E-09 3.2E-10 1.5E-10 4.7E+00 8.1E+00 3.1E+04 3.7E+04 1.7E-03 2.6E-03 1.5E-01 1.6E-01 15 4Biv 40%
60%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.6E+00 7.8E+00 3.0E+04 3.6E+04 1.7E-03 2.6E-03 1.5E-01 1.5E-01 16 4Ci(1) 58%
42%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.5E+00 7.8E+00 2.9E+04 3.7E+04 1.6E-03 2.5E-03 1.5E-01 1.6E-01 17 4Ci(2) 42%
58%
0.0E+00 1.3E-09 3.1E-10 1.4E-10 4.5E+00 7.6E+00 3.0E+04 3.7E+04 1.6E-03 2.4E-03 1.5E-01 1.6E-01 18 4Cii 42%
58%
0.0E+00 1.3E-09 3.0E-10 1.4E-10 4.4E+00 7.4E+00 2.9E+04 3.6E+04 1.5E-03 2.3E-03 1.5E-01 1.5E-01 19 4Ciii 42%
58%
0.0E+00 1.3E-09 3.1E-10 1.4E-10 4.4E+00 7.6E+00 3.0E+04 3.7E+04 1.6E-03 2.4E-03 1.5E-01 1.6E-01 20 4Civ 40%
60%
0.0E+00 1.3E-09 3.0E-10 1.4E-10 4.3E+00 7.4E+00 2.9E+04 3.6E+04 1.5E-03 2.3E-03 1.5E-01 1.5E-01
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-48 1
Figure H-8 Comparison of Regulatory Analysis Alternatives Using Population Dose Risk 2
(0-50 miles) 3 (Source: NUREG-2206, Figure 5-2) 4 5
6 Figure H-9 Reduction in 50-mile Offsite Cost Risk ($/reactor-year) 7 (Source: SECY-12-0157, Enclosure 5c, Figure 5) 8
H-49 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
2 Figure H-10 Uncertainty in Reduction in 50-mile Offsite Cost Risk 3
(Source: SECY-12-0157, Enclosure 5c, Figure 10) 4 5
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2015d. ADAMS Accession No. ML15049A213.
8 NRC, Seventh 6-Month Status Update on Response to Lessons Learned from Japan's March 9
11, 2011, Great Tohoku Earthquake and Subsequent Tsunami, SECY-15-0059, 2015e.
10 ADAMS Accession No. ML15069A444.
11 NRC, Staff RequirementsProposed Rulemaking: Mitigation of Beyond-Design-Basis Events, 12 SECY-15-0065, 2015f. ADAMS Accession No. ML15231A471.
13 NRC, Generic Issues Program, Management Directive 6.4, 2015g. ADAMS Accession No.
14 ML18073A162.
15 NRC, Closure of Fukushima Tier 3 Recommendations Related to Containment Vents, 16 Hydrogen Control, and Enhanced Instrumentation, SECY-16-0041, 2016a. ADAMS Accession 17 No. ML16049A079 (package).
18 NRC, State-of-the-Art Reactor Consequence Analyses Project: Uncertainty Analysis of the 19 Unmitigated Long-Term Station Blackout of the Peach Bottom Atomic Power Station, 20 NUREG/CR-7155, SAND2012-10702P, 2016b. ADAMS Accession No. ML16133A461.
21 NRC, Probabilistic Risk Assessment and Regulatory Decisionmaking: Some Frequently Asked 22 Questions, NUREG-2201, 2016c. ADAMS Accession No. ML16245A032.
23 NRC, Historical Review and Observations of Defense-in-Depth, NUREG/KM-0009, 2016d.
24 ADAMS Accession No. ML16104A071.
25 NRC, Guidance on the Treatment of Uncertainties Associated with PRAs in Risk-Informed 26 Decisionmaking, Final Report, NUREG-1855, Revision 1, 2017a. ADAMS Accession 27 No. ML17062A466.
28 NRC, Proposed Revision to NUREG-1530 Reassessment of NRCs Dollar Per Person-Rem 29 Conversion Factor Policy, SECY-17-0017, 2017b. ADAMS Accession No. ML16147A293 30 (package).
31 NRC, An Approach for Using Probabilistic Risk Assessment in Risk-Informed Decisions on 32 Plant-Specific Changes to the Licensing Basis, Regulatory Guide 1.174, current version.
33 NRC, Strategic Plan: Fiscal Years 2018-2022, NUREG-1614, Volume 7, 2018a. ADAMS 34 Accession No. ML18032A561.
35
H-57 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 NRC, Technical Basis for the Containment Protection and Release Reduction Rulemaking for 1
Boiling-Water Reactors with Mark I and Mark II Containments, NUREG-2206, 2018b. ADAMS 2
Accession No. ML18065A048.
3 NRC, State-of-the-Art Reactor Consequence Analyses (SOARCA) Project: Sequoyah 4
Integrated Deterministic and Uncertainty Analyses, NUREG/CR-7245, Sandia National 5
Laboratories, 2019a.
6 NRC, 2019-2020 Information Digest, NUREG-1350, Volume 31, 2019b. ADAMS Accession 7
No. ML19242D326.
8 NRC, Benefits and Uses of the State-of-the-Art Reactor Consequence Analyses (SOARCA) 9 Project, Research Information Letter 19-01, 2019c.
10 NRC, SecPop Version 4: Sector Population, Land Fraction, and Economic Estimation 11 Program, NUREG/CR-6525, Revision 2, Sandia National Laboratories, 2019d. ADAMS 12 Accession No. ML19182A284.
13 NRC, State-of-the-Art Reactor Consequence Analyses (SOARCA) Project: Uncertainty 14 Analysis of the Unmitigated Short-Term Station Blackout of Surry Power Station, 15 NUREG/CR-7262, Sandia National Laboratories, 2020.
16 NRC and Commission of European Communities, Probabilistic Accident Consequence 17 Uncertainty Analysis, NUREG/CR-6244 Report Series, 1995.
18 NRC and FEMA, Criteria for Preparation and Evaluation of Radiological Emergency Response 19 Plans and Preparedness in Support of Nuclear Power Plants, NUREG-0654 and FEMA-REP-1, 20 Revision 1, 1980. ADAMS Accession No. ML040420012.
21 22
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-58 ENCLOSURE H-1: DESCRIPTION OF ANALYTICAL TOOLS AND 1
CAPABILITIES 2
3 Risk can be characterized in many ways, depending on the end states of interest for a decision 4
or application. To provide some overall logic and structure and to facilitate evaluation of 5
intermediate results, probabilistic risk assessments (PRAs) for nuclear power plants (NPPs) 6 have traditionally been organized into three analysis levels, with the scope and level of 7
complexity of the PRA model increasing with each level. These levels are defined by three 8
sequential adverse end states that can occur in the progression of postulated NPP accident 9
scenarios: (1) core damage, (2) radiological release, and (3) offsite radiological consequences.
10 11 Several computer codes exist for performing PRA and severe accident consequence analysis.
12 For regulatory analyses that require detailed analyses of offsite consequences, most recent 13 light-water reactor applications have used the U.S. Nuclear Regulatory Commission 14 (NRC)-sponsored MELCOR and MELCOR Accident Consequence Code System (MACCS) 15 code suites. These codes include state-of-the-art integrated modeling of severe accident 16 behavior that incorporates insights from decades of research into severe accident 17 phenomenology and radiation health effects. The NRC-sponsored Systems Analysis Programs 18 for Hands-on Integrated Reliability Evaluations (SAPHIRE) code is also available for performing 19 PRAs using event trees and fault trees. Figure H-11 notes the role of these three code suites in 20 NPP PRAs. The sections below describe these code suites, their capabilities, and their typical 21 uses.
22 23
H-59 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
2 3
Figure H-11 Overall Logic and Structure of Traditional NPP PRA Models and Role of 4
SAPHIRE, MELCOR, and MACCS Code Suites 5
6 Severe Accident Scenario Modeling and Frequency Analysis 7
8 Systems Analysis Programs for Hands-on Integrated Reliability Evaluations 9
(SAPHIRE) 10 11 SAPHIRE is an NRC-sponsored software application that the Idaho National Laboratory 12 developed and maintains for performing PRAs of complex engineered facilities, systems, or 13 processes.
14 15 The NRC uses SAPHIRE to develop Level 1 and Level 2 PRA logic models for NPPs. The end 16 state of interest for a Level 1 PRA is core damage. SAPHIRE can (1) model plant and operator 17 responses to initiating events to identify sequences (combinations of system and operator action 18 successes and failures) that result in either the achievement of a safe state or the onset of core 19 damage, (2) quantify the frequencies of sequences that result in core damage and total core 20 damage frequency (CDF) for the NPP, and (3) identify important contributors to CDF. The end 21 state of interest for a Level 2 PRA is radiological release. SAPHIRE can also be used to 22 expand upon a Level 1 PRA model to (1) model containment systems and operator responses 23 to severe accident conditions, (2) quantify radiological release category frequenciesincluding 24 a large early release frequency (LERF), and (3) identify important contributors to radiological 25 release category frequencies. A Level 3 PRA combines the results of the SAPHIRE radiological 26 release category frequencies (from the Level 2 PRA) with the results from the corresponding 27 MACCS offsite radiological consequence model to provide an overall characterization of the risk 28 to the offsite public from a broad spectrum of postulated accidents involving a modeled NPP 29 site.
30 31 SAPHIRE MELCOR MACCS
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-60 SAPHIRE contains graphical editors for creating, viewing, and modifying fault tree and event 1
tree models that serve as logical representations of accident sequences that can occur at an 2
NPP. SAPHIRE uses event tree and fault tree models, coupled with accident sequence linkage 3
rules and postprocessing rules, to generate unique combinations of individual failures 4
(i.e., minimal cut sets) that can result in an undesired end state. SAPHIRE quantifies the 5
frequencies and probabilities associated with the minimal cut sets to estimate the frequencies of 6
selected undesired end states. In addition, SAPHIRE includes many useful features to support 7
the frequency quantification of PRA models and identification of significant contributors to risk 8
(e.g., calculation of traditional PRA importance measures described below). Finally, SAPHIRE 9
can perform an uncertainty analysis using either Monte Carlo or Latin Hypercube sampling 10 methods to estimate the uncertainty in calculated results (e.g., CDF, LERF, or importance 11 measures) caused by epistemic23 uncertainties in input parameters for basic events in the 12 Level 1 and Level 2 PRA logic models.
13 14 NUREG/CR-7039, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations 15 Version 8, issued June 2011, contains detailed information about the features and capabilities 16 of SAPHIRE Version 8. Some basic features and capabilities in SAPHIRE include the following:
17 18 Basic events: Basic events typically represent events involving failures of structures, 19 systems, or components; adverse environmental or phenomenological conditions that 20 could lead to failures; or human failure events for operator actions. Basic events are 21 logically linked together in fault trees and provide SAPHIRE with the probabilistic 22 information (e.g., failure data input and type of probability calculation) needed to quantify 23 the PRA model. Basic events appear as circles at the bottom of the example in 24 Figure H-12 (feeding System A and System B fault trees).
25 26 Fault trees: A fault tree generally represents a failure model. A fault tree model consists 27 of a top event (e.g., failure of System A in the example in Figure H-12), usually defined 28 by a heading in an event tree (e.g., System A appears as a heading in the example 29 event tree in Figure H-12, for the initiating event IE). A combination of basic events 30 must occur to result in the undesired top event, using a logic structure as a model for the 31 basic events.
32 33 Event trees: An event tree is a logic structure that chains sequential events together to 34 model the likelihood of the potential outcome(s) of those events. The simple example in 35 Figure H-12 contains a chain of three events: initiating event IE, System A (success or 36 failure), and System B (success or failure). The analyst defines accident sequences 37 using an event tree to indicate the failure or success of top events. Each heading in the 38 event tree is associated with a system fault tree. Event trees are constructed and 39 modified using a graphical editor that allows the linkage of multiple event trees and the 40 creation of very large event trees.
41 42 Rule-based fault tree linking: In generating accident sequences, the analyst uses a set 43 of defined rules to reduce the complexity of the overall logic structure.
44 45 Cut sets: A cut set is a combination of faults that must occur together to result in the 46 failure of a top event. To solve an accident sequence, SAPHIRE constructs a fault tree 47 23 Epistemic uncertainty is the uncertainty related to the lack of knowledge or confidence about the system or model and is also known as state-of-knowledge uncertainty (NUREG-2122, Glossary of Risk-Related Terms in Support of Risk-Informed Decision Making, issued November 2013).
H-61 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 for those systems that are defined to be failed in the sequence logic by creating a 1
temporary AND gate with these systems as inputs. SAPHIRE then solves this fault 2
tree using specified cut set probability truncation values. This process results in a list of 3
cut sets for the failed systems in the accident sequence. SAPHIRE then uses Boolean 4
reduction techniques to further reduce this list of cut sets to the set of minimal cut sets 5
for the accident sequence. The analyst can specify one of three main cut set 6
quantification techniques, depending on the desired tradeoff between accuracy and 7
computation time.
8 9
Uncertainty analysis: Both Monte Carlo and Latin Hypercube sampling methods are 10 available for performing an uncertainty analysis. The uncertainty analysis functions in 11 SAPHIRE estimate the uncertainty in calculated output quantities caused by epistemic 12 uncertainties in the basic event frequencies or probabilities. These output quantities 13 include (1) fault tree top event probabilities, (2) event tree sequence frequencies, (3) end 14 state frequencies, or (4) importance measures. In an uncertainty analysis, SAPHIRE 15 samples analyst-specified distributions for each basic event in a group of cut sets and 16 then quantifies these cut sets using the sampled values.
17 18 Importance measures: SAPHIRE can quantify a range of traditional importance 19 measures that are used to measure the absolute or relative importance of basic events 20 in the PRA model to specified end-state frequencies. As previously stated, uncertainty 21 analyses on these measures can use Monte Carlo or Latin Hypercube sampling 22 techniques.
23 24 The NRC designed its SAPHIRE software development and maintenance program to provide an 25 analytical tool that performs risk calculations accurately and efficiently and reports the results in 26 a clear and concise manner to support risk-informed decisionmaking. Idaho National 27 Laboratory has created a software quality assurance program to ensure SAPHIRE continues to 28 meet its requirements as new features and changes are implemented.
29 30
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-62 1
Figure H-12 Simplified Diagram of Event Tree with Initiating Event (IE) and Two 2
Supporting Fault Trees 3
4 Standardized Plant Analysis Risk Models 5
6 The NRC established the Standardized Plant Analysis Risk (SPAR) model program to support 7
regulatory reviews and independent evaluations of risk-related issues. The SPAR models are 8
plant-specific NRC-developed PRA models using standardized modeling conventions and data.
9 This standardization allows agency risk analysts to efficiently use SPAR models for diverse 10 plant designs in support of various regulatory activities. The regulatory uses of SPAR models 11 include the following:
12 13 Inspection Program (e.g., Significance Determination Process Phase 3): Determine the 14 risk significance (with respect to CDF and LERF) of inspection findings or of events to 15 decide (1) the allocation and characterization of inspection resources, (2) the initiation of 16 an inspection team, or (3) the need for further analysis or action by other agency 17 organizations.
18 19
H-63 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Management Directive 8.3, NRC Incident Investigation Program: Estimate the risk 1
significance of events or conditions at operating NPPs so the agency can analyze and 2
evaluate the implications of plant operating experience to (1) compare the operating 3
experience with the results of licensee PRAs, (2) identify risk-significant conditions that 4
need additional regulatory attention, (3) identify conditions that need less regulatory 5
attention, and (4) evaluate the risk impact of regulatory or licensee programs.
6 7
Accident Sequence Precursor Program: Screen and analyze operating experience data 8
using a systematic approach to identify those events or conditions that are precursors to 9
severe accident sequences (core damage events).
10 11 Generic Issues Program: Provide the capability to resolve generic safety issues, both 12 for screening (or prioritization) and conducting a more rigorous analysis to (1) determine 13 if licensees should be required to make a change to their plants or (2) assess if the 14 agency should modify or eliminate one or more existing regulatory requirements.
15 16 License Amendment Reviews: Enable the NRC staff to make risk-informed decisions on 17 plant-specific changes to the licensing basis as proposed by licensees and provide risk 18 perspectives in support of agency reviews of licensee submittals.
19 20 Verification of Performance Indicators: Assist in (1) identifying threshold values for 21 risk-based performance indicators and (2) developing integrated or aggregate 22 performance indicators.
23 24 Special Studies: Undertake various studies in support of risk-informed regulatory 25 decisions (e.g., regulatory analysis and backfit analysis).
26 27 Operating Experience: Support and provide rigorous and peer reviewed evaluations of 28 operating experience, thereby demonstrating the agencys ability to analyze operating 29 experience independently of licensee PRAs and thus enhancing the technical credibility 30 of the agency.
31 32 The SPAR models allow agency risk analysts to perform independent evaluations of regulatory 33 issues without reliance on licensee-developed PRA models and analyses. The SPAR models 34 integrate systems analysis, accident scenarios, component failure likelihoods, and human 35 reliability analysis into a coherent model that reflects the design and operation of a specific 36 plant. These models give agency risk analysts the capability to (1) quantify the expected risk of 37 an NPP in terms of CDF or LERF, (2) identify and understand the attributes that significantly 38 contribute to risk, and (3) develop insights on how to manage that risk.
39 40 The SPAR models use an NRC-developed standard set of event trees and standardized input 41 data for initiating event frequencies, equipment performance, and human performance.
42 However, these input data may be modified to be more plant-or event-specific, when needed.
43 The system fault trees contained in the SPAR models are generally not as detailed as those 44 contained in licensee PRA models. However, SPAR models may need to be more advanced in 45 some areas than licensee PRA models (e.g., modeling of support system initiating events and 46 electrical power recovery). The staff has performed detailed cut set reviews for all SPAR 47 models to (1) more accurately model plant operation and configuration and (2) identify 48 significant differences between licensee PRAs and the corresponding SPAR models.
49 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-64 In addition to internal events, at-power models, the staff has developed the following models for 1
a subset of units: (1) external event models based on the licensee responses to Generic 2
Letter 88-20, Supplement 4, Individual Plant Examination of External Events for Severe 3
Accident Vulnerabilities, dated June 28, 1991, (2) low-power/shutdown models, and 4
(3) extended Level 1 PRA models supporting limited Level 2 PRA modeling and quantification of 5
LERF. SPAR model development work in these areas is ongoing. The staff has updated all 6
internal events models to include FLEX modeling. Additionally, the staff has developed 7
design-specific internal events SPAR models for new reactor designs and is developing a plant 8
specific new reactor SPAR model.
9 10 The staff has developed a formal SPAR model quality assurance plan and the Risk Assessment 11 Standardization Project Handbook. The SPAR model quality assurance plan provides 12 reasonable assurance that the SPAR models used by agency risk analysts represent the 13 as-built, as-operated plants to the extent intended within the scope of the SPAR models. As 14 part of this plan, the staff periodically updates the SPAR models for operating NPPs to reflect 15 the most recent operating experience and reliability data, performing routine updates to 16 approximately 6 SPAR models per year. The Risk Assessment Standardization Project 17 Handbook implements a formal, written process for maintaining SPAR models that are 18 sufficiently representative of the as-built, as-operated plants to support model uses. The staff 19 and Idaho National Laboratory also developed a SAPHIRE quality assurance program that is 20 compliant with NUREG/BR-0167, Software Quality Assurance Program and Guidelines, and 21 developed and released SAPHIRE Version 8, issued February 1993, which was independently 22 verified and validated.
23 24 American Society of Mechanical Engineers and American Nuclear Society PRA 25 Standard 26 27 In 2009, the staff, along with peer review teams comprised of industry experts, performed a peer 28 review of a representative boiling-water reactor SPAR model and a representative 29 pressurized-water reactor SPAR model in accordance with the American Society of Mechanical 30 Engineers (ASME) and American Nuclear Society (ANS) PRA Standard, ASME RA-S-2002, 31 Standard for Probabilistic Risk Assessment for Nuclear Power Plant Applications, and 32 Regulatory Guide 1.200, An Approach for Determining the Technical Adequacy of Probabilistic 33 Risk Assessment Results for Risk-Informed Activities. The peer review teams concluded 34 thatwithin constraints on access to licensee data and resourcesthe SPAR models are an 35 appropriate tool to provide a check and to prompt questions on the licensee-maintained and 36 peer reviewed PRA. The staff therefore concluded that SPAR models are an efficient tool for 37 obtaining qualitative and quantitative insights for agency risk-informed applications.
38 39 Severe Accident Progression and Source Term Analysis 40 41 The MELCOR Code 42 43 The MELCOR code is a fully integrated, engineering-level computer code designed to model the 44 progression of a broad spectrum of postulated severe accidents in light-water reactors and in 45 nonreactor systems (e.g., spent fuel pool and dry cask). MELCOR has been under continuous 46 development by the NRC and Sandia National Laboratories. Current activities involve the 47 development and implementation of new and improved models to predict the severe accident 48 behavior of various reactor (both light water and nonlight water) and spent fuel pool designs and 49 to reduce modeling uncertainties. In addition, enhancements and more flexibility are being 50
H-65 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 added to the code to evaluate the safety of accident-tolerant fuel designs. MELCOR represents 1
the current state-of-the-art in accident progression analysis, which has developed from domestic 2
and international research. The MELCOR code development meets the following criteria:
3 4
The prediction of phenomena is in qualitative agreement with the current 5
understanding of physics, and uncertainties are in quantitative agreement with 6
experiments.
7 8
The focus is on mechanistic models, where feasible, with adequate flexibility for 9
parametric models.
10 11 The code is portable, robust, and relatively fast running, and its maintenance 12 follows established Software Quality Assurance standards.
13 14 Detailed code documentation (including user guide, model reference, and 15 assessment) is available.
16 17 The NRC uses MELCOR to model severe accident progression and to compute the resulting 18 source terms for use in plant-specific PRAs and regulatory and backfit analyses. Recent 19 examples include the technical bases for the following NRC studies:
20 21 Enclosure H-3, Summary of Detailed Analyses for SECY-12-0157, of this appendix 22 summarizes the detailed analyses supporting SECY-12-0157, Consideration of 23 Additional Requirements for Containment Venting Systems for Boiling Water Reactors 24 with Mark I and Mark II Containments, dated November 26, 2012.
25 26 Enclosure H-4, Summary of Detailed Analyses for SECY-15-0085, of this appendix 27 summarizes the detailed analyses supporting SECY-15-0085, Evaluation of the 28 Containment Protection and Release Reduction for Mark I and Mark II Boiling-Water 29 Reactors Rulemaking Activities, dated June 18, 2015; the NRC subsequently published 30 the detailed analyses as NUREG-2206, Technical Basis for the Containment Protection 31 and Release Reduction Rulemaking for Boiling-Water Reactors with Mark I and Mark II 32 Containments, issued March 2018.
33 34 Enclosure H-5, Summary of Detailed Analyses for SECY-13-0112 and NUREG-2161, 35 of this appendix summarizes the detailed analyses supporting SECY-13-0112, 36 Consequence Study of a Beyond-Design-Basis Earthquake Affecting the Spent Fuel 37 Pool for a U.S. Mark I Boiling-Water Reactor, dated October 9, 2013, which was 38 documented in NUREG-2161, Consequence Study of a Beyond-Design-Basis 39 Earthquake Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water Reactor, 40 issued September 2014.
41 42 Enclosure H-6, Summary of Detailed Analyses in COMSECY-13-0030, Enclosure 1, of 43 this appendix summarizes the detailed analyses supporting COMSECY-13-0030, Staff 44 Evaluation and Recommendation for Japan Lessons-Learned Tier 3 Issue on Expedited 45 Transfer of Spent Fuel, dated November 12, 2013.
46 47 Level 1 success criteria analyses have used MELCOR, as noted in Figure H-11 (see, for 48 example, NUREG/CR-7177, Compendium of Analyses to Investigate Select Level 1 49
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-66 Probabilistic Risk Assessment End-State Definition and Success Criteria Modeling Issues, 1
issued May 2014). The discussion of the MACCS code below notes a variety of NRC research 2
studies that have used MELCOR. Additionally, some international organizations have used the 3
code to assess severe accident management strategies.
4 5
MELCOR Code Structure 6
7 MELCOR is a modular code consisting of three general types of packages: (1) basic physical 8
phenomena (i.e., hydrodynamicscontrol volume and flowpaths, heat and mass transfer to 9
structures, gas combustion, and aerosol and vapor physics), (2) reactor-specific phenomena 10 (i.e., decay heat generation, core degradation and relocation, ex-vessel [outside the reactor 11 vessel] phenomena, and engineering safety systems), and (3) support functions 12 (i.e., thermodynamics, equations of state, material properties, data-handling utilities, and 13 equation solvers). These packages model the major systems of an NPP and their associated 14 interactions. The various code packages have been written with well-defined interfaces 15 between them. This allows the exchange of complete and consistent information among them 16 so that all phenomena are coupled at every step.
17 18 MELCOR modeling makes use of a control volume approach in describing the plant system. No 19 specific nodalization (how the control volumes are defined) of a system is forced on the user, 20 which allows a choice of the degree of detail appropriate to the task at hand. Reactor-specific 21 geometry is imposed only in modeling the reactor core. Even here, one basic model suffices for 22 representing various core and fuel assembly designs, and a wide range of levels of modeling 23 detail is possible.
24 25 MELCOR Source Term 26 27 The MELCOR output binary plot file contains the time-dependent variables of interest as a 28 function of time at a frequency specified by the user. Of interest in Level 2 and Level 3 29 consequence analyses, MELCOR provides data on fluid flows and radionuclide transport to the 30 environment through flowpaths identified as release paths. This information constitutes the 31 source term and defines the magnitude and timing of the release of radionuclides. It is 32 characterized by the following MELCOR plot variables:
33 34 nominal aerosol density 35 36 fluid temperature 37 38 enthalpy 39 40 cumulative fluid mass flow 41 42 released radioactive mass for each radionuclide class 43 44 aerosol size distribution 45 46 This information can be converted into a MACCS input file by the MelMACCS preprocessor 47 code. The sections below describe MelMACCS, along with other associated codes.
48 49
H-67 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 ASME/ANS Level 2 PRA Standard 1
2 In January 2015, ASME/ANS issued for trial use ASME/ANS RA-S-1.2-2014: Severe Accident 3
Progression and Radiological Release (Level 2) PRA Standard for Nuclear Power Plant 4
Applications for LWRs. The NRCs Site Level 3 PRA Level 2 analysis team used a 5
prepublication draft of this trial use Level 2 PRA standard in a pilot application to perform a 6
self-assessment of its draft internal events and floods Level 2 PRA.
7 8
Severe Accident Consequence Analysis 9
10 The MELCOR Accident Consequence Code System (MACCS) 11 12 MACCS is the NRC code used to estimate the offsite consequences associated with a 13 hypothetical release of radioactive material into the atmosphere from a severe accident at an 14 NPP. The code models atmospheric transport and dispersion (ATD); mitigative actions based 15 on dose projections; dose accumulation by several pathways, including food and water 16 ingestion; early and latent health effects; and economic costs. MACCS is currently the only 17 code used in the United States for the offsite consequence analyses portion of NPP Level 3 18 PRAs.
19 20 As indicated in the main body of this NUREG, the NRC uses MACCS to estimate the averted 21 offsite property damage cost and the averted offsite dose cost elements in the performance of 22 cost-benefit analyses as part of backfit and regulatory analyses. The NRC has also used 23 MACCS to support calculations of individual latent cancer fatality and prompt fatality risks for 24 comparison to quantitative health objectives. As with the previous discussion on MELCOR, 25 recent examples in which the NRC used MACCS in regulatory analyses include SECY-12-0157, 26 SECY-15-0085, SECY-13-0112, and COMSECY-13-0030. The U.S. NPP license renewal 27 applicants use MACCS to support the plant-specific evaluation of severe accident mitigation 28 alternatives (SAMAs) that may be required as part of the applicants environmental report for 29 license renewal. Additionally, MACCS is used in severe accident analyses and severe accident 30 mitigation design alternative (SAMDA) assessments for environmental analyses supporting 31 design certification, early site permit, and combined construction and operating license reviews 32 for new reactors.
33 34 A variety of NRC research studies also used MACCS. The State-of-the-Art Reactor 35 Consequence Analyses (SOARCA) project used MELCOR and MACCS to develop best 36 estimates of the offsite radiological health consequences for potential severe reactor accidents 37 at Peach Bottom Atomic Power Station (Peach Bottom), the Surry Power Station, and the 38 Sequoyah Nuclear Plant. The MELCOR and MACCS best practices as applied in the 2012 39 SOARCA project were respectively documented in NUREG/CR-7008, MELCOR Best Practices 40 as Applied in the State-of-the-Art Reactor Consequence Analyses Project, and 41 NUREG/CR-7009, MACCS Best Practices as Applied in the State-of-the-Art Reactor 42 Consequence Analyses Project, both issued August 2014. Three SOARCA uncertainty 43 analyses have also been completed, including one for the Peach Bottom unmitigated long-term 44 station blackout, documented in NUREG/CR-7155, State-of-the-Art Reactor Consequence 45 Analyses Project: Uncertainty Analysis of the Unmitigated Long-Term Station Blackout of the 46 Peach Bottom Atomic Power Station, issued May 2016. These studies propagated uncertainty 47 for a variety of key uncertain MELCOR and MACCS parameters to develop insights into the 48 overall sensitivity of SOARCA results and conclusions to input uncertainty and to identify the 49 most influential input parameters for accident progression and offsite consequences. MACCS 50 was also used in a consequence study of a beyond-design-basis earthquake affecting the spent 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-68 fuel pool for a U.S. Mark I boiling-water reactor and is documented in NUREG-2161. In 1
addition, the NRCs Full-Scope Site Level 3 PRA for a reference NPP site uses MACCS to 2
support the offsite consequence analyses.
3 4
MACCS Code Structure 5
6 The MACCS code is subdivided into three modules that handle the various components of the 7
consequence analysis calculation: ATMOS, EARLY, and CHRONC. These modules estimate 8
consequences in sequential steps:
9 10
- 1.
ATMOS models atmospheric transport and deposition of radioactive materials onto land 11 and water bodies.
12 13
- 2.
EARLY calculates the acute and lifetime doses, along with the associated health effects, 14 during the emergency phase simulation.
15 16
- 3.
CHRONC calculates the estimated exposures and health effects during an intermediate 17 period of up to 1-year (intermediate phase) and computes the long-term (e.g., 50 years) 18 exposures and health effects (late-phase model). CHRONC also calculates the 19 economic costs of the intermediate and long-term protective actions, as well as the cost 20 of the emergency response actions in the EARLY module.
21 22 The following sections summarize the MACCS code models. More detailed descriptions appear 23 in the MACCS Code User Guide and Model Description, which includes NUREG/CR-4691, 24 MELCOR Accident Consequence Code System, issued February 1990 (NRC, 1990a) and 25 NUREG/CR-6613, Code Manual for MACCS2, issued May 1998 (NRC, 1998).
26 27 Atmospheric Transport and Dispersion 28 29 ATMOS models the dispersion of radioactive materials released into the atmosphere using the 30 straight-line Gaussian plume segment model with provisions for meander and surface 31 roughness effects. The ATD model treats buoyant plume rise, initial plume size caused by 32 building wake effects, release of up to 500 plume segments, dispersion under given 33 meteorological conditions, deposition under given dry and wet (precipitation) conditions, and 34 decay and ingrowths of up to 150 radionuclides and a maximum of six generations.
35 36 The analyst has the option of using a single weather sequence. Sampling among multiple 37 weather sequences is used in probabilistic consequence analysis studies to evaluate the 38 variability in consequences that can result from uncertain weather conditions at the time of a 39 future, hypothetical release of radioactive material. The results generated by the ATD model 40 include radionuclide concentrations in air, on land, and as a function of time and distance from 41 the release source; these results are subsequently used to model early, intermediate, and 42 long-term phase radiological exposure, as discussed below.
43 44 Early (Emergency) Phase Protective Actions and Exposure Pathways 45 46 The EARLY module in MACCS assesses the time period immediately following a radioactive 47 release while releases are ongoing. This is analogous to the emergency phase of a severe 48 accident. Early phase exposure calculations account for reductions in dose from the use of 49 emergency response measures such as sheltering, evacuation, and relocation of the population.
50
H-69 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 MACCS models sheltering and evacuation for user-specified population cohorts.24 Different 1
shielding factors for the different exposure pathways (i.e., cloudshine, groundshine, inhalation, 2
and deposition on the skin) are associated with three types of activities: (1) normal activity, 3
(2) sheltering, and (3) evacuation.
4 5
Intermediate Phase Protective Actions and Exposure Pathways 6
7 MACCS can model an intermediate phase following the end of the early phase. The only 8
protective action modeled in this phase is relocation. If the projected dose to a population 9
exceeds a user-specified threshold over a user-specified time duration, the population is 10 assumed to be relocated to an uncontaminated area for the entire duration of this phase. The 11 user defines a corresponding per-capita per diem economic cost. If the projected dose does not 12 reach the user-specified threshold, MACCS models exposure pathways for groundshine and 13 inhalation of resuspended material.
14 15 Long-Term Phase Protective Actions and Exposure Pathways 16 17 In the long-term phase, which follows the intermediate phase and can last, from months to 18 years, protective actions are defined to keep the dose to an individual below specified limits.
19 Protective actions in this phase include dose reduction measures, such as decontamination and 20 interdiction of contaminated areas. Decisions on protective actions are based on two sets of 21 independent criteria relating to whether land, at a specific location and time, is suitable for 22 human habitation (habitability) or agricultural production (farmability). Habitability and 23 farmability are defined by a set of user-specified maximum doses and a user-specified exposure 24 period to receive those doses. The long-term phase includes both direct exposure pathways 25 (i.e., groundshine, resuspension inhalation) and indirect exposure pathways through ingestion 26 (i.e., food and water consumption).
27 28 Health Effects Modeling 29 30 MACCS employs a user-specified dose conversion factor file based on the most recent 31 U.S. Environmental Protection Agency (EPA) guidance, currently, EPAs Federal Guidance 32 Report No. 13, Cancer Risk Coefficients for Environmental Exposure to Radionuclides, issued 33 September 1999. Federal Guidance Report No. 13 converts the integrated air concentration 34 and ground deposition of 825 radionuclides to a whole-body effective dose and individual organ 35 doses for 26 tissues and organs and for four exposure pathways. In general, the radiological 36 dose to a receptor (i.e., person) in each spatial element (i.e., an area of land) is the product of 37 the radionuclide concentration or quantity, the exposure duration, the shielding factor, the dose 38 conversion factor, and the usage factor (e.g., breathing rate). The total dose to an organ or the 39 whole body is then obtained by summation across the relevant exposure pathways and 40 radionuclides.
41 42 Offsite Consequence Measures 43 44 The results of a MACCS analysis can be reported in terms of population dose, health risks to 45 the public, land contamination, population subject to long-term protective actions, and economic 46 costs. Consequence results discussed in this section are conditional consequences 47 (i.e., assuming the accident occurs). Therefore, this section does not consider the different 48 24 Cohorts are subsets of the population with similar characteristics (e.g., school children in school at the time of the accident).
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-70 probabilities or frequencies of the different accident progression scenarios. Typical cost-benefit 1
analyses and SAMDA/SAMA analyses generally report the individual risks, population dose, 2
and economic costs as mean values (i.e., expected values). The values are averaged over 3
sampled weather conditions representing a year of meteorological data and over the entire 4
residential population within a circular or annular region. Past PRA applications have also 5
shown complementary cumulative distribution functions of these consequence measures (the 6
outputs of analysis), illustrating variability across weather conditions (inputs to the analysis).
7 8
Population Dose 9
10 As noted above, in general, the radiological dose to a receptor in each spatial element is the 11 product of the radionuclide concentration or quantity, the exposure duration, the shielding factor, 12 the dose conversion factor, and the usage factor (e.g., breathing rate). The total dose to an 13 organ or the whole body is then obtained by summation across the relevant exposure pathways 14 and radionuclides. Long-term population dose results are summed over the user-specified 15 areas of interest and reported in person-Sieverts.
16 17 Individual (Population-Weighted) Latent Cancer Fatality Risk and Early Fatality Risk 18 19 The individual, population-weighted, latent cancer fatality25 risk calculations include only the 20 direct exposure pathways (i.e., groundshine, cloudshine, cloud inhalation, and resuspension 21 inhalation) and exclude the ingestion (i.e., consumption of food and water) pathways. The 22 MACCS early fatality model provides a pooled risk estimate of death from any of a number of 23 competing causes of early death, such as hematopoietic, gastrointestinal, and pulmonary 24 syndromes. Only the early phase exposure pathways are considered in the calculation of 25 individual early fatality risk. The individual latent cancer fatality and early fatality risks are 26 computed over user-specified regions. For example, for a large light-water reactor, a 10-mile 27 radius circular region centered on the plant is used, for purposes of comparison to the latent 28 cancer fatality risk quantitative health objective, and within 1 mile of the site boundary is used, 29 for purposes of comparison to the prompt fatality risk quantitative health objective (NRC, 1986).
30 31 Economic Consequences 32 33 The offsite economic consequences model in MACCS estimates the direct offsite costs that 34 result from protective actions modeled to reduce radiation exposures to the public. The current 35 cost-based economic model treats the following costs:
36 37 Evacuation costs: The daily cost of compensation for evacuees could include food, 38 housing, transportation, and lost income.
39 40 Relocation costs: The costs associated with relocating individuals during the 41 intermediate and long-term phases.
42 43 Decontamination of property: Costs are to decontaminate inhabited areas and farmland.
44 45 Loss of use: Economic losses from loss of return on investment and depreciation of 46 property value are incurred while property is temporarily interdicted. The depreciation of 47 value of the buildings and other structures results from lack of habitation and 48 maintenance.
49 25 This is a fatal cancer incurred from radiological exposure.
H-71 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Condemnation of property: Economic losses result from the permanent interdiction of 2
property.
3 4
Disposal of contaminated farm products and interdiction of farming: The economic cost 5
is from the loss of sales of farm products.
6 7
To obtain the total offsite economic costs, all the costs for the six cost categories are summed 8
over the entire region of interest affected by the atmospheric release. Many of the values 9
affecting the economic cost model are user inputs and thus can account for a variety of costs 10 and can be adjusted for inflation, new technology, or changes in policy or practices.
11 12 Ongoing Updates 13 14 Work is ongoing to update the MACCS code to include additional state-of-practice modeling 15 approaches (SECY-12-0110, Consideration of Economic Consequences within the 16 U.S. Nuclear Regulatory Commissions Regulatory Framework, Enclosure 9, MELCOR 17 Accident Consequence Code System, Version 2 (MACCS2), dated August 14, 2012).
18 Alternate ATD models are being implemented within MACCS by adding the capability to use 19 results from the National Oceanic and Atmospheric Administrations HYbrid Single-Particle 20 Lagrangian Integrated Trajectory (HYSPLIT) code (Stein et al., 2015). This will allow the use of 21 models that may provide a better representation of atmospheric transport, dispersion, and 22 deposition at longer ranges or in complex windfields. In addition, an alternative economic model 23 will use regional gross domestic product-based input-output models to capture the upstream 24 supply chain impacts of affected industries outside areas directly affected by radiological 25 releases.
26 27 Associated Codes 28 29 WinMACCS 30 31 WinMACCS is a graphical user interface that assists the user in constructing and executing 32 MACCS input files. The graphical user interface acts as a wizard that identifies what input is 33 necessary for a particular calculation. WinMACCS allows the user to interact with graphical 34 tools to aid in user input by visualization, such as defining an evacuation network using a map 35 with the polar grid superimposed.
36 37 MelMACCS 38 39 MelMACCS is a graphical user interface that converts source term information from the severe 40 accident analysis code MELCOR into a form suitable for use in the consequence analysis code 41 MACCS. MelMACCS processes MELCOR information for use in the ATMOS package of 42 MACCS for atmospheric transport and dispersion. Not all MACCS variables for source term 43 input are directly obtained from a MELCOR plot file. The variables not provided are either 44 calculated from other values in the plot file or are requested in the MelMACCS interface.
45 46 SecPop 47 48 SecPop is a preprocessor code for MACCS that enables the use of site-specific population, 49 economic, and land use data in the calculation of offsite consequences. SecPop uses a 50 block-level database of the U.S. population based on the U.S. Census and county-level data for 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-72 economic information from the U.S. Department of Agriculture Census of Agriculture and 1
Bureau of Economic Analysis. SecPop allows the user to scale population and economic data 2
from the database years to a target year based on a user-specified growth rate. The output of 3
SecPop is a site file that is input into MACCS. NUREG/CR-6525, Revision 2, SecPop Version 4
4: Sector Population, Land Fraction, and Economic Estimation Program, issued June 2019, 5
provides more information.
6 7
COMIDA2 8
9 COMIDA2 is a preprocessor code that models the food-chain dose pathway. COMIDA2 can 10 calculate estimates of radionuclide concentrations in agricultural products after a radioactive 11 release following a hypothetical severe accident. This code calculates the uptake of 12 radioisotopes into the edible portions of plants as a function of the development of the plant. It 13 also considers the decay chains of nuclides, up to four daughters, and can, therefore, consider 14 the loss and ingrowth of radioisotopes in the plant.
15 16 17
H-73 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 ENCLOSURE H-2:
SUMMARY
OF THE STATE-OF-THE-ART REACTOR 1
CONSEQUENCE ANALYSES (SOARCA) PROJECT 2
3 Project Overview 4
5 The U.S. Nuclear Energy Commission (NRC) initiated the State-of-the-Art Reactor 6
Consequence Analyses (SOARCA) project to further its understanding of the realistic 7
consequences of severe reactor accidents. SOARCA addresses the consequences of rare but 8
severe accidents at commercial reactors in the United States. The SOARCA analysts focused 9
on accident progression, source term, and conditional consequences should the postulated 10 accidents occur. The project did not include within its scope new work to calculate the 11 frequencies associated with the postulated severe accidents.
12 13 The project, which began in 2006, combined information available at the time about the pilot 14 plants layout and operations, local population and site data, and emergency preparedness 15 plans. The NRC analyzed information using the MELCOR and MELCOR Accident 16 Consequence Code System (MACCS) suite of computer codes for integrated severe accident 17 progression and offsite consequence modeling. The modeling incorporated insights from 18 decades of research into severe reactor accidents.
19 20 Plants and Accident Scenarios Studied 21 22 The NRC staff initially evaluated potential consequences of select, important severe accidents 23 at the Peach Bottom Atomic Power Station (Peach Bottom) and Surry Power Station (Surry) 24 (NRC, 2012a). Selected accidents included station blackout scenarios for both plants and 25 bypass scenarios for Surry. Peach Bottom is a General Electric boiling-water reactor with a 26 Mark I containment, located in Pennsylvania; Surry is a Westinghouse 3-loop pressurized-water 27 reactor (PWR) with a subatmospheric large, dry containment, located in Virginia. The staff 28 subsequently evaluated a more limited set of scenarios at a third plant, the Sequoyah Nuclear 29 Plant (Sequoyah), a Westinghouse 4-loop PWR with an ice condenser containment, located in 30 Tennessee (NRC, 2019a). The Sequoyah study focused on issues unique to the ice condenser 31 containment design because of its lower design pressure and smaller volume. For this third 32 study, the staff also conducted an uncertainty analysis for one of the scenarios concurrently with 33 the deterministic calculations, in which it conducted uncertainty analyses for one scenario each 34 at the Peach Bottom and Surry plants after the initial deterministic SOARCA calculations 35 (NRC, 2016b and NRC, 2015a, a draft that will be updated for the Surry uncertainty analysis).
36 37 The SOARCA projects main findings fall into three basic areas: how a reactor accident 38 progresses, how existing systems and emergency measures can affect an accidents outcome, 39 and how an accident would affect public health. The 2012 project findings, corroborated by 40 subsequent uncertainty analyses and the Sequoyah analyses, include the following:
41 42 Existing resources and procedures can stop an accident, slow it down, or reduce its 43 impact before it can affect public health, if successfully implemented.
44 45 Even if accidents proceed without successful intervention, they generally take longer to 46 happen and release less radioactive material within the simulation time than earlier 47 analyses suggested. Hence, some accidents that may have been traditionally classified 48 as large-early release scenarios (e.g., interfacing systems loss-of-coolant accident for 49
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-74 Surry) may no longer contribute to large early release frequency because release is 1
delayed beyond the time assumed to successfully evacuate the close-in population.
2 3
The analyzed accidents pose essentially zero risk of early death (from radiological 4
consequences) and only a negligible increase in the risk of a long-term cancer death, to 5
a member of the public.
6 7
The small risk for the calculated individual cancer fatalities is dominated by the long-term 8
accumulation of very small doses (below allowable habitability criteria) to the public in 9
the affected area.
10 11 The NRC makes supporting technical information available on the deterministic Peach Bottom 12 analysis and Surry analysis in NUREG/CR-7110, State-of-the-Art Reactor Consequence 13 Analyses Project: Peach Bottom Integrated Analysis, Volume 1, issued May 2013 14 (NRC, 2013a), and NUREG/CR-7110, State-of-the-Art Reactor Consequence Analyses Project:
15 Surry Integrated Analysis, Volume 2, issued August 2013 (NRC, 2013b). NUREG/BR-0359, 16 Modeling Potential Reactor Accident Consequences, issued December 2012, describes this 17 Peach Bottom and Surry research for a general audience. The Peach Bottom uncertainty 18 analysis of the unmitigated long-term station blackout (LTSBO) scenario is available in 19 NUREG/CR-7155, State-of-the-Art Reactor Consequence Analyses Project: Uncertainty 20 Analysis of the Unmitigated Long-Term Station Blackout of the Peach Bottom Atomic Power 21 Station, issued May 2016. The Sequoyah integrated deterministic and uncertainty analyses 22 are available in NUREG/CR-7245, State-of-the-Art Reactor Consequence Analyses (SOARCA) 23 Project: Sequoyah Integrated Deterministic and Uncertainty Analyses, issued October 2019 24 (NRC, 2019a). The Surry uncertainty analysis of the unmitigated short-term station blackout 25 (STSBO), including a potential induced steam generator tube rupture, is available in 26 NUREG/CR-7262, State-of-the-Art Reactor Consequence Analyses (SOARCA) Project:
27 Uncertainty Analysis of the Unmitigated Short-Term Station Blackout of Surry Power Station, 28 issued in 2020 (NRC, 2020).
29 30 Results of the Mitigated Scenarios 31 32 One of the goals of the original Peach Bottom and Surry SOARCA analyses was to study the 33 benefits of the then-recently established mitigation measures in Title 10 of the Code of Federal 34 Regulations (10 CFR) 50.54(hh) (formerly B.5.b) for the accidents analyzed. All mitigated cases 35 of SOARCA scenarios, except for one, result in prevention of core damage or no offsite release 36 of radioactive material. The only mitigated case still leading to an offsite release was the Surry 37 STSBO-induced steam generator tube rupture. In this case, mitigation is still beneficial in that it 38 keeps most radioactive material inside containment and delays the onset of containment failure 39 by about 2 days (NRC, 2012a). The NRC made no attempt to quantify the likelihood that 40 mitigation would be successful and conducted no human reliability analysis. Instead, the 41 scenarios were analyzed twiceone case assuming that mitigation was successful and an 42 unmitigated case assuming successful mitigation did not occur.
43 44 The mitigated scenarios show zero individual early fatality risk from radiation exposure and zero 45 risk or a very small risk of long-term cancer fatalities, depending on the specific scenario. The 46 SOARCA results demonstrate the potential benefits of the mitigation measures analyzed in this 47 project. SOARCA shows that successful mitigation either prevents core damage or prevents, 48 delays, or reduces offsite health consequences.
49 50
H-75 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 The NRC was nearing completion of the SOARCA analyses when the accident at the 1
Fukushima Dai-ichi plants in Japan occurred in 2011. The NRC did not redefine or reanalyze 2
the scenarios following the Fukushima accident. It included a brief comparison to the 3
Fukushima Dai-ichi nuclear power plant accident in the Peach Bottom uncertainty analysis 4
technical report (NRC, 2016b). None of the SOARCA analyses included the use of flexible 5
coping strategies (FLEX) because FLEX was still under development at the time of the analysis.
6 7
Results of Unmitigated Scenarios 8
9 Even the unmitigated scenarios result in essentially zero individual early fatality risk from 10 radiation exposure. Although these unmitigated scenarios result in core damage and release of 11 radioactive material to the environment, the release is delayed, which allows the population to 12 take protective actions (including evacuation and sheltering). The individual risk of long-term 13 cancer fatality is calculated to be very small. Table H-8 shows the point estimates 14 (NRC, 2012a; NRC, 2019a), as well as uncertainty analysis bands where available 15 (NRC, 2016b; NRC, 2019a; NRC, 2020), for the conditional risk (assuming that the accident 16 occurs) to the public living between 0 and 10 miles from the plants, assuming the linear no-17 threshold dose response model. The SOARCA analyses calculated risk to individuals out to 50 18 miles from the plants. For some scenarios, the risks to the 10- to 30-mile population (outside 19 the plume exposure pathway emergency planning zone) are slightly higher than the risk to the 20 0- to 10-mile population. Considering that the frequencies estimated for these scenarios are in 21 the range of one per 100,000 to one per 30 million reactor-years, the absolute risk of long-term 22 cancer fatality from the analyzed SOARCA scenarios is projected to be negligible.
23 24 Table H-8 Conditional Annual Average Individual Latent Cancer Fatality Risk from 25 SOARCA Unmitigated Scenarios within 10 miles of the Plant 26 Scenario Peach Bottom Surry Sequoyah LTSBO STSBO LTSBO STSBO Induced SGTR ISLOCA STSBO Point estimatea 9x10-5 2x10-4 5x10-5 9x10-5 3x10-4 3x10-4 8x10-5 5th percentileb 3x10-5 N/A N/A 3x10-7 N/A N/A 1x10-8 95th percentileb 4x10-4 2x10-4 2x10-4 a The Peach Bottom and Surry accident simulations were carried out to 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br />; the Sequoyah accident was 27 simulated out to 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br />.
28 b The Peach Bottom uncertainty analysis simulation was carried out to 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br />; the Surry and Sequoyah uncertainty 29 analysis simulations were carried out to 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br />. The Surry STSBO 5th and 95th percentiles include induced steam 30 generator tube rupture (SGTR).
31 32 Notable Assumptions 33 34 The SOARCA models assume that 99.5 percent of the population residing in the 10-mile 35 emergency planning zone will evacuate as ordered. Shadow evacuationsthe voluntary 36 evacuation of members of the public who have not been ordered to evacuateare also 37 modeled for 10- to 15-mile or 10- to 20-mile radius annular rings around the plants. The 38 Sequoyah analysis explicitly considered the potential impact of the seismic initiating event on 39 emergency response and included sensitivity calculations for extended sheltering-in-place with 40 and without degraded shielding caused due to structural damage, in case evacuation is delayed 41 (NRC, 2019a). The Peach Bottom and Surry calculations assume the unmitigated accident 42 releases can be terminated within 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br />. The Sequoyah calculation assumes releases can 43 be terminated within 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br />.
44
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-76 1
Uses of SOARCA Models and Insights 2
3 SOARCA models and insights were subsequently leveraged in a variety of projects, including 4
the analyses summarized in Enclosures H-3 through H-6 to this appendix. The NRC also 5
published research Information Letter 19-01, Benefits and Uses of the State-of-the-Art Reactor 6
Consequence Analyses (SOARCA) Project, issued 2019 (NRC, 2019c), which summarizes 7
many of the uses of the SOARCA body of work.
8 9
H-77 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 ENCLOSURE H-3:
SUMMARY
OF DETAILED ANALYSES FOR 1
SECY-12-0157, CONSIDERATION OF ADDITIONAL REQUIREMENTS 2
FOR CONTAINMENT VENTING SYSTEMS FOR BOILING WATER 3
REACTORS WITH MARK I AND MARK II CONTAINMENTS 4
5 This enclosure summarizes the 2012 analyses supporting the consideration of additional 6
requirements for containment venting systems for boiling-water reactors (BWRs) with Mark I 7
and Mark II containments, following the 2011 accident at the Fukushima Dai-ichi nuclear power 8
plant in Japan. The contents of this enclosure should be considered with the Commission 9
direction in its staff requirements memorandum (SRM)-SECY-12-0157, Consideration of 10 Additional Requirements for Containment Venting Systems for Boiling Water Reactors with 11 Mark I and Mark II Containments, dated March 19, 2013, and the subsequent analysis 12 described in Enclosure H-4, Summary of Detailed Analyses for SECY-15-0085, Evaluation of 13 the Containment Protection and Release Reduction for Mark I and Mark II Boiling-Water 14 Reactors Rulemaking Activities to this appendix. A summary of SRM-SECY-12-0157 is 15 provided at the end of this enclosure.
16 17 Problem Statement and Regulatory Objectives 18 19 The accident that occurred on March 11, 2011, at the Fukushima Dai-ichi nuclear power plant in 20 Japan underscored the potential need for nuclear power plant safety improvements related to 21 beyond-design-basis events involving natural hazards and their causal effects on plant systems 22 and barriers from an extended loss of electrical power and access to heat removal systems. As 23 part of its response to lessons learned from this accident, the U.S. Nuclear Regulatory 24 Commission (NRC) staff issued Order EA-12-050, Issuance of Order to Modify Licenses with 25 Regard to Reliable Hardened Containment Vents, dated March 12, 2012. This order required 26 licensees that use the boiling-water reactor (BWR) with Mark I and Mark II containment designs 27 to install hardened containment vents. These hardened containment vents would address 28 problems encountered during the Fukushima accident by providing plant operators with 29 improved methods for venting containment during accident conditions and thereby preventing 30 containment overpressurization and subsequent failure.
31 32 While developing the requirements for Order EA-12-050, the staff acknowledged that questions 33 remained about maintaining containment integrity and limiting the release of radiological 34 materials if licensees used the venting systems during severe accident conditions. In 35 SECY-11-0137, Prioritization of Recommended Actions to be Taken in Response to Fukushima 36 Lessons Learned, dated October 3, 2011, the staff also identified the addition of an engineered 37 filtered vent system to improve reliability and limit the release of radiological materials should 38 the venting systems be used after significant core damage had occurred.
39 40 Regulatory Alternatives 41 42 The NRC considered four regulatory alternatives that address containment venting systems for 43 BWRs with Mark I and Mark II containments in the regulatory analysis performed in support of 44 SECY-12-0157:
45 46 Option 1: Reliable Hardened Vents (Status Quo). Continue to implement 47 Order EA-12-050 and install reliable hardened vents to reduce the probability of failure of 48 BWR Mark I and Mark II containments and take no additional action to improve their 49
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-78 ability to operate under severe accident conditions or to require the installation of an 1
engineered filtered vent system. This alternative represented the status quo and served 2
as the regulatory baseline against which the costs and benefits of other alternatives 3
were measured.
4 5
Option 2: Severe-Accident-Capable Venting System Order (without Filter). Upgrade or 6
replace the reliable hardened vents required by Order EA-12-050 with a containment 7
venting system designed and installed to remain functional during severe accident 8
conditions. This alternative would increase confidence in maintaining containment 9
functionality following core damage events. Although venting containment during severe 10 accident conditions may result in significant radiological releases, it would prevent 11 overpressurization and reduce the probability of gross containment failures that could 12 hamper accident management and result in larger radiological releases.
13 14 Option 3: Filtered Severe Accident Venting System Order. Design and install an 15 engineered filtered containment venting system that is intended to prevent the release of 16 significant amounts of radiological materials for dominant severe accident scenarios at 17 BWRs with Mark I and Mark II containments. The engineered filtering system would 18 need to operate under severe accident conditions to reduce the amount of radiological 19 material released to the environment from venting containment to prevent 20 overpressurization.
21 22 Option 4: Severe Accident Confinement Strategies. Pursue development of 23 requirements and technical acceptance criteria for confinement strategies and require 24 licensees to justify operator actions and systems or combinations of systems 25 (e.g., suppression pools, containment sprays, and engineered filters) to accomplish the 26 function and meet the requirements. For this option, the staff did not evaluate a specific 27 filtering system; instead, it drew on insights from various sensitivity studies to define a 28 possible approach.
29 30 Safety Goal Evaluation 31 32 This regulatory analysis required a safety goal evaluation because each of the alternatives was 33 considered a generic safety enhancement backfit subject to the substantial additional protection 34 standard in Title 10 of the Code of Federal Regulations (10 CFR) 50.109 (a)(3). Each 35 alternative, if implemented, would improve containment performance by reducing the probability 36 of containment failure, given the assumed occurrence of a severe accident scenario, or the 37 amount of radiological material released to the environment from a severe accident scenario, or 38 both. However, since none of the alternatives would impact the frequency of core damage 39 accidents (i.e., the change in core damage frequency (CDF) for each alternative relative to the 40 regulatory baseline was zero), the safety goal screening criteria in the regulatory analysis 41 guidelines could not be used to determine whether each alternative could result in a substantial 42 increase in overall protection of public health and safety.
43 44 Therefore, the Japan Lessons-Learned Steering Committee (NRC, 2011c) evaluated whether 45 imposition of requirements for severe-accident-capable or filtered venting systems would satisfy 46 the substantial additional protection standard. The Japan Lessons-Learned Steering Committee 47 decided that the staff should take the next step within the regulatory analysis process by 48 estimating and evaluating the costs and benefits.
49 50
H-79 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Technical Evaluation 1
2 To support the assessment of the quantitative costs and benefits of severe-accident-capable 3
vents (Option 2) and filtered containment venting (Option 3), the staff (with support from Sandia 4
National Laboratories) analyzed selected accident scenarios for a BWR plant with a Mark I 5
containment. The staff used the NRCs severe accident analysis code, MELCOR, and the 6
MELCOR Accident Consequence Code System (MACCS) to perform the analysis. The staff 7
used the MELCOR code to calculate fission product release estimates for each of the selected 8
accident scenarios, and this information was used in MACCS to calculate the offsite radiological 9
consequences for each of the selected accident scenarios. Enclosure H-1, Description of 10 Analytical Tools and Capabilities, to this appendix describes these codes and their capabilities 11 in more detail.
12 13 Accident Scenario Selection 14 15 The selection of accident scenarios considered for MELCOR and MACCS analyses was 16 informed by both the State-of-the-Art Reactor Consequence Analyses (SOARCA) studies and a 17 study of the Fukushima accident that Sandia National Laboratories was performing at the time.
18 Two of the accident scenarios from the SOARCA study for Peach Bottom Atomic Power Station 19 (Peach Bottom) selected for MELCOR and MACCS analyses were (1) the long-term station 20 blackout (LTSBO) and (2) the short-term station blackout (STSBO).
21 22 MELCOR Severe Accident Progression and Source Term Analyses 23 24 Thirty MELCOR cases were run, simulating accident scenarios with different possible outcomes.
25 Cases 2, 3, 6, 7, 12, 13, 14, and 15 became MELCOR base cases, with the results used for 26 MACCS consequence calculations and for the regulatory analysis. The remaining cases were 27 run as variations of the base cases for sensitivity analyses. The base cases represented the 28 following accident scenarios:
29 30 Case 2: No venting or spray 31 32 Case 3: Wetwell venting but no spray 33 34 Case 6: Core spray only 35 36 Case 7: Core spray with wetwell venting 37 38 Case 12: Drywell venting 39 40 Case 13: Drywell venting and drywell spray 41 42 Case 14: Drywell spray only 43 44 Case 15: Drywell spray with wetwell venting 45 46 Collectively, the base cases encompassed all representative combinations of prevention and 47 mitigation measures considered in the description of alternatives used in the regulatory analysis.
48 Case 2 with no venting or spray mapped to Option 1 (status quo). Likewise, all venting cases 49 (Cases 3, 7, 12, 13, and 15) mapped to Option 2 (severe-accident-capable vent) andwhen 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-80 considered in combination with an external filterto Option 3 (filtered vent). Case 6 and 1
Case 14 (both without venting but with sprays) were considered variations of Option 1.
2 3
The selected MELCOR accident scenarios were organized into four groups to compare the 4
effect of venting and additional mitigation actions:
5 6
Base case: Case 2 and Case 3 7
8 Core spray after reactor pressure vessel failure: Case 6 and Case 7 9
10 Main steamline failure with drywell venting at 24 hour2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />s: Case 12 and Case 13 11 12 Drywell spray at 24 hour2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />s: Case 14 and Case 15 13 14 MACCS Consequence Analyses 15 16 The analysts used MACCS to perform consequence analyses for selected accident scenarios to 17 calculate offsite doses and land contamination and their effect on members of the public with 18 respect to individual prompt and latent cancer fatality risk, land contamination areas, population 19 dose, and economic costs. They used the Peach Bottom unmitigated LTSBO MACCS input 20 deck from the SOARCA study, with two key modifications. One modification was the modeling 21 of the ingestion pathway, which was excluded in the SOARCA analyses. Another modification 22 was the use of revised source terms calculated from the MELCOR analyses for this study to 23 account for variation in the LTSBO scenario and the effect of adding an external filter to the vent 24 paths.
25 26 Risk Evaluation 27 28 The analysts constructed a simplified event tree to estimate the radiological release frequencies 29 of the MELCOR accident scenarios. Coupled with the MACCS consequence results developed 30 for each MELCOR scenario, this simplified event tree provided the information needed to 31 assess the reduction in risk resulting from the installation of a severe-accident-capable venting 32 system. The simplified event tree structure used to estimate radiological release frequencies 33 was designed to allow assessment of a wide range of severe-accident-capable vent system 34 designs that varied depending on (1) where the vent is attached (wetwell or drywell), (2) how the 35 vent is actuated (manually by the operator or passively using a rupture disk), and (3) whether 36 the severe-accident-capable venting system has a filter. Table H-9 identifies the nine 37 hypothetical plant modifications (Mods) that were assessed using the simplified event tree 38 structure.
39 40
H-81 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-9 Hypothetical Plant Modifications 1
Identifier Severe-Accident-Capable Vent Filter Severe-Accident-Capable Vent Location Severe-Accident-Capable Vent Actuation Mod 0 (current situation)
NA None NA Mod 1 No Wetwell Manual Mod 2 No Wetwell Passive Mod 3 No Drywell Manual Mod 4 No Drywell Passive Mod 5 Yes Wetwell Manual Mod 6 Yes Wetwell Passive Mod 7 Yes Drywell Manual Mod 8 Yes Drywell Passive 2
The simplified event tree shown in Figure H-13 traced the accident progression starting from the 3
onset of core damage. The first two event tree headings parsed the total CDF according to the 4
type of hazard that initiated the accident (internal or external) and the type of core damage 5
sequence (station blackout [SBO] sequences, bypass sequences in which venting containment 6
has little or no impact because the containment is bypassed, fast sequences that evolve rapidly 7
and reduce the available time for the operator to manually open the severe-accident-capable 8
vent, and other sequences). Subsequent event tree headings consider (1) operation of the 9
severe-accident-capable vent, (2) offsite power recovery (which is influenced by the type of 10 hazard that initiated the accident), and (3) the availability of a water supply (portable pump) to 11 the drywell. Each sequence was assigned to one of four possible containment status end 12 states:
13 14 Vented: The severe-accident-capable vent is opened, preventing containment 15 overpressurization failure. A source of water to the drywell exists, preventing liner 16 melt-through.
17 18 Liner Melt-through (LMT): The severe-accident-capable vent is opened, preventing 19 containment overpressurization failure. No source of water to the drywell exists, and 20 liner melt-through occurs.
21 22 Overpressurization (OP): The severe-accident-capable vent is closed, resulting in 23 containment overpressurization failure. A source of water to the drywell exists, 24 preventing liner melt-through.
25 26 OP + LMT: The severe-accident-capable vent is closed, resulting in containment 27 overpressurization failure. No source of water to the drywell exists, and liner 28 melt-through occurs.
29 30
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-82 1
Figure H-13 Simplified Event Tree Structure 2
3 This simplified event tree delineates 16 post-core-damage accident sequences. Each sequence 4
in the simplified event tree was assigned to a unique containment status. This mapping, 5
together with the definitions of the hypothetical plant modifications shown in Table H-10, 6
determined the specific MELCOR case and MACCS calculation that applies to each sequence, 7
as shown in Table H-11.
8 9
Table H-10 Mapping of Simplified Event Tree Sequences to Plant Modifications and 10 MELCOR Cases 11 Modification Description Release Sequence Containment Status End State Mod Filter Location Actuation Vented Sequence: 1, 4, 5, 10, and 13 LMT Sequence: 2, 6, 11, and 14 OP Sequence: 7 OP + LMT Sequence: 3, 8, 9, 12, 15, and 16 0
NA NA None NA NA Case 6 Case 2 1
No Wetwell Manual Case 7 or 15 (no filter)
Case 3 (no filter)
Case 6 Case 2 2
No Wetwell Passive 3
No Drywell Manual Case 13 (no filter)
Case 12 (no filter)
Case 14 Case 2 4
No Drywell Passive 5
Yes Wetwell Manual Case 7 or 15 (filter)
Case 3 (filter)
Case 6 Case 2 6
Yes Wetwell Passive 7
Yes Drywell Manual Case 13 (filter)
Case 12 (filter)
Case 14 Case 2 8
Yes Drywell Passive 12 Analysts developed parameter values based on information from a variety of sources to 13 estimate the radiological release frequencies for each sequence in the simplified event tree.
14 Table H-11 summarizes this information.
15 16
H-83 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-11 Parameter Values Used to Estimate Radiological Release Frequencies 1
Parameter Value Basis CDF 2.0x10-5 per reactor-year (ry)
Standardized Plant Analysis Risk (SPAR) external hazard models Fraction of total CDF due to external hazards 0.8 SPAR external hazard models; review of previous probabilistic risk assessments (PRAs)
Breakdown of sequence types for internal hazardsa Other 0.83 SPAR internal hazard models SBO 0.12 Bypass 0.05 Fast 0.01 Breakdown of sequence types for external hazardsa Other 0.95 Review of previous PRAs; engineering judgment Bypass 0.05 Probability that severe-accident-capable vent fails to open Mod 0 1
Vent not installed Mods 1, 3, 5, 7other or SBO 0.3 SPAR-H method (manual vent; longer available time)
Mods 1, 3, 5, 7fast 0.5 SPAR-H method (manual vent; shorter available time)
Mods 2, 4, 6, 8 0.001 Engineering judgment (passive vent mechanical failure)
Conditional probability that offsite power is not recovered by the time of lower head failure given not recovered at the time of core damage (internal hazards) 0.38 Historical data (NUREG/CR-6890)
Probability that portable pump for core spray or drywell spray fails 0.3 SPAR-H; consistent with SPAR B.5.b study by Idaho National Laboratory a The values may not total to one due to rounding.
2 3
MACCS is used to calculate the mean conditional offsite radiological consequences per release, 4
conditioned on the assumed occurrence of the accident scenario that each MELCOR case 5
represented. Table H-12 provides the mean results for the 50-mile population dose and 50-mile 6
offsite cost consequence metrics.
7 8
Table H-12 Mean MACCS Consequence Results for Selected MELCOR Accident 9
Scenarios 10 Casea,b Core Spray Drywell Spray Venting Location 50-mile Population Dose (person-rem/event) 50-mile Offsite Cost (million $/event) 2 no no no NA 514,000 1,910 3F no no yes wetwell 183,000 274 3NF no no yes wetwell 397,000 1,730 6
yes no no NA 305,000 847 7F yes no yes wetwell 37,300 18 7NF yes no yes wetwell 235,000 484 12F no no yes drywell 232,000 391 12NF no no yes drywell 3,810,000 33,300 13F no yes yes drywell 59,990 38 13NF no yes yes drywell 3,860,000 33,000 14 no yes no NA 86,100 116 15F no yes yes wetwell 43,300 20 15NF no yes yes wetwell 280,000 588 a F: filtered case 11 b NF: not filtered case 12 13
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-84 The analysts calculated risk by combining the frequencies of radiological releases with their 1
conditional offsite radiological consequences. Table H-13 provides the point estimate values for 2
the 50-mile population dose risk and the 50-mile offsite cost risk for each of the nine 3
hypothetical plant modifications.
4 5
Table H-13 Point Estimate Risk Values for Each Hypothetical Plant Modification 6
Mod Vent Filtered Vent Location Vent Actuation 50-mile Population Dose Risk (person-rem/reactor-year [ry])
50-mile Offsite Cost Risk ($/ry) 0 NA None NA 10.2
$37,884 1
No Wetwell Manual 7.2
$24,041 2
No Wetwell Passive 5.9
$18,117 3
No Drywell Manual 54.5
$452,466 4
No Drywell Passive 73.5
$630,000 5
Yes Wetwell Manual 4.5
$13,958 6
Yes Wetwell Passive 2.0
$3,717 7
Yes Drywell Manual 4.9
$14,540 8
Yes Drywell Passive 2.6
$4,642 7
8 Table H-14 provides the risk reductions (relative to Mod 0, the current situation) associated with 9
implementing plant modifications for the severe-accident-capable venting system (Mods 1 10 through 8). Figures H-14 and H-15 graphically illustrate this information.
11 12 Table H-14 Risk Reductions from Severe-Accident-Capable Venting System Plant 13 Modifications 14 Mod Vent Filtered Vent Location Vent Actuation Reduction in 50-mile Population Dose Risk (person-rem/ry)
Reduction in 50-mile Offsite Cost Risk ($/ry) 1 No Wetwell Manual 3.0
$13,842 2
No Wetwell Passive 4.3
$19,767 3
No Drywell Manual (44.3)a
($414,582) 4 No Drywell Passive (63.3)
($592,117) 5 Yes Wetwell Manual 5.7
$23,926 6
Yes Wetwell Passive 8.2
$34,166 7
Yes Drywell Manual 5.3
$23,344 8
Yes Drywell Passive 7.6
$33,242 a Negative values are shown using parentheses (e.g., negative 44.3 is displayed as (44.3)).
15
H-85 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-14 Reduction in 50-mile Population Dose Risk (person-rem/ry) 2 3
4 Figure H-15 Reduction in 50-mile Offsite Cost Risk ($/ry) 5 6
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-86 To gain further insight into the risk reductions afforded by the hypothetical plant modifications, 1
analysts performed a simple parametric Monte Carlo uncertainty analysis. They assigned an 2
uncertainty distribution to each of the parameters used to quantify the radiological release 3
frequencies and to each of the consequences. Table H-15 shows parameters that specify the 4
uncertainty distribution.
5 6
Table H-15 Parameter Uncertainty Distributions 7
Parameter Mean Distribution CDF 2.0x10-05/ry Lognormal; error factor = 10 Fraction of total CDF due to external hazards 0.8 Beta; = 0.5, = 0.125 Breakdown of sequence types for internal hazards Other 0.83 Dirichleta 1 (other) = 41 2 (SBO) = 6 3 (bypass) = 2.5 4 (fast) = 0.5 SBO 0.12 Bypass 0.05 Fast 0.01 Breakdown of sequence types for external hazards Other 0.95 Beta; (bypass) = 0.5, (bypass) = 9.5 Bypass 0.05 Probability that severe-accident-capable vent fails to open Mod 0 1
Held constant Mods 1, 3, 5, 7 other or SBO 0.3 Beta; = 0.5, = 1.167 Mods 1, 3, 5, 7fast 0.5 Beta; = 0.5, = 0.5 Mods 2, 4, 6, 8 0.001 Beta; = 0.5, = 499.5 Conditional probability that offsite power is not recovered by the time of lower head failure given not recovered at the time of core damage (internal hazards) 0.38 Beta; = 0.5, = 0.816 Probability that portable pump for core spray or drywell spray fails 0.3 Beta; = 0.5, = 1.167 Consequences Per Table H-6 Lognormal; error factor = 10 Within a given consequence category, consequences were assumed to be totally dependent.
a The Dirichlet distribution is a family of continuous multivariate probability distributions parameterized by a vector of 8
positive reals. It is a multivariate generalization of the Beta distribution. Dirichlet distributions are commonly used as 9
prior distributions in Bayesian statistics.
10 11 Figures H-16 and H-17 show the results26 of the parametric uncertainty analysis. These figures 12 show that, although somewhat higher, the mean values are very close to the corresponding 13 point estimates. In general, the ratio of the 95th percentile to the point estimate varies from 14 3.5 to 4.0 depending on the consequence category. The major contributors to uncertainty in the 15 risk reduction results were uncertainty in both the CDF and the conditional consequences.
16 17 26 These figures do not show the results of Mods 3 and 4 because the results are negative (i.e., detrimental compared to the status quo), as shown in Figures H-16 and H-17.
H-87 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Figure H-16 Uncertainty in Reduction in 50-mile Population Dose Risk 2
3 4
Figure H-17 Uncertainty in Reduction in 50-mile Offsite Cost Risk 5
6 7
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-88 These risk results that incorporated insights from the MELCOR and MACCS analyses led to the 1
following specific conclusions about severe-accident-capable venting:
2 3
The installation of an unfiltered wetwell severe-accident-capable venting system would 4
reduce public health risk and offsite economic cost risk. By contrast, the installation of 5
an unfiltered drywell severe-accident-capable venting system would increase public 6
health risk and offsite economic cost risk.
7 8
The installation of a filtered severe-accident-capable venting system (attached to either 9
the wetwell or the drywell) would reduce public health risk and offsite economic cost risk.
10 The installation of an external filter into the severe-accident-capable venting system is 11 preferable.
12 13 By preventing containment overpressurization failure, the successful operation of a 14 severe-accident-capable venting system promotes access to plant areas where portable 15 pumps could be installed to provide core debris cooling.
16 17 Passive actuation (via a rupture disk) is preferred to manual actuation because it is more 18 reliable and thus results in larger risk reductions.
19 20 The uncertainty in the amount of risk reduction achieved by the installation of a 21 severe-accident-capable venting system comes mainly from uncertainty both in the CDF 22 and in the consequences resulting from radiological releases.
23 24 Cost-Benefit Analysis Results 25 26 The reductions in 50-mile population dose risk and 50-mile offsite cost risk (relative to Mod 0, 27 the current situation) associated with implementation of the severe-accident-capable venting 28 system plant modifications (Mods 1 through 8) were respectively used to calculate the values of 29 the public health and offsite property attributes for Options 2 and 3 in a cost-benefit analysis.
30 For the purposes of this analysis, Option 2 used the results for Mod 2 and Option 3 used the 31 results for Mod 6. These results corresponded to the plant design modifications that achieved 32 the largest risk reduction for each alternative.
33 34 Table H-16 summarizes the results of the quantitative cost-benefit analysis of a 35 severe-accident-capable (Option 2) and filtered vent system (Option 3) that used the regulatory 36 analysis guidelines that were in effect at the time. This table includes results for both the 37 base-case analysis that used the best estimate CDF value of 2.0x10-5 per reactor-year and a 38 one-way sensitivity analysis in which a CDF value of 2.0x10-4 per reactor-year was used to 39 evaluate the impact on the results of varying this important uncertain parameter.
40 41
H-89 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-16 Summary of Quantitative Cost-Benefit Analysis Results for Filtered 1
Containment Vent System using a $2,000 per Person-Rem Conversion 2
Factor 3
Attribute Severe-Accident-Capable Venting Systems Engineered Filtered Venting Systems Base Casea CDF=2.0x10-5/ry Sensitivity Casea CDF=2.0x10-4/ry Base Casea CDF=2.0x10-5/ry Sensitivity Casea CDF=2.0x10-4/ry Public Health 150 1,500 290 2,900 Occupational Health 11 110 19 190 Offsite Property 348 3,480 600 6,000 Onsite Property 268 2,680 430 4,300 Industry Implementation (2,000)b (2,000)
(15,000)
(15,000)
Industry Operation n/a n/a (1,100)
(1,100)
NRC Implementation (27)
(27)
(27)
(27)
Net Benefit (1,250) 5,743 (14,778)
(2,737) a Values are in thousand dollars per unit.
4 b Negative values are shown using parentheses (e.g., negative 2,000 is displayed as (2,000)).
5 (Source: SECY-12-0157, Enclosure 1, Table 1) 6 7
At the time of the analysis, the staff was updating the dollar per person-rem conversion factor 8
policy and performed sensitivity analyses to evaluate the impact on results of increasing the 9
dollar per person-rem conversion factor from $2,000 per person-rem to $4,000 per person-rem.
10 Table H-17 summarizes the results of these sensitivity analyses.
11 12 Table H-17 Summary of Adjusted Quantitative Cost-Benefit Analysis Results for 13 Filtered Containment Vent System using a $4,000 per Person-Rem 14 Conversion Factor 15 Attribute Severe-Accident-Capable Venting Systems Engineered Filtered Venting Systems Base Casea CDF=2.0x10-5/ry Sensitivity Casea CDF=2.0x10-4/ry Base Casea CDF=2.0x10-5/ry Sensitivity Casea CDF=2.0x10-4/ry Public Health 300 3,000 580 5,800 Occupational Health 22 220 38 380 Offsite Property 348 3,480 600 6,000 Onsite Property 268 2,680 430 4,300 Industry Implementation (2,000)b (2,000)
(15,000)
(15,000)
Industry Operation n/a n/a (1,100)
(1,100)
NRC Implementation (27)
(27)
(27)
(27)
Net Benefit (1,089) 7,353 (14,479) 353 a Values are in thousand dollars per unit.
16 b Negative values are shown using parentheses (e.g., negative 2,000 is displayed as (2,000)).
17 (Source: SECY-12-0157, Enclosure 1, Table 3) 18 19 Qualitative Factors 20 21 Because the net benefits for both Option 2 and Option 3 were negative for the base case, the 22 quantitative cost-benefit analysis did not appear to justify the imposition of additional 23 requirements on the venting systems for BWR Mark I and Mark II containments under 24 base-case assumptions. However, a one-way sensitivity analysis using a CDF value in the 25 upper range of its uncertainty band resulted in a positive net benefit for Option 2, indicating it 26 may be cost-beneficial. Moreover, a two-way sensitivity analysis within which the higher CDF 27
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-90 value and a $4,000 per person-rem conversion factor was used resulted in a positive net benefit 1
for both Option 2 and Option 3, indicating that both options may be cost-beneficial, with Option 2 2
being the preferred alternative because of its greater net benefit.
3 4
However, in addition to performing these quantitative cost-benefit analyses, the staff considered 5
several qualitative factors in its regulatory analysis. For each qualitative factor, the staff 6
assigned a qualitative rating to each alternative. This qualitative rating used the number of 7
up-arrows to indicate the impact of considering that qualitative factor on the relative desirability 8
of the alternative. Table H-18 shows these qualitative ratings.
9 10 Table H-18 Ratings Assigned to Each Alternative by Qualitative Factor 11 Qualitative Factor Option 1 Option 2 Option 3 Option 4 Defense-in-depth Uncertainties Severe accident management Hydrogen control External events Multiunit events Independence of barriers Emergency planning Consistency between reactor technologies Severe accident policy statement International practices Source: Summarized from SECY-12-0157, Enclosure 1 12 13 Note: The analyst should refer to the Commissions response and direction on qualitative factors in 14 SRM-SECY-12-0157 and Appendix A, Qualitative Factors Assessment Tools, to this NUREG before 15 presenting qualitative factors in this manner.
16 17 Summary and Conclusion 18 19 The staff determined that many of the qualitative factors supported the following:
20 21 Pursuing an improved venting system for BWRs with Mark I and Mark II containments to 22 address specific design concerns (e.g., high conditional containment failure probability 23 given core melt) 24 25 Providing additional support for severe accident management functions by preventing 26 radiological releases, hydrogen, and steam from entering the reactor building or other 27 locations on the site 28 29 Minimizing the contamination of the site environment 30 31 Reducing the reliance on emergency planning for the protection of public health and 32 safety 33 34 Considering both the quantitative cost-benefit analysis results and the qualitative factors, the 35 staff further determined that Options 2 and 3, and most likely Option 4, were cost-justified, 36 based on the substantial increase in overall protection of public health and safety that would be 37 provided by addressing severe accident conditions for BWRs with Mark I and Mark II 38 containments.
39 40
H-91 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Based on its regulatory analysis, the staff concluded that Option 3 (installation of engineered 1
filtered venting systems for Mark I and Mark II containments) was the alternative that would 2
provide the most regulatory certainty and the most timely implementation.
3 4
Commissions Response to the Staffs Analysis and Recommendations 5
6 The Commission approved Option 2 and directed the staff to further evaluate Options 3 and 4.
7 Enclosure H-4 to this appendix summarizes the staffs further evaluation of Options 3 and 4.
8 The Commission also directed the staff to seek detailed Commission guidance on the use of 9
qualitative factors in a future notation vote paper. In response, the staff submitted 10 SECY-14-0087, Qualitative Consideration of Factors in the Development of Regulatory 11 Analyses and Backfit Analyses, dated August 14, 2014, and developed Appendix A to this 12 NUREG.
13 14
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-92 ENCLOSURE H-4:
SUMMARY
OF DETAILED ANALYSES FOR 1
SECY-15-0085, EVALUATION OF THE CONTAINMENT PROTECTION 2
AND RELEASE REDUCTION FOR MARK I AND MARK II BOILING-3 WATER REACTORS RULEMAKING ACTIVITIES 4
5 This enclosure summarizes the detailed analyses supporting the evaluation of containment 6
protection and release reduction strategies for boiling-water reactor (BWR) plants with Mark I 7
and Mark II containments, as documented in SECY-15-0085, Evaluation of the Containment 8
Protection and Release Reduction for Mark I and Mark II Boiling-Water Reactors Rulemaking 9
Activities, dated June 18, 2015, as well as in NUREG-2206, Technical Basis for the 10 Containment Protection and Release Reduction Rulemaking for Boiling-Water Reactors with 11 Mark I and Mark II Containments, issued March 2018. The contents of this enclosure should 12 be considered with the previous detailed analyses supporting SECY-12-0157, Consideration of 13 Additional Requirements for Containment Venting Systems for Boiling Water Reactors with 14 Mark I and Mark II Containments, dated November 26, 2012. Enclosure H-3, Summary of 15 Detailed Analyses for SECY-12-0157, Consideration of Additional Requirements for 16 Containment Venting Systems for Boiling Water Reactors with Mark I and Mark II 17 Containments, to this appendix summarizes the detailed analyses for SECY-12-0157.
18 19 Problem Statement and Regulatory Objectives 20 21 The accident that occurred on March 11, 2011, at the Fukushima Dai-ichi nuclear power plant in 22 Japan underscored the importance of reliable operation of containment vents for BWR plants 23 with Mark I and Mark II containments. As part of its response to the lessons learned from this 24 accident, the staff of the U.S. Nuclear Regulatory Commission (NRC) issued Order EA-12-050, 25 Issuance of Order to Modify Licenses with Regard to Reliable Hardened Containment Vents, 26 dated March 12, 2012. This Order required licensees that operate BWRs with Mark I and 27 Mark II containment designs to install hardened containment vents. These vents would address 28 problems encountered during the Fukushima accident by providing plant operators with 29 improved methods for venting containment during accident conditions and thereby preventing 30 containment overpressurization and subsequent failure. In SECY-11-0137, Prioritization of 31 Recommended Actions to be Taken in Response to Fukushima Lessons Learned, dated 32 October 3, 2011, the staff also identified an issue involving containment vent filtration and 33 included a recommendation for the addition of an engineered filtered vent system to improve 34 reliability and limit the release of radiological materials if the venting systems are used in a 35 severe accident after the occurrence of significant core damage.
36 37 In SECY-12-0157, the staff analyzed whether additional requirements might be warranted to 38 address venting from BWRs with Mark I and Mark II containments after core damage and 39 whether filtering of radiological materials that may be released from the vents would be 40 necessary. The staff evaluated four regulatory options, including (1) the status quowhich 41 served as the regulatory baseline and assumed the staff would continue to implement 42 Order EA-12-050 and install reliable hardened vents to reduce the probability of failure of BWR 43 Mark I and Mark II containments but would take no additional action, (2) upgrade or replace the 44 reliable hardened vents required by Order EA-12-050 with a containment venting system 45 designed and installed to remain functional during severe accident conditions, (3) design and 46 install an engineered filtered containment venting system intended to prevent the release of 47 significant amounts of radioactive material following the dominant severe accident sequences at 48 BWRs with Mark I and Mark II containments, and (4) pursue development of requirements and 49 technical acceptance criteria for performance-based severe accident confinement strategies.
50
H-93 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 The NRC staff provided an evaluation that considered both results from quantitative cost-benefit 1
analyses and qualitative factors related to the four options and recommended that the 2
Commission approve Option 3 to require the installation of an engineered filtering system.
3 While acknowledging that the quantitative analyses indicated the costs of the proposed actions 4
outweighed the benefits, the staff recommended in SECY-12-0157 that the Commission 5
consider both the quantitative and qualitative factors and concluded the proposed additional 6
regulatory actions associated with Option 3 were cost-justified.
7 8
In its staff requirements memorandum (SRM) for SECY-12-0157, dated March 19, 2013, the 9
Commission directed the staff to (1) issue a modification to Order EA-12-050 to require BWR 10 licensees with Mark I and Mark II containments to upgrade or replace the reliable hardened 11 vents required by Order EA-12-050 with a containment venting system designed and installed to 12 remain functional during severe accident conditions, and (2) develop technical bases and 13 pursue rulemaking for filtering strategies with drywell filtration and severe accident management 14 of BWR Mark I and Mark II containments. The Commission further ordered that the technical 15 bases should (1) assume that severe-accident-capable vents had been ordered and, as a 16 consequence of that action, should assume that the benefits of these vents accrue equally to 17 engineered filters and to filtration strategies, (2) explore requirements associated with measures 18 to enhance the capability to maintain confinement integrity and to cool core debris, and 19 (3) evaluate multiple performance criteria, including a required decontamination factor and 20 equipment and procedure availability like those required to implement Title 10 of the Code of 21 Federal Regulations (10 CFR) 50.54 (hh).27 22 23 In response to SRM-SECY-12-0157, the staff issued Order EA-13-109, Issuance of Order To 24 Modify Licenses with Regard to Reliable Hardened Containment Vents Capable of Operation 25 Under Severe Accident Conditions, dated June 6, 2013, which rescinded certain requirements 26 imposed in Order EA-12-050 and required BWR licensees with Mark I and Mark II containments 27 to upgrade or replace their vents with a containment venting system designed and installed to 28 remain functional during severe accident conditions. Order EA-13-109 had two primary 29 requirements that would be implemented sequentially in two phases:
30 31
- 1.
Phase 1: Upgrade the venting capabilities from the containment wetwell to provide 32 reliable, severe-accident-capable hardened vents to assist in preventing core damage 33 and, if necessary, to provide venting capability during severe accident conditions.
34 35
- 2.
Phase 2: Either install a reliable severe-accident-capable drywell venting system or 36 develop and implement a reliable containment venting strategy that makes it unlikely that 37 a licensee would need to vent from the containment drywell during severe accident 38 conditions.
39 40 In response to Order EA-13-109, the severe accident water addition (SAWA) approach required 41 licensees to use water addition in combination with one of two strategies(1) a 42 severe-accident-capable drywell vent designed to lower temperature limits, or (2) severe 43 accident water management (SAWM) to control the water levels in the suppression pool such 44 that it would be unlikely that a licensee would need to vent from the containment drywell during 45 severe accident conditions (Nuclear Energy Institute (NEI), 2014).
46 47 27 The SRM for SECY-12-0157 provided additional directions which are addressed in SECY-15-0085.
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-94 With the issuance of Order EA-13-109, the staff also began developing the regulatory basis for 1
the containment protection and release reduction (CPRR)28 rulemaking for BWRs with Mark I 2
and Mark II containments. The objective of the CPRR regulatory basis was to determine what, 3
if any, additional requirements were warranted on filtering strategies and severe accident 4
management for BWRs with Mark I and Mark II containments, assuming the installation of 5
severe-accident-capable hardened vents per Order EA-13-109.
6 7
Regulatory Alternatives 8
9 The staff interacted with industry and members of the public and identified four major regulatory 10 alternatives comprising numerous subalternatives for choices on filtering strategies and severe 11 accident management for BWRs with Mark I and Mark II containment designs. The four main 12 CPRR regulatory alternatives considered in the regulatory analysis performed in support of 13 SECY-15-0085 were the following:
14 15 Alternative 1: Severe-Accident-Capable Vents (Status Quo). Continue with the 16 implementation of Order EA-13-109 and installation of severe-accident-capable vents, 17 without taking additional regulatory actions related to BWR Mark I and Mark II 18 containments. This alternative represented the status quo and served as the regulatory 19 baseline against which the benefits and costs of other alternatives were measured.
20 21 Alternative 2: Rulemaking to Make Order EA-13-109 Generically Applicable. Pursue 22 rulemaking to make Order EA-13-109 generically applicable to protect BWR Mark I and 23 Mark II containments against overpressurization. The potential benefits associated with 24 this option resulted from making generically applicable the requirements in 25 Order EA-13-109 related to improved reporting, change control, and other aspects of 26 controlling licensing basis information.
27 28 Alternative 3: Rulemaking to Make Order EA-13-109 Generically Applicable and 29 Additional Requirements for SAWA to Address Uncontrolled Releases from Major 30 Containment Failure Modes. Pursue rulemaking to address overall BWR Mark I and 31 Mark II containment protection against multiple failure modes by making 32 Order EA-13-109 generically applicable and requiring external water addition points that 33 would allow water to be added into the reactor pressure vessel (RPV) or drywell to 34 prevent containment failure from both overpressurization and liner melt-through.
35 36 Alternative 4: Rulemaking to Reduce Releases during Controlled Venting (Filtering 37 Strategies, Engineered Filters). Pursue rulemaking to address both containment 38 protection against multiple failure modes and release reduction measures for controlling 39 releases through the containment venting systems. This alternative would make 40 Order EA-13-109 generically applicable and require external water addition into the RPV 41 or drywell. In addition, licensees would be required to reduce the fission products 42 released from containment by (1) implementing strategies to maximize the availability 43 and efficiency of the wetwell in scrubbing or filtering fission products before venting from 44 containment or (2) installing an engineered filter in the containment vent paths (or both).
45 46 28 As the rulemaking progressed, the staff determined that the original rulemaking name (filtering strategies) no longer matched the purpose of the activity. The staff believed it was more logical to have the rulemaking reflect the two issues being analyzedenhanced containment protection and release reduction.
H-95 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 A CPRR strategy is an action taken before or during a severe accident to protect the 1
containments structural integrity or to reduce the amount of radiological material released to the 2
environment. Examples include containment venting following core damage (a containment 3
protection strategy) and the installation of engineered filters on the containment vent lines (a 4
release reduction strategy). Such high-level strategies can be divided into more specific 5
categories according to how they are implemented. From the four main regulatory alternatives 6
defined above, 20 regulatory subalternatives were defined by specific combinations of CPRR 7
strategies. These combinations of CPRR strategies considered many factors, including the 8
following:
9 10 Wetwell and drywell venting priority (before and after core damage) 11 12 Venting actuation (before and after core damage) 13 14 Venting operation mode (before and after core damage) 15 16 Vent reclosure if core damage is imminent 17 18 Postaccident water injection location and operating mode 19 20 Filter size and decontamination factor 21 22 Table 19 summarizes the 20 regulatory subalternatives, how each subalternative maps to the 23 options defined in SECY-12-0157 and the alternatives defined in SECY-15-0085, and the 24 combinations of CPRR strategies used to distinguish among them.
25 26 Safety Goal Evaluation 27 28 A safety goal evaluation for Alternative 3 and Alternative 4 was performed in this regulatory 29 analysis because these two main regulatory alternatives were considered generic safety 30 enhancement backfits subject to the substantial additional protection standard at 31 10 CFR 50.109(a)(3). Each alternative, if implemented, would improve containment 32 performance by reducing (1) the probability of containment failure, given the assumed 33 occurrence of a severe accident scenario, and/or (2) the amount of radiological material 34 released to the environment from a severe accident scenario. However, since none of the 35 alternatives would impact the frequency of core damage accidents (i.e., the change in core 36 damage frequency (CDF) for each alternative relative to the regulatory baseline was zero), the 37 safety goal screening criteria in the regulatory analysis guidelines could not be used to 38 determine whether each alternative could result in a substantial increase in overall protection of 39 public health and safety.
40 41 To perform the safety goal evaluation, the staff analyzed numerous regulatory alternatives to 42 directly compare their potential safety benefits to the quantitative health objectives (QHOs) for 43 average individual early fatality risk and average individual latent cancer fatality risk described in 44 the Commissions Safety Goal Policy Statement (NRC, 1986). Each of the alternatives was 45 compared to Alternative 1 (status quo and regulatory baseline) to determine the relative benefits 46 and costs of the alternative.
47 48 The staff determined there was zero average individual early fatality risk, conditioned on the 49 assumed occurrence of the modeled severe accident scenarios. In part this resulted from the 50
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-96 fact that the modeled accident progression resulted in releases that begin late when compared 1
to the time needed to evacuate members of the public living near the modeled nuclear power 2
plant site.
3 4
Table H-19 Summary of Regulatory Subalternatives and Distinguishing Attributes 5
Index Regulatory Subalternative SECY-12-0157 Option SECY-15-0085 Alternative Before Core Damage After Core Damage Filter Size and DF Venting Priority Venting Actuation Venting Operation Mode Reclose Valve if Core Damage is Imminent Postaccident Water Injection Location Postaccident Water Injection Operating Mode Venting Priority Venting Actuation Venting Operation Mode 1
1 2
NA WWF M
AV Yes NA NA WWF M
OLO NA 2
2A 2
NA WWF M
AV Yes NA NA WWF M
OLO NA 3
3A 2
1,2,3 WWF M
OLO NA 4
3B 2
1,2,3 WWF M
OLO NA 5
4Ai(1) 4 4
WWF M
VC NA 6
4Ai(2) 4 4
WWF M
VC NA 7
4Aii(1) 4 4
WWF M
OLO NA 8
4Aii(2) 4 4
WWF M
OLO NA 9
4Aiii(1) 4 4
WWF M
VC NA 10 4Aiii(2) 4 4
WWF M
VC NA 11 4Bi(1) 3 4
WWF M
OLO S
12 4Bi(2) 3 4
WWF M
OLO S
13 4Bii 3
4 WWF M
OLO S
14 4Biii 3
4 WWF M
OLO S
15 4Biv 3
4 DWF P
OLO S
16 4Ci(1) 3 4
WWF M
OLO L
17 4Ci(2) 3 4
WWF M
OLO L
18 4Cii 3
4 WWF M
OLO L
19 4Ciii 3
4 WWF M
OLO L
20 4Civ 3
4 DWF P
OLO L
Venting Priority DWF: drywell first strategy WWF: wetwell first strategy Venting Actuation M: manual P: passive (rupture disc)
Venting Operation Mode AV: anticipatory venting OLO: open at 15 psig and leave open VC: venting cycling at primary containment pressure limit with 10 psi band Postaccident Water Injection Location DW: drywell via external connection RPV: reactor pressure vessel via external connection Postaccident Water Injection Operating Mode SAWA severe accident water addition SAWM severe accident water management Filter Size and Decontamination Factor (DF)
L: large with DF of 1000 S: small with DF of 10 (Source: NUREG-2206, Table 2-2) 6 7
The staff then performed a screening analysis for the average individual latent cancer fatality 8
risk QHO by evaluating all United States (U.S.) BWRs with Mark I containments (a total of 9
22 units at 15 sites) and Mark II containments (a total of eight units at five sites). For this 10 screening analysis, the staff developed a conservative high estimate of frequency-weighted 11
H-97 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 average individual latent cancer fatality risk within 10 miles using the following parameter 1
values:
2 3
An extended loss of alternating current power (ELAP)29 frequency value of 7x10-5 per 4
reactor-yearwhich represented the highest value among all BWRs with Mark I and 5
Mark II containments 6
7 A success probability for flexible coping strategies (FLEX) equipment of 0.6 per 8
demandwhich assumed implementation of FLEX will successfully mitigate an accident 9
involving an ELAP 6 out of 10 times 10 11 A conditional average individual latent cancer fatality risk of 2x10-3 per eventwhich 12 represented the highest value among all BWRs with Mark I and Mark II containments 13 14 These assumed parameter values resulted in a conservative high estimate of 15 frequency-weighted individual latent cancer fatality risk within 10 miles of approximately 16 7x10-8 per reactor-year, which is greater than an order of magnitude less than the QHO for an 17 average individual latent cancer fatality risk of approximately 2x10-6 per reactor-year. This 18 conservative high estimate did not take credit for any of the accident strategies and capabilities 19 described in the 20 CPRR alternatives and subalternatives. Figure H-19 shows the incremental 20 benefit for each alternative and subalternative, compared to the status quo and Order 21 EA-13-109. If licensees were to choose to implement SAWA/SAWM as part of compliance with 22 EA-13-109, the uncertainty band for Alternative 3 would apply. However, since EA-13-109 did 23 not specifically require SAWA/SAWM, it was not credited in Figure H-18 for Alternative 1 or 24 Alternative 2.
25 26 If an ELAP occurs and results in core damage, an engineered filtered containment venting 27 system would reduce offsite consequences. However, because the average individual latent 28 cancer fatality risk within 10 miles for the status quo alternative (Alternative 1) was already well 29 below the associated QHO, the staff concluded that the design and installation of an engineered 30 filtered containment venting system or a performance-based confinement strategy for BWRs 31 with Mark I and Mark II containments would not meet the threshold for a substantial safety 32 enhancement. Moreover, although this analysis did not include all accident scenarios that a 33 full-scope Level 3 PRA would need to consider, the staff concluded that none of the alternatives 34 could result in a substantial increase in overall protection of public health and safety. Therefore, 35 the staff recommended that rulemaking not be pursued for SECY-12-0157 Option 3 or Option 4.
36 Furthermore, the staff concluded that a detailed regulatory analysis of the various alternatives 37 was not warranted and would provide little additional insight into the regulatory decision 38 because the margin to the QHOs did not support a substantial safety benefit.
39 40 29 An ELAP is defined as a station blackout (SBO) that lasts longer than the SBO coping duration specified in 10 CFR 50.63, Loss of all alternating current power.
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-98 1
Figure H-18 Uncertainty in Average Individual Latent Cancer Fatality Risk (0-10 miles) 2 (Source: SECY-15-0085, Enclosure, Figure 3-3) 3 4
Technical Evaluation 5
6 Accident Scenario Selection 7
8 The staff considered the following factors during the development of the technical approach for 9
the accident sequence analysis performed for SECY-15-0085:
10 11 The risk evaluation should provide risk metrics for each of the 20 CPRR regulatory 12 analysis subalternatives, according to the schedule established by the Commission and 13 the resources allotted by NRC management.
14 15 Consistent with the NRCs regulatory analysis guidelines, the risk evaluation should 16 provide fleet-average risk estimates. Therefore, the technical approach should consider 17 the impacts of plant-to-plant variability.
18
H-99 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
Consistent with Recommendation 5.1 in the Fukushima Near-Term Task Force (NTTF) 2 report, the accident sequence analysis should focus on accidents initiated by ELAP 3
events.
4 5
The generic estimates of release sequence frequencies and conditional consequences 6
in NUREG/BR-0184, Regulatory Analysis Technical Evaluation Handbook, issued 7
January 1997, were developed from previous probabilistic risk assessments (PRAs) that 8
did not consider CPRR strategies and therefore cannot be used to provide an adequate 9
technical basis for the CPRR risk evaluation.
10 11 Core damage event trees (CDETs) should be developed to (1) model the impact of 12 equipment failures and operator actions occurring before core damage that affect severe 13 accident progression and the probability that CPRR strategies are successfully 14 implemented, (2) match the initial and boundary conditions used in the thermal-hydraulic 15 simulation of severe accidents in MELCOR, and (3) probabilistically consider mitigating 16 strategies for beyond-design-basis external events required by Order EA-12-049, 17 Issuance of Order to Modify Licenses with Regard to Requirements for Mitigation 18 Strategies for Beyond-Design-Basis External Events, dated March 12, 2012.
19 20 The CPRR strategies addressed in the set of 20 regulatory analysis subalternatives are 21 specified at a conceptual level. Therefore, it is acceptable to develop high-level generic 22 accident progression event trees (APETs) to model the CPRR strategies because no 23 information is available about their specific design details.
24 25 Analysts used a modular approach to develop the CDETs and APETs, as shown in Figure H-19.
26 This modeling approach streamlined the development of risk estimates.
27 28
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-100 1
Figure H-19 Modular Approach to Event Tree Development 2
(Source: NUREG-2206, Figure 2-1) 3 4
H-101 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 MELCOR Severe Accident Progression and Source Term Analyses 1
2 The MELCOR analyses addressed two main categories: (1) reactor systems and containment 3
thermal-hydraulics under severe accident conditions and (2) assessment of source termsthe 4
timing, magnitude, and other characteristics of fission product releases to the environment. The 5
first category provided insight into the state of containment vulnerability under severe accident 6
conditions and information needed to assess containment integrity. The second category 7
provided information needed to assess the offsite radiological consequences associated with 8
releases of radioactive materials to the environment.
9 10 The NRC based the development of the MELCOR calculation matrices (see Table 3-2 and 11 Table 3-3, NRC, 2018b) on the CPRR alternatives defined by the accident sequence analysis.
12 The MELCOR analyses investigated detailed accident progression, containment response, and 13 source terms for representative Mark I and Mark II containment designs following an ELAP.
14 The selection of accident scenarios considered for MELCOR analyses was informed by the 15 State-of-the-Art Reactor Consequence Analyses (SOARCA) Project (see Enclosure H-2, 16 Summary of the State-of-the-Art Reactor Consequence Analyses (SOARCA) Project, to this 17 appendix), the Fukushima Dai-ichi nuclear power plant accident reconstruction study (Sandia 18 National Laboratories, 2012), and the detailed analyses in SECY-12-0157. The representative 19 Mark I containment selected was similar in configuration to Peach Bottom Atomic Power Station 20 (Peach Bottom), Unit 2, and the representative Mark II containment was similar in configuration 21 to LaSalle County Station (LaSalle). The Mark I MELCOR calculation matrix included sensitivity 22 cases to evaluate the impact on results of using plausible alternative assumptions about 23 multiple factors, including (1) mode of venting, (2) status of RPV depressurization, (3) mode of 24 FLEX water injection, and (4) water management. The Mark II MELCOR calculation matrix 25 included a subset of the Mark I matrix, based on the insights from the Mark I MELCOR 26 calculations, and included sensitivity cases to evaluate the impact of the pedestal and lower 27 cavity designs among the fleet by modifying the base model.
28 29 The scope and technical approach for the MELCOR analyses performed in support of 30 SECY-15-0085 were similar to those of SECY-12-0157. In both cases, the technical approach 31 considered best estimate modeling of accident progression and incorporated both preventive 32 and mitigative accident management measures, including (1) venting, (2) water addition, water 33 management, or both, and (3) installation of engineered filters. However, an important 34 distinction between the technical approaches is that, in SECY-12-0157, water addition was 35 considered in a generic way because the industrys post-Fukushima Dai-ichi severe accident 36 management strategies were still evolving and the concepts of SAWA and SAWM had not yet 37 emerged. Moreover, the industry was formulating its FLEX strategy for severe accident 38 mitigation applications at the time. By contrast, these various concepts and severe accident 39 management measures were more mature by the time detailed analyses were performed for 40 SECY-15-0085 and were, therefore, considered in developing the technical approach for these 41 analyses.
42 43 MACCS Consequence Analyses 44 45 Like the MELCOR analyses, the scope and technical approach for the MACCS analyses 46 performed in support of SECY-15-0085 were similar to those of SECY-12-0157. The NRC used 47 MACCS to calculate offsite radiological consequences with site-specific population, economic, 48 land use, weather, and evacuation data for reference Mark I and Mark II sites. The agency 49 selected Peach Bottom and the Limerick Generating Station (Limerick) as the site-specific 50 reference models for the offsite consequence analyses to enable greater modeling fidelity for 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-102 sites with relatively high population densities (Peach Bottom had the second highest population 1
within a 50-mile radius among the 15 Mark I sites and Limerick had the highest population within 2
a 50-mile radius among the five Mark II sites).
3 4
The staff performed offsite consequence analyses for the source terms generated by MELCOR 5
corresponding to different CPRR accident management strategies following an ELAP event. It 6
assessed the relative public health risk reduction associated with various containment protection 7
and release reduction measures with respect to various offsite radiological consequence 8
measures, including (1) average individual early fatality risk and average individual latent cancer 9
fatality risk, (2) population dose, (3) land contamination, (4) economic costs, and (5) displaced 10 population. Land contamination areas and displaced populations represented additional 11 consequence metrics that the staff reported for consideration by decisionmakers, although they 12 are not required as inputs to safety goal evaluations or regulatory analyses. The calculated 13 offsite radiological consequences were weighted by accident frequency to assess relative public 14 health risk reduction.
15 16 Tables H-20 and H-21 show the summary MACCS results respectively for the 18 Mark I and the 17 9 Mark II source term bins. As shown on the tables, the staff reported some consequence 18 metrics out to a 100-mile radius from the plant.
19 20
H-103 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-20 MACCS Results for 18 Mark I Source Term Bins 1
2 Note: To quantify the time signature of a source term release, an hourly plume segment is 3
considered significant if it contributes at least 0.5 percent of that source terms total cumulative 4
cesium release to the environment. Cesium, rather than iodine, was selected here because all of the 5
resulting offsite consequences are driven by long-term phase exposures.
6 (Source: NUREG-2206, Table 4-22) 7 8
Individiual Early Fatality Risk 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
28DF1000 0.0006%
0.006%
14.9 7
0 4.65E-07 4.57E-08 2.06E-08 1,620 2,380 2
48DF100 0.002%
0.02%
11.4 8
0 1.90E-06 1.90E-07 8.69E-08 5,480 8,260 3
10DF100 0.01%
0.08%
16.3 6
0 6.25E-06 7.16E-07 3.21E-07 16,500 27,300 4
7DF1000 0.02%
0.26%
14.9 20 0
1.72E-05 2.35E-06 1.01E-06 48,400 77,600 5
11DF10 0.06%
0.78%
14.4 4
0 2.03E-05 3.36E-06 1.62E-06 71,200 127,000 6
48 0.23%
1.69%
11.4 8
0 7.95E-05 1.61E-05 7.79E-06 253,000 450,000 7
15 0.60%
5.85%
14.9 7
0 1.21E-04 3.28E-05 1.64E-05 524,000 932,000 8
46 0.98%
11.01%
14.8 17 0
1.53E-04 4.59E-05 2.34E-05 790,000 1,410,000 9
5DF10 1.05%
2.89%
24.2 34 0
3.55E-04 7.50E-05 3.35E-05 1,040,000 1,720,000 10 5
1.39%
6.46%
24.2 41 0
4.06E-04 9.78E-05 4.51E-05 1,360,000 2,290,000 11 8
1.49%
19.25%
14.9 5
0 1.35E-04 6.41E-05 3.43E-05 1,110,000 2,030,000 12 1
1.93%
22.68%
14.9 22 0
2.91E-04 1.01E-04 5.23E-05 1,720,000 3,090,000 13 41DF1000 3.40%
7.65%
9.8 17 0
5.22E-04 1.49E-04 7.89E-05 1,900,000 3,610,000 14 22dw 2.82%
18.64%
14.9 27 0
4.27E-04 1.28E-04 6.57E-05 1,830,000 3,320,000 15 53 2.79%
29.05%
17.4 13 0
2.59E-04 1.19E-04 6.96E-05 1,740,000 3,520,000 16 41 4.54%
14.10%
9.8 16 0
5.57E-04 1.75E-04 9.82E-05 2,300,000 4,520,000 17 3DF10 8.85%
24.65%
9.8 63 0
7.10E-04 2.95E-04 1.68E-04 3,830,000 7,720,000 18 52 15.90%
34.32%
17.4 11 0
5.39E-04 2.23E-04 1.50E-04 3,080,000 6,870,000 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
28DF1000 0.0006%
0.006%
14.9 7
78,900,000 78,900,000 0
0 2
48DF100 0.002%
0.02%
11.4 8
79,700,000 79,700,000 1
1 0
0 3
10DF100 0.01%
0.08%
16.3 6
98,100,000 98,700,000 10 11 1
1 4
7DF1000 0.02%
0.26%
14.9 20 141,000,000 141,000,000 23 23 7
7 5
11DF10 0.06%
0.78%
14.4 4
220,000,000 240,000,000 41 65 118 118 6
48 0.23%
1.69%
11.4 8
1,150,000,000 1,390,000,000 116 175 3,440 3,440 7
15 0.60%
5.85%
14.9 7
2,740,000,000 3,690,000,000 190 361 15,000 16,600 8
46 0.98%
11.01%
14.8 17 3,760,000,000 5,220,000,000 242 506 20,700 27,400 9
5DF10 1.05%
2.89%
24.2 34 7,290,000,000 8,600,000,000 351 429 35,200 35,200 10 5
1.39%
6.46%
24.2 41 9,900,000,000 12,000,000,000 479 715 51,400 51,500 11 8
1.49%
19.25%
14.9 5
5,960,000,000 9,720,000,000 286 673 40,500 55,800 12 1
1.93%
22.68%
14.9 22 13,000,000,000 17,400,000,000 549 1,040 64,500 79,700 13 41DF1000 3.40%
7.65%
9.8 17 19,400,000,000 24,700,000,000 783 1,170 168,000 190,000 14 22dw 2.82%
18.64%
14.9 27 12,900,000,000 18,300,000,000 544 1,010 93,700 114,000 15 53 2.79%
29.05%
17.4 13 15,700,000,000 26,500,000,000 573 1,290 111,000 142,000 16 41 4.54%
14.10%
9.8 16 25,500,000,000 35,400,000,000 904 1,500 235,000 281,000 17 3DF10 8.85%
24.65%
9.8 63 47,000,000,000 68,100,000,000 1,360 2,470 417,000 504,000 18 52 15.90%
34.32%
17.4 11 46,500,000,000 87,700,000,000 987 2,170 467,000 873,000 Rep Case I (%)
Start Time (hrs)
Land (sq mi) Exceeding Long-Term Habitability Criterion Population Subject to Long-Term Protective Actions Individual Latent Cancer Fatality Risk Population Dose (person-rem)
Offsite Cost ($ 2013)
- Hrs with Significant Cs Release*
Bin Rep Case Rep Case Cs (%)
Rep Case I (%)
Start Time (hrs)
- Hrs with Significant Cs Release*
Bin Rep Case Rep Case Cs (%)
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-104 Table H-21 MACCS Results for 9 Mark II Source Term Bins 1
2 Note: To quantify the time signature of a source term release, an hourly plume segment is 3
considered significant if it contributes at least 0.5 percent of that source terms total cumulative 4
cesium release to the environment. Cesium, rather than iodine, was selected here because all the 5
resulting offsite consequences are driven by long-term phase exposures.
6 (Source: NUREG-2206, Table 4-23) 7 8
The offsite radiological consequence estimates for SECY-15-0085 were like those of 9
SECY-12-0157. However, an important distinction between the detailed analyses for 10 SECY-15-0085 and SECY-12-0157 is the use of different performance criteria to evaluate the 11 offsite radiological consequence results. Although not explicitly stated, the detailed analyses for 12 SECY-12-0157 implicitly assumed decontamination factor (DF) as a performance criterion.
13 Specifically, consistent with international nuclear safety practices and guidelines, a DF value of 14 1,000 was established as a performance target. This is equivalent to one-tenth of one percent 15 of cesium release to the environment and serves as an indirect measure of latent cancer fatality 16 risk and land contamination risk. By contrast, SECY-15-0085 defined six performance criteria 17 related to the attributes of (1) conditional containment failure probability, (2) DF, (3) equipment 18 and procedure availability, (4) total population dose, (5) margin to the QHOs, and (6) long-term 19 relocation. Ultimately, the detailed analyses for SECY-15-0085 used the margin to the safety 20 goal QHOs for average individual early fatality risk within 1 mile and average individual latent 21 cancer fatality risk within 10 miles as the performance criteria to determine whether each 22 alternative could result in a substantial increase in the overall protection of public health and 23 safety.
24 25 Risk Evaluation 26 27 The staff expanded the scope and level of detail of the PRA model developed for 28 SECY-12-0157 for the detailed analyses for SECY-15-0085. The PRA model used in 29 SECY-12-0157 did not delineate core damage accident sequences. Instead, it relied on a 30 generic estimate of CDF developed from previous NRC staff and licensee PRAs. To provide a 31 Individual Early Fatality Risk 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
11DF1000 0.00004%
0.0005%
20.3 20 0
9.72E-08 1.03E-08 3.45E-09 282 345 2
5DF1000 0.0006%
0.005%
32.2 20 0
1.15E-06 1.81E-07 6.35E-08 4,340 5,440 3
42DF100 0.0043%
0.037%
14.3 13 0
6.58E-06 8.67E-07 3.02E-07 20,700 26,700 4
11 0.042%
0.45%
20.3 20 0
7.90E-05 9.68E-06 3.27E-06 202,000 261,000 5
51DF10 0.23%
2.01%
16.6 9
0 1.35E-04 3.39E-05 1.21E-05 689,000 888,000 6
5 0.55%
4.94%
32.2 20 0
2.29E-04 1.05E-04 4.01E-05 2,160,000 2,900,000 7
3 1.09%
10.26%
14.3 20 0
3.08E-04 1.88E-04 7.43E-05 4,140,000 5,580,000 8
1 2.46%
19.81%
22.8 25 0
4.70E-04 3.17E-04 1.25E-04 6,110,000 8,260,000 9
52 3.57%
28.67%
16.6 10 0
4.03E-04 2.46E-04 1.01E-04 5,430,000 7,440,000 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
11DF1000 0.00004%
0.0005%
20.3 20 381,000,000 381,000,000 2
5DF1000 0.0006%
0.005%
32.2 20 381,000,000 381,000,000 0
0 3
42DF100 0.0043%
0.037%
14.3 13 393,000,000 393,000,000 2
2 0
0 4
11 0.042%
0.45%
20.3 20 844,000,000 846,000,000 44 47 1,030 1,030 5
51DF10 0.23%
2.01%
16.6 9
4,250,000,000 4,380,000,000 130 221 15,400 15,400 6
5 0.55%
4.94%
32.2 20 24,000,000,000 28,000,000,000 303 551 62,400 62,400 7
3 1.09%
10.26%
14.3 20 80,800,000,000 105,400,000,000 698 1,200 619,000 649,000 8
1 2.46%
19.81%
22.8 25 85,500,000,000 109,300,000,000 854 1,680 721,000 741,000 9
52 3.57%
28.67%
16.6 10 53,600,000,000 63,800,000,000 618 1,400 414,000 449,000 Offsite Cost ($ 2013)
Population Dose (person-rem)
Land (sq mi) Exceeding Long-Term Habitability Criterion Bin Rep Case Rep Case Cs (%)
Rep Case I (%)
Start Time (hrs)
Individual Latent Cancer Fatality Risk
- Hrs with Significant Cs Release*
Population Subject to Long-Term Protective Actions Bin Rep Case Rep Case Cs (%)
Rep Case I (%)
Start Time (hrs)
- Hrs with Significant Cs Release*
H-105 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 quantitative basis for regulatory decisionmaking, the PRA performed in support of 1
SECY-15-0085 included the following features:
2 3
Models to estimate the frequency of ELAP events resulting from internal events and 4
earthquakes, based on industry-developed re-evaluations of seismic hazard estimates.
5 6
CDETs that delineate accident sequences from the occurrence of an ELAP event to the 7
onset of core damage. The CDETs reflect SBO mitigation strategies using installed 8
plant and portable equipment.
9 10 APETs that delineate accident sequences from the onset of core damage to the release 11 of radioactive materials to the environment. The APETs reflect CPRR strategies such as 12 post-core-damage containment venting and water addition.
13 14 Models that include random and seismically-induced equipment failures.
15 16 In-control room and local manual operator actions consistent with emergency operating 17 procedures and severe accident management guidelines.
18 19 Models that identify important contributors to CDF.
20 21 Sensitivity analyses to gain insight into how plausible alternative assumptions about 22 human error probability estimates impact the quantitative results.
23 24 These revisions to the PRA model resulted in a lower value for conditional CDF, conditioned on 25 the assumed occurrence of an ELAP, than was reported in SECY-12-0157. The model 26 calculated the CDF caused by ELAPs to be 8.9x10-6 per reactor-year, which was about two 27 times lower than the value of 1.6x10-5 that SECY-12-0157 estimated. The CDF calculation 28 averaged together the CDF for each BWR plant that was included in the scope of the accident 29 sequence analysis.
30 31 Table H-22 summarizes the risk estimates of each regulatory analysis subalternative. These 32 risk estimates represent the point estimate, baseline-case results.
33 34
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-106 Table H-22 Risk Estimates by Regulatory Analysis Subalternative 1
2 (Source: NUREG-2206, Table 5-1) 3 Index Regulatory Analysis Sub-Alternative Fraction of Core-Damage Frequency Individual Early Fatality Risk (/y)
Individual Latent Cancer Fatality Risk (/y)
Population Dose (person-rem/y)
Offsite Cost
($ 2013/y)
Land Exceeding Long-Term Habitability Criterion (square miles/y)
Population Subject to Long-Term Protective Actions (persons/y)
Vented Uncontrolled Release 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 1
1 0%
100%
0.0E+00 3.0E-09 8.6E-10 4.2E-10 1.3E+01 2.3E+01 9.9E+04 1.3E+05 4.4E-03 7.6E-03 5.1E-01 5.8E-01 2
2A 0%
100%
0.0E+00 3.0E-09 8.6E-10 4.2E-10 1.3E+01 2.3E+01 9.9E+04 1.3E+05 4.4E-03 7.6E-03 5.1E-01 5.8E-01 3
3A 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 4
3B 42%
58%
0.0E+00 2.1E-09 6.7E-10 3.4E-10 1.1E+01 1.9E+01 7.4E+04 1.0E+05 3.4E-03 6.4E-03 4.1E-01 4.9E-01 5
4Ai(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 6
4Ai(2) 42%
58%
0.0E+00 2.1E-09 6.1E-10 3.1E-10 9.5E+00 1.7E+01 6.8E+04 9.0E+04 3.2E-03 5.8E-03 3.6E-01 4.1E-01 7
4Aii(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 8
4Aii(2) 42%
58%
0.0E+00 2.4E-09 7.7E-10 3.9E-10 1.2E+01 2.2E+01 8.9E+04 1.2E+05 3.9E-03 7.3E-03 4.8E-01 5.8E-01 9
4Aiii(1) 58%
42%
0.0E+00 1.8E-09 5.5E-10 2.7E-10 8.6E+00 1.5E+01 6.5E+04 8.5E+04 2.9E-03 5.0E-03 3.3E-01 3.9E-01 10 4Aiii(2) 42%
58%
0.0E+00 2.0E-09 5.6E-10 2.7E-10 8.7E+00 1.5E+01 6.2E+04 7.9E+04 3.0E-03 5.1E-03 3.1E-01 3.4E-01 11 4Bi(1) 58%
42%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.5E+00 7.8E+00 2.9E+04 3.7E+04 1.6E-03 2.5E-03 1.5E-01 1.6E-01 12 4Bi(2) 42%
58%
0.0E+00 1.4E-09 3.3E-10 1.5E-10 4.8E+00 8.2E+00 3.1E+04 3.8E+04 1.8E-03 2.7E-03 1.6E-01 1.6E-01 13 4Bii 42%
58%
0.0E+00 1.4E-09 3.2E-10 1.5E-10 4.6E+00 7.9E+00 3.0E+04 3.7E+04 1.7E-03 2.6E-03 1.5E-01 1.5E-01 14 4Biii 42%
58%
0.0E+00 1.4E-09 3.2E-10 1.5E-10 4.7E+00 8.1E+00 3.1E+04 3.7E+04 1.7E-03 2.6E-03 1.5E-01 1.6E-01 15 4Biv 40%
60%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.6E+00 7.8E+00 3.0E+04 3.6E+04 1.7E-03 2.6E-03 1.5E-01 1.5E-01 16 4Ci(1) 58%
42%
0.0E+00 1.3E-09 3.1E-10 1.5E-10 4.5E+00 7.8E+00 2.9E+04 3.7E+04 1.6E-03 2.5E-03 1.5E-01 1.6E-01 17 4Ci(2) 42%
58%
0.0E+00 1.3E-09 3.1E-10 1.4E-10 4.5E+00 7.6E+00 3.0E+04 3.7E+04 1.6E-03 2.4E-03 1.5E-01 1.6E-01 18 4Cii 42%
58%
0.0E+00 1.3E-09 3.0E-10 1.4E-10 4.4E+00 7.4E+00 2.9E+04 3.6E+04 1.5E-03 2.3E-03 1.5E-01 1.5E-01 19 4Ciii 42%
58%
0.0E+00 1.3E-09 3.1E-10 1.4E-10 4.4E+00 7.6E+00 3.0E+04 3.7E+04 1.6E-03 2.4E-03 1.5E-01 1.6E-01 20 4Civ 40%
60%
0.0E+00 1.3E-09 3.0E-10 1.4E-10 4.3E+00 7.4E+00 2.9E+04 3.6E+04 1.5E-03 2.3E-03 1.5E-01 1.5E-01
H-107 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 1
In addition to these point estimate baseline-case results, the staff conducted uncertainty and 2
sensitivity analyses. The staff performed a parametric Monte Carlo uncertainty analysis to gain 3
additional perspective into the uncertainty of the point estimate risk evaluation results. The 4
uncertainty analysis considered seismic hazard curves, seismic fragility curves, random 5
equipment failures, operator actions, and consequences. Table H-23 summarizes information 6
used to perform the parametric uncertainty analysis. Figure H-19 shows the results of the 7
uncertainty analysis.
8 9
Table H-23 Uncertainty Analysis Inputs 10 Events Distribution Remarks Frequency of ELAPs due to internal events Lognormal Mean = point estimate Error factor =15 An error factor of 15 maximizes the ratio of the 95th percentile to the mean value. This approach does not explicitly consider the uncertainty in the offsite power recovery curves or the uncertainty in the EPS reliability parameters (failure rate and failure-on-demand probability).
Seismic hazard curves Lognormal Normal parameters were developed for each point on the seismic hazard curve using the fractile information provided by licensees in their responses to the 10 CFR 50.54(f) information request concerning NTTF Recommendation 2.1.
Seismic fragilities Double lognormal, using the developed values of C50, R, and U Traditional approach to modeling uncertainty in seismic fragility.
Hardware-related failures Lognormal Mean = point estimate Error factor = 15 An error factor of 15 maximizes the ratio of the 95th percentile to the mean value.
Human failure events Constrained non-informative prior A constrained non-informative prior distribution is a beta distribution with mean = point estimate and = 0.5.
Conditional consequences Lognormal Mean = point estimate Error factor = 10 Informed by preliminary results of the SOARCA uncertainty analysis project.a a NUREG/CR-7155 (draft), State-of-the-Art Reactor Consequence Analyses Project, Uncertainty Analysis of the 11 Unmitigated Long-Term Station Blackout of the Peach Bottom Atomic Power Station.
12 (Source: NUREG-2206, Table 5-2) 13 14 Staff also performed MACCS sensitivity calculations to analyze the influence of site to site 15 variation. The following sensitivities were conducted:
16 17 Population (low, medium, high) 18 19 Evacuation delay (1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />) 20 21 Nonevacuating cohort size (5 percent of emergency planning zone population) 22 23 Intermediate phase duration (0, 3 months, and 1 year) 24 25 Long-term habitability criterion (500 mrem per year and 2 rem per year), which can vary 26 among states in the U.S.
27 28
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-108 A final sensitivity calculation examined evacuation delays on the risk to determine the influence 1
of the plume arrival time on the evacuating population (base case, 3 hour3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> delay, 6 hour6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> delay, 2
no evacuation).
3 4
The results of these sensitivity analyses appear in a series of tables in Chapter 4 of 5
NUREG-2206, which report the ratio of the consequences for the sensitivity cases compared to 6
the baseline cases. Table H-24 below shows an example of these sensitivity results tables, 7
analyzing the effect of different site files (different populations) on the baseline-case results.
8 The results show that individual latent cancer fatality risk is relatively insensitive to site file data 9
(variations are within 60 percent). Population dose is directly related to population size, so the 10 sensitivity cases show a strong increase in population dose for larger population site files. For 11 example, for the Mark II high source term, the high site file case has a population dose about 12 11 times higher than the low site file case. For a given source term, the total offsite cost also 13 increases with higher population site files.
14 15 Table H-24 Results for Baseline Cases with Different Site Files 16 17
- Indicates that both the numerator and denominator in the ratio are zero 18 (Source: NUREG-2206, Table 4-36) 19 20 Cost-Benefit Analysis Results 21 22 Although the potential benefits from possible measures to limit releases through the 23 containment venting systems during severe accidents were well below the NRCs threshold for 24 developing regulatory requirements, the staff reported updated industry cost estimates for 25 implementing the CPRR alternatives in SECY-15-0085. However, these updated cost estimates 26 did not change the staffs conclusion from SECY-12-0157 that none of the proposed regulatory 27 alternatives would satisfy the substantial additional protection standard at 10 CFR 50.109 (a)(3).
28 29 Summary and Conclusion 30 31 The staff developed a risk evaluation and evaluated alternative courses of action related to 32 filtering strategies and severe accident management of BWRs with Mark I and Mark II 33 containments relative to the safety goal QHOs. The staff determined that the possible plant 34 modifications (e.g., engineered filters) to enhance containment protection and release reduction 35 capability beyond those imposed by Order EA-13-109 could result in reductions in offsite 36 consequences. However, these reductions would not meet the quantitative threshold for a 37 38 Individual Early Fatality Risk 0-1.3 mi and beyond 0-10 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi 0-50 mi 0-100 mi Med (VT Yankee) / Low (Hatch) 1.52 0.98 0.90 0.92 1.19 2.79 2.75 0.39 0.43 6.20 6.20 High (Peach Bottom) / Low (Hatch) 0.94 0.74 0.96 2.82 2.07 4.65 4.57 1.53 1.45 2.07 2.07 Med (VT Yankee) / Low (Hatch) 1.25 0.98 0.97 1.88 2.37 3.08 3.60 0.67 0.72 2.91 2.92 High (Peach Bottom) / Low (Hatch) 1.02 0.83 1.02 5.83 4.00 8.84 8.22 1.28 1.08 7.15 7.15 Med (VT Yankee) / Low (Hatch) 1.23 1.05 1.08 2.26 3.33 3.58 4.95 0.82 0.82 3.11 4.16 High (Peach Bottom) / Low (Hatch) 1.00 0.89 1.00 6.78 5.04 11.11 9.33 1.11 0.98 9.96 9.59 Med (Susquehanna) / Low (Columbia) 1.20 0.93 0.49 0.70 1.00 4.90 4.90 3.93 3.93 High (Limerick) / Low (Columbia) 1.63 1.10 0.69 2.33 2.25 20.48 20.48 12.79 12.79 Med (Susquehanna) / Low (Columbia) 0.94 0.86 0.49 1.38 1.96 2.32 2.33 0.40 0.56 6.35 6.35 High (Limerick) / Low (Columbia) 1.17 1.03 0.65 6.53 4.82 11.71 10.63 0.52 0.61 28.96 28.96 Med (Susquehanna) / Low (Columbia) 0.89 0.85 0.59 2.06 3.71 3.07 6.60 0.61 0.76 3.00 3.42 High (Limerick) / Low (Columbia) 1.07 1.04 0.68 10.82 9.32 18.49 17.97 0.69 0.75 17.87 17.09 Land (sq mi)
Exceeding Long-Term Habitability Criterion Mark I - Peach Bottom Mark I - Low (Bin 3)
Mark I - Med (Bin 10)
Mark I - High (Bin 17)
Mark II - Limerick Mark II - Low (Bin 2)
Mark II - Med (Bin 5)
Mark II - High (Bin 8)
Individual early fatality risk is zero for all baseline and sensitivity cases.
Individual Latent Cancer Fatality Risk Population Dose (person-rem)
Offsite Cost
($ 2013)
Population Subject to Long-Term Protective Actions Base Model Source Term Site File
H-109 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 substantial safety enhancement because the average individual early fatality risk and average 1
individual latent cancer fatality risk are well below the QHOs without additional plant 2
modifications.
3 4
Based on the results of the detailed analyses for SECY-15-0085, the staff planned to proceed 5
with Alternative 3: Rulemaking to Make Order EA-13-109 Generically Applicable and Additional 6
Requirements for SAWA to Address Uncontrolled Releases from Major Containment Failure 7
Modes. The rulemaking would include the planned implementation of Phase 2 of the order to 8
require licensees of BWRs with Mark I and Mark II containments to have the capability to add 9
water from external sources and control the flow to cool core debris during severe accident 10 conditions. The staff concluded that the ability to provide post-core-damage water addition 11 results in worthwhile additional protection for public health and safety by: (1) protecting the 12 integrity of the containment; (2) reducing the release of radioactive materials in some severe 13 accident scenarios; and (3) contributing to the balance between accident prevention and 14 mitigation.
15 16 The staffs plan to proceed with Alternative 3 for the CPRR rulemaking differed from the staffs 17 recommendation in SECY-12-0157 to require the installation of an engineered filtering system.
18 More detailed analyses resulted in the following findings:
19 20 The CDF from an ELAP event was lower than estimated in SECY-12-0157.
21 22 The identification of important contributors to CDF and sensitivity analyses enhanced the 23 staffs confidence in its quantitative analyses and therefore reduced the importance of 24 remaining uncertainties.
25 26 External water addition was shown to avert containment failure and achieve benefits in 27 terms of averted health risks in a wider range of scenarios than an engineering filtering 28 system (e.g., in scenarios where the release pathway bypasses the filtering system).
29 30 Therefore, the staff recommended proceeding with a proposed rulemaking to address the 31 containment protection improvements related to venting and water addition without including 32 requirements for installing engineered filtering systems.
33 34 Commissions Response to the Staffs Analysis and Recommendations 35 36 The Commission disapproved the staff's plan to proceed with Alternative 3. Instead, the 37 Commission approved Alternative 1, which was to continue with the implementation of Order 38 EA-13-109 and installation of severe-accident-capable vents (including SAWA/SAWM as part of 39 Phase 2 compliance with the Order), without taking additional regulatory actions related to BWR 40 Mark I and Mark II containments. The reasoning for this decision was articulated in the 41 Chairmans comments in the Commission Voting Record. The Chairman noted that there is no 42 practical difference in safety outcomes between Alternatives 1 and 3Order EA-13-109, which 43 was imposed on all BWRs with Mark I and II containments in 2013, already serves as a legally 44 binding mechanism that effectively achieves the results the staff is seeking[Furthermore]
45 there are no expectations that a BWR with a Mark I or II containment will ever be licensed to 46 operate in the United States again, which obviated the need to expend agency resources to 47 make Order EA-13-109 generically applicable through rulemaking (NRC, 2015b).
48 49
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-110 The Commission further directed the staff to leverage the draft regulatory basis to the extent 1
applicable to support resolution of the post-Fukushima Dai-ichi Tier 3 item related to 2
containments of other designs (NTTF Recommendation 5.2). The NTTF Recommendation 5.2 3
was subsequently closed by SECY-16-0041, Closure of Fukushima Tier 3 Recommendations 4
Related to Containment Vents, Hydrogen Control, and Enhanced Instrumentation, dated 5
March 31, 2016, with no further regulatory action.
6 7
H-111 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 ENCLOSURE H-5:
SUMMARY
OF DETAILED ANALYSES FOR 1
SECY-13-0112 AND NUREG-2161, CONSEQUENCE STUDY OF A 2
BEYOND-DESIGN-BASIS EARTHQUAKE AFFECTING THE SPENT 3
FUEL POOL FOR A U.S. MARK I BOILING-WATER REACTOR 4
5 This enclosure summarizes the detailed analyses supporting the evaluation of expedited spent 6
fuel transfer from the spent fuel pool (SFP) to dry cask storage for a reference plant, as 7
documented in SECY-13-0112, Consequence Study of a Beyond-Design-Basis Earthquake 8
Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water Reactor, dated October 9, 2013, 9
and in NUREG-2161, Consequence Study of a Beyond-Design-Basis Earthquake Affecting the 10 Spent Fuel Pool for a U.S. Mark I Boiling-Water Reactor. The contents of this enclosure should 11 be considered with the subsequent detailed analyses supporting COMSECY-13-0030, Staff 12 Evaluation and Recommendation for Japan Lessons-Learned Tier 3 Issue on Expedited 13 Transfer of Spent Fuel. Enclosure H-6, Summary of Detailed Analyses in 14 COMESECY-13-0030, Enclosure H-1, Regulatory Analysis for Japan Lessons-Learned Tier 3 15 Issue on Expedited Transfer of Spent Fuel, to this appendix summarizes the detailed analyses 16 for COMSECY-13-0030.
17 18 Problem Statement and Regulatory Objectives 19 20 Previous risk studies have shown that storage of spent fuel in a high-density configuration in 21 SFPs is safe and that the risk is appropriately low (see for example, NUREG-1738, Technical 22 Study of Spent Fuel Pool Accident Risk at Decommissioning Nuclear Power Plants). These 23 studies used simplified and sometimes bounding assumptions and models to characterize the 24 likelihood and consequences of beyond-design-basis accidents involving SFPs. As part of the 25 Nuclear Regulatory Commissions (NRCs) post-9/11 security assessments, detailed 26 thermal-hydraulic and severe accident progression models for SFPs were developed and 27 applied to assess the realistic heatup of spent fuel under various pool draining conditions. In 28 2009, together with these post-9/11 security assessments, the NRC issued additional regulatory 29 requirements codified in Title 10 of the Code of Federal Regulations (10 CFR) Part 50, 30 Section 54, Conditions of licenses. In particular, 10 CFR 50.54(hh)(2) requires that each 31 reactor licensee develop and implement guidance and strategies intended to maintain or restore 32 core cooling, containment, and SFP cooling capabilities under conditions associated with certain 33 beyond-design-basis events.
34 35 Following the 2011 accident at the Fukushima Dai-ichi nuclear power plant in Japan that 36 resulted from the Tohoku earthquake and tsunami, several stakeholders submitted comments to 37 the NRC Commission and staff requesting that regulatory action be taken to require the 38 expedited transfer of spent fuel stored in SFPs to dry casks. The basis for these requests was 39 that expediting the transfer of spent fuel in SFPs to dry casks would reduce the potential 40 consequences associated with a loss of SFP coolant inventory by decreasing the amount of 41 spent fuel stored in affected SFPs, thereby decreasing the heat generation rate and 42 radionuclide source term associated with affected spent fuel. In response to Commission 43 direction in staff requirements memorandum (SRM)-SECY-12-0025, Staff Requirements 44 SECY-12-0025Proposed Orders and Requests for Information in Response to Lessons 45 Learned from Japans March 11, 2011, Great Tohoku Earthquake and Tsunami, dated 46 March 9, 2012, the staff implemented regulatory actions that originated from the Near-Term 47 48
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-112 Task Force (NTTF) recommendations to enhance reactor and SFP safety. The staff issued two 1
orders requiring enhancements to SFP safety:
2 3
- 1.
Order EA-12-049, Issuance of Order to Modify Licenses with Regard to Requirements 4
for Mitigation Strategies for Beyond-Design-Basis External Events, dated 5
March 12, 2012, which requires that licensees develop, implement, and maintain 6
guidance and strategies to maintain or restore core cooling, containment, and SFP 7
cooling capabilities following a beyond-design-basis external event.
8 9
- 2.
Order EA-12-051, Order Modifying Licenses with Regard to Reliable Spent Fuel Pool 10 Instrumentation, dated March 12, 2012, which requires that licensees install reliable 11 means of remotely monitoring wide-range SFP levels to support effective prioritization of 12 event mitigation and recovery actions in the event of a beyond-design-basis external 13 event.
14 15 The results are based on previous risk studies without these enhancements, in which the staff 16 had concluded that existing requirements for both SFPs and dry casks provide adequate 17 protection of public health and safety. However, in response to events following the accident at 18 Fukushima, the staff determined that it should (1) confirm that high-density SFP configurations 19 continue to provide adequate protection of public health and safety; and (2) assess potential 20 safety benefits (or detriments) and costs associated with expediting the transfer of spent fuel 21 from the SFP to dry casks at a reference plant with a boiling-water reactor (BWR) and Mark I 22 containment design (the same type of reactor involved in the Fukushima Dai-ichi nuclear power 23 plant accident).
24 25 Regulatory Alternatives 26 27 The regulatory analyses performed in support of SECY-13-0112 and NUREG-2161 considered 28 the following two regulatory alternatives that address spent fuel storage requirements:
29 30
- 1.
Option 1: Maintain Existing Spent Fuel Storage Requirements (Status Quo). This 31 alternative reflected the Commission decision not to expedite the storage of spent fuel 32 from SFPs to dry casks but to continue with the NRCs existing regulatory requirements 33 for spent fuel storage. Under this alternative, spent fuel is moved into dry storage only 34 as necessary to accommodate fuel assemblies being removed from the core during 35 refueling operations. It also assumed that all applicable requirements and guidance to 36 date had been implemented, but no implementation was assumed for related generic 37 issues or other staff requirements or guidance that were unresolved or still under review 38 at the time of the analysis. This alternative assumed (1) continued storage of spent fuel 39 in high-density racks within a relatively full SFP, and (2) compliance with all current 40 regulatory requirements, including those described above for 10 CFR 50.54(hh)(2),
41 Order EA-12-049, and Order EA-12-051.30 Furthermore, because SFPs have a limited 42 amount of available storageeven after licensees expanded their storage capacity 43 using high-density storage racksthe alternative assumed that the existing practice of 44 transferring spent fuel from SFPs to casks in accordance with 10 CFR Part 72, 45 Licensing Requirements for the Independent Storage of Spent Nuclear Fuel and 46 30 Although Option 1 assumed compliance with the post-Fukushima mitigation strategies required under Order EA-12-049 and the reliable SFP instrumentation required under Order EA-12-051, this was not explicitly modeled as part of the study. Instead, compliance with these requirements was treated as a qualitative factor that would significantly enhance the likelihood of successful mitigation, and thereby reduce the conditional probability of radiological release under Option 1.
H-113 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 High-Level Radioactive Waste, and Reactor-Related Greater than Class C Waste, 1
would continue. This alternative represented the status quo and served as the 2
regulatory baseline against which the costs and benefits of Option 2 were measured.
3 4
- 2.
Option 2: Expedited Spent Fuel Transfer to Achieve Low-density SFP Storage. This 5
alternative assumed that older spent fuel assemblies would be expeditiously moved from 6
SFP storage to dry cask storage beginning in 2014 to achieve and maintain a 7
low-density loading of spent fuel in existing high-density racks within 5 years. It did not 8
evaluate re-racking of the SFP to a low-density rack configuration because such a 9
situation was judged to be inefficient in terms of regulatory benefit, given that much of 10 the benefit could be achieved by storing less fuel in the existing high-density racks.
11 Because of the low-density SFP loading, this alternative had a smaller long-lived 12 radionuclide inventory in the SFP, a lower overall heat load in the SFP, and a slight 13 increase in the initial water inventory that displaced the removed spent fuel assemblies.
14 15 The staff recognized potential cost and risk impacts associated with the transfer of spent fuel 16 from SFPs to dry casks after 5 years of cooling and during long-term dry cask storage. If 17 included, these cost and risk impacts would have reduced the overall net benefit of Option 2 18 relative to Option 1. However, these effects were conservatively ignored to calculate the 19 potential benefit per reactor-year by comparing only the safety of high-density SFP storage to 20 low-density SFP storage and its implementation costs.
21 22 Safety Goal Evaluation 23 24 To perform the safety goal evaluation, the staff analyzed the regulatory alternatives to directly 25 compare their potential safety benefits to the quantitative health objectives (QHOs) for average 26 individual early fatality risk and average individual latent cancer fatality risk described in the 27 Commissions Safety Goal Policy Statement (NRC, 1986).
28 29 Since the reactor building that houses the SFP does not provide a containment barrier like the 30 containment structure surrounding the reactor coreespecially under conditions postulated to 31 dominate the release of radioactive materials from spent fuelthe staff assumed the frequency 32 of a release of radioactive material to the environment would be the same as the frequency of 33 spent fuel damage. Under this assumption, the radiological release frequency was estimated to 34 range from 7x10-7 to 5x10-6 per reactor-year, when considering all initiators that could challenge 35 SFP cooling or integrity.
36 37 Despite the large releases for certain predicted accident progressions, the staff determined 38 there was zero average individual early fatality risk, conditioned on the assumed occurrence of 39 the modeled severe accident scenarios. In part, this was because the modeled accident 40 progressions resulted in releases that begin late relative to the time needed to evacuate 41 members of the public living near the modeled nuclear power plant site.
42 43 Using the upper limit of the spent fuel damage and radiological release frequency of 5x10-6 per 44 reactor-year combined with a conditional average individual latent cancer fatality risk within 45 10 miles of 4x10-4 resulted in a bounding average individual latent cancer fatality risk of 46 2x10-9 per reactor-year. This calculated value was about 3 orders of magnitude below the QHO 47 of 2x10-6 per reactor-year for an average individual latent cancer fatality risk within 10 miles.
48 The staff therefore concluded that Option 2 could not result in a substantial increase in overall 49 protection of public health and safety.
50 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-114 Technical Evaluation 1
2 The staff performed detailed analyses using state-of-the-art, validated, deterministic methods 3
and assumptions, supplemented with probabilistic insights where practical.
4 5
The study considered two SFP configurations:
6 7
- 1.
High-density Loading Configuration: A relatively full SFP in which the hottest spent fuel 8
assemblies are surrounded by four cooler fuel assemblies in a 1x4 loading pattern 9
throughout the pool31 10 11
- 2.
Low-density Loading Configuration: A minimally loaded pool in which all spent fuel with 12 at least 5 years of pool cooling has been removed to ensure the hottest fuel assemblies 13 are surrounded by additional water 14 15 To evaluate the potential benefits of mitigation strategies required in 10 CFR 50.54 (hh)(2), the 16 study analyzed each loading configuration for two different cases(1) the mitigated case, in 17 which 10 CFR 50.54 (hh)(2) mitigation strategies were assumed to be successful and (2) the 18 unmitigated case, in which these mitigation strategies were assumed to be unsuccessful.
19 Following the evaluation of these cases, the staff performed a limited scope human reliability 20 analysis to estimate the likelihood of successful operator actions implementing 21 10 CFR 50.54(hh)(2) mitigation measures to prevent fuel damage. Key assumptions made in 22 this limited scope human reliability analysis are that (1) post-earthquake onsite portable 23 mitigation equipment required by 10 CFR 50.54(hh)(2) was available, (2) minimum plant staffing 24 was available for implementing SFP mitigation, and (3) operators had access to areas needed 25 to implement mitigation measures. The study considered scenarios in which some preplanned 26 and improvised mitigating actions were either unsuccessful or not implemented before the 27 analysis was terminated at 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br />. For example, in addition to the 10 CFR 50.54(hh)(2) 28 mitigation strategies, the site emergency response organization would request support from 29 offsite response organizations to implement additional mitigating actions that are improvised, 30 such as pumping water into the SFP using a fire truck. However, these additional mitigating 31 actions were determined to be beyond the scope of the study.
32 33 Accident Scenario Selection 34 35 Previous risk studies had shown that earthquakes represent the dominant risk contributor for 36 SFPs. Therefore, to deliberately challenge the integrity of the SFP, the accident initiator for this 37 study was a beyond-design-basis earthquake with ground motion (0.7g peak ground 38 acceleration) stronger than the maximum earthquake reasonably expected to occur for the 39 reference plant. An earthquake of this severity was estimated to occur about once every 40 60,000 years.
41 42 The SFP accident scenarios evaluated in this study were developed for a single operating cycle.
43 However, the conditions of the SFP change throughout an operating cycle. For example, the 44 SFP can change from being an isolated pool to being hydraulically connected to the reactor 45 vessel (e.g., during refueling operations), or spent fuel can be moved around within the SFP 46 during a cycle to satisfy regulatory requirements with respect to criticality or heat distribution.
47 Such changes affect the consequences of a postulated accident. Therefore, for this study, the 48 31 A limited sensitivity analysis of a 1x8 spent fuel configuration and a uniform configuration was also performed to better understand the potential effects of plausible alternative SFP configurations on results and insights.
H-115 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 continual changes that occur during a single operating cycle were discretized into discrete 1
quasi-steady snapshots referred to as operating cycle phases (OCPs). Since the number of 2
OCPs has a roughly linear scaling effect on the number of MELCOR analyses required, the 3
study defined in terms of the minimum number that most accurately represented pool-reactor 4
configurations (i.e., whether the SFP is connected to the reactor), spent fuel loading 5
configurations, and decay heat levels. Five OCPs were identified based on the timing of fuel 6
movement, key changes in pool-reactor configuration, and peak assembly and whole pool 7
decay heat curves, as listed in Table H-25. Note that, while the beyond-design-basis 8
earthquake described above is equally likely to happen throughout an entire operating cycle, the 9
conditional probability of it occurring during a given OCP is the length of time in an OCP divided 10 by the duration of the entire operating cycle (i.e., fraction of time in each OCP).
11 12 Table H-25 Operating Cycle Phase Descriptions 13 OCP No.
OCP Description OCP Time Duration (days)
% of Total Operating Cycle Pool-Reactor Configuration*
1 Defueling of reactor core (~1/3 core) 2-8 0.9 Refueling 2
Reactor testing, maintenance, inspection and refueling 8-25 2.4 Refueling 3
Highest decay power portion of non-outage period 25-60 5
Unconnected 4
Next highest decay power portion of non-outage period 60-240 25.7 Unconnected 5
Remainder of operating cycle 240-700; 0-2 66 Unconnected
- Note: The refueling pool-reactor configuration refers to the configuration in which the SFP and the reactor are 14 hydraulically connected. During other stages of the operating cycle, the SFP and reactor are not connected.
15 16 As part of scenario development, the study also considered onsite mitigation and offsite support.
17 It treated onsite mitigation by modeling two cases, successful and unsuccessful mitigation, for 18 each scenario. Successful mitigation occurred when mitigative actions required by 19 10 CFR 50.54(hh)(2) were successfully deployed, additional onsite capabilities were used to 20 extend the use of the mitigation equipment, and arrival of offsite resources allowed the 21 mitigative equipment to be used until onsite capabilities could be recovered. Unsuccessful 22 mitigation occurred when none of the onsite mitigative actions were successful for an extended 23 period. Offsite support was treated using the following assumptions:
24 25 Offsite support arrives within 24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />.
26 27 Actions are planned, and equipment is staged within 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br />.
28 29 The accident progression analysis is truncated if the fuel is not uncovered and the pool 30 can be refilled by 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br /> with an injection rate of 500 gallons per minute.
31 32 If the above mitigation actions are unsuccessful, the sequence is run to 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br />.
33 34 To develop accident scenarios, the NRC made several key assumptions based on structural 35 analyses, including (1) all offsite and onsite alternating current power is lost as a result of the 36 seismic event, (2) direct current power may be lost, (3) 10 CFR 50.54(hh)(2) equipment, when 37 credited, is available for the duration of the event, (4) tearing of the SFP liner is possible, and 38 (5) there is no failure of penetrations. Based on these and other assumptions, the NRC 39 developed six accident cases for each OCP using a combination of zero, small, and moderate 40
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-116 leakage damage states with successful and unsuccessful mitigation actions taken for each 1
leakage scenario. The staff used these accident cases for both high-and low-density loading 2
configurations, as summarized in Table H-26.
3 4
Table H-26 Scenario Descriptions for a Given Operating Cycle Phase 5
Case No.
Scenario Characteristics SFP Leakage Rate Mitigation?
1 None Yes 2
No 3
Small Yes 4
No 5
Moderate Yes 6
No 6
7 MELCOR Severe Accident Progression and Source Term Analyses 8
9 Analysts used the MELCOR code (Version 1.8.6) to model severe accident progression for the 10 scenarios described in the previous section. Enclosure H-1, Description of Analytical Tools and 11 Capabilities, to this appendix describes the MELCOR code. The code was ideal for modeling 12 accident progression for SFPs because SFP models had already been developed and 13 validated, and it was also capable of modeling in-building transport/retention and radionuclide 14 release, the latter of which was a key input for subsequent accident consequence analysis 15 modeling using the MELCOR Accident Consequence Code System (MACCS).
16 17 To facilitate modeling of the SFP for BWR fuel assemblies, the staff used a recently developed 18 rack component for improved spent fuel rack modeling and an oxidation kinetics model. These 19 two additions to MELCOR enabled the evaluation of two types of SFP accidents: a partial 20 loss-of-coolant inventory or boiloff accident, and a complete loss-of-coolant inventory accident.
21 A partial loss-of-coolant inventory or boiloff accident could involve no or late uncovery of the 22 bottom of the racks, and boiloff of the coolant could ultimately lead to hydrogen combustion. A 23 complete loss-of-coolant accident occurs when the bottom of the racks is uncovered, leading to 24 air oxidation of the cladding and enhanced ruthenium release.
25 26 The staff used the radionuclide package in MELCOR to model the release and transport of 27 fission product vapors and aerosols. It tracks radionuclides by combining them into material 28 classes, which are groups of elements with similar chemical and transport behavior. The SFP 29 MELCOR model includes 15 default material classes and 2 user-defined classes that can model 30 cesium iodide and cesium molybdate behavior. This study modified the default cesium, iodine, 31 and molybdenum radionuclide classes to accommodate new insights obtained from the Phebus 32 experimental program.32 In addition, the staff developed a new ruthenium release model in 33 which it adjusted the default vapor pressure parameters for the ruthenium material class to 34 match the ruthenium dioxide vapor pressure at 2,200 K. However, it only used this latter model 35 in scenarios involving rapid draindown (i.e., moderate leak rates) in the SFP. All scenarios 36 applied a 5 percent gap release criterion.
37 38 32 The PHEBUS Fission Products international research program took place between 1988 and 2010. Its purpose was to improve the understanding of the phenomena occurring during a core meltdown accident in a light-water reactor and to reduce uncertainties in calculated radionuclide releases for reactor safety evaluations that model core meltdown accidents.
H-117 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 The decay heat and radionuclide packages were used to calculate the fission product inventory 1
and specific decay power for 29 elemental groups; the specific elemental decay power is 2
compiled as a function of time after shutdown. Because these packages were originally 3
designed for reactor accident progression analyses, the shutdown time for each assembly is the 4
same. Unlike the case for reactor accidents, SFP accidents involve fuel assemblies with 5
multiple shutdown times. To address this discrepancy, a scaling procedure in MELCOR 6
enabled the use of batch-average decay heat results. Each batch also used a post-processing 7
routine with MELCOR-predicted release fractions and actual inventories. Lastly, to map the 8
calculated releases from MELCOR to the MACCS33 code for accident consequence analyses, 9
the MELCOR input file was modified to enable tracking of fission product releases from each 10 ring, or collection of assemblies in the MELCOR radial nodalization, as well as the subsequent 11 releases to the environment.
12 13 To calculate the above mentioned radionuclides and decay heats, the reference plants utility 14 provided information for all assemblies that had been discharged from the reference plant to the 15 SFP over 18 cycles. From this information, the actual analysis basis for the high-density SFP 16 inventory was 3,055 assemblies, based on the SFP capacity of 3,819 assemblies minus 17 764 assemblies to accommodate a full core offload capability. Although the utility provided data 18 for 18 discharge cycles, this study only included cycles 7-18, since these cycles provided the 19 requisite target inventory (3,055 assemblies). For the burnup analysis, the ORIGEN code 20 simulated the irradiation and decay history for each of the 3,055 assemblies. In this case, the 21 assemblies were each decayed to a reference date, which was the end of the last cycle (18),
22 and the resulting inventories were combined into groups for analysis. These analysis groups 23 were additionally decayed to determine assembly activities and decay heat power to simulate 24 cooling of the discharged fuel after reactor shutdown. The assemblies were then placed into six 25 groups according to the cycle in which they were discharged. The benefit of grouping these 26 assemblies in this manner is that it facilitated the use of the data for analyses of low-density 27 SFP configurations in which assemblies that had been cooled for more than 5 years were 28 removed.
29 30 Description of SFP MELCOR Models 31 32 The SFP for the reference plant is located on the refueling floor of the reactor building. In one 33 corner of the SFP is a cask area. At the bottom of the SFP, high-density SFP racks are located 34 to store the SFP. During operation, these racks are covered with approximately 23 feet of water 35 to provide radiation shielding. Each rack is rectilinear in shape and comes in nine different 36 sizes, and a total of 3,819 storage locations are located in the pool. Each stainless-steel rack 37 includes cell assemblies, a baseplate with flow-through holes, and base support assemblies.
38 39 For the entire SFP model, MELCOR used a series of control volumes for regions at the top and 40 bottom of the SFP (see Figures 39 and 40 in NUREG-2161). The region at the bottom of the 41 SFP containing the empty and loaded spent fuel storage racks was more finely divided into 42 several control volumes to enable detailed analyses of all 3,819 storage locations for high-and 43 low-density configurations. The BWR assembly canisters were modeled using the MELCOR 44 canister component. In addition to the detailed SFP model, the staff used a simplified reactor 45 building model consisting solely of the refueling room, since the bulk of the reactor building 46 33 At the time of this analysis, the MACCS code was called the MACCS2 code, a leftover notation from the time that the original MACCS code was substantially upgraded to Version 2. Since then, the staff has referred to the code as the MACCS code and notes the version number of the code used in a particular analysis, since code development and maintenance continues.
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-118 components do not play a significant role in SFP accidents. The refueling room was modeled 1
using a single control volume in MELCOR, which accounted for nominal reactor building 2
leakage and simulated overpressure failure flowpaths.
3 4
To model reactor outages in which the SFP and the reactor are hydraulically connected 5
(i.e., OCP1 and OCP2), a single control volume represented the reactor well and 6
separator/dryer pool. This control volume was then connected to the spent fuel model 7
described above for the analyses. For each OCP, the assembly layout was also modified to 8
account for assembly offloads for both the high-and low-density loadings.
9 10 MELCOR Accident Progression Analysis Results and Source Terms 11 12 The MELCOR analyses of the six cases per OCP and illustrated in Table H-26 revealed that 13 four classes of scenarios did not lead to a release:
14 15 boiloff scenarios with no SFP leaks 16 17 mitigated scenarios for small leaks 18 19 unmitigated scenarios in late phases (OCP4, OCP5) 20 21 mitigated moderate leak scenarios in OCP2, OCP3, OCP4, and OCP5 22 23 For the boiloff scenarios, a simplified MELCOR model in which all assemblies are combined in 24 only two rings (collections of assemblies) that represent the fuel and empty cells was used to 25 estimate the pool heatup and water level drop. The study used the thermal-hydraulic models in 26 MELCOR, and the simplified model for boiloff, to evaluate sets of both low-density and 27 high-density cases. For both sets, no release occurred because the water level never dropped 28 below the top of the SFP racks. If boiloff of the coolant below the top of the SFP racks had 29 occurred, it could have led to steam generation, oxidation of the cladding, hydrogen production, 30 and possibly hydrogen combustion and release of radionuclides. Similarly, none of the 31 mitigated scenarios for small leaks led to release during any OCP because the rate of water 32 injection (500 gallons per minute) as a mitigative action ensured that the fuel never became 33 uncovered or overheated.
34 35 The results of MELCOR analyses of the unmitigated scenarios in OCP4 and OCP5 indicated 36 that, although there was fuel heatup in both high-and low-density configurations after the rack 37 baseplate was uncovered, there was no release because the total decay heat of the assemblies 38 in these stages was at least 37 to 48 percent lower than the total decay heat of assemblies in 39 OCP3, and natural circulation was sufficient to slow down the rate of fuel heatup to the point at 40 which the fuel failure could occur.
41 42 For moderate leaks, mitigation involved spray activation for outage phases OCP1 and OCP2, 43 and direct injection for post-outage phases OCP3, OCP4, and OCP5. The results of analyses 44 of moderate leaks during phase OCP2 indicated that no releases occurred from various heat 45 transfer mechanisms. Since the unmitigated scenarios for phases OCP3, OCP4, and OCP5 led 46 to no release, the study only evaluated the results of the high-density moderate leak scenario 47 for phase OCP3 (with and without spray flow turned on). The staff determined that modeling the 48 mitigation of moderate leak scenarios with and without the spray mechanism activated led to no 49 release of radionuclides because the fuel clad temperature never surpassed 900 degrees 50
H-119 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Celsius (C) (1,652 degrees Fahrenheit (F)), at which point gap release would begin to occur. A 1
key observation was that these results underscored the importance of natural circulation of air 2
through the racks for heat removal to help keep the fuel clad temperatures below the gap 3
release temperature. The study also modeled the moderate leak scenario for OCP3, assuming 4
an additional 3-hour delayed activation of the spray for a spray activation time of 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> after 5
the leak occurs. In this case, it was shown that the maximum clad temperature reached just 6
under 627 degrees C (1,160 degrees F) after 6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br />, at which point the activated spray was 7
sufficient to keep the fuel clad well below the gap release temperature of 900 degrees C 8
(1,652 degrees F).
9 10 The 14 scenarios that led to release of radionuclides can be categorized as follows:
11 12 unmitigated small leaks in OCP1, OCP2, and OCP3, in both high-and low-density 13 configurations 14 15 unmitigated moderate leaks in OCP1, OCP2, and OCP3, in both high-and low-density 16 configurations 17 18 mitigated moderate leak in OCP1 in both high-and low-density configurations 19 20 Tables H-27 and H-28 summarize the release characteristics for the 14 scenarios that led to a 21 release of radionuclides.
22 23 Table H-27 Summary of Release Results for High-Density Configurations 24 High-Density Case No.
Scenario Characteristics Release Characteristics SFP Leakage 50.54(hh)(2)
Equipment?
Cesium Release at 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br /> Cs-137 Released (MCi)
Iodine Release at 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br /> I-131 Released (MCi)
OCP1 Small No 0.6%
0.33 3.5%
0.27 Moderate Yes 0.5%
0.26 5.0%
0.39 Moderate No 1.5%
0.8 2.1%
0.16 OCP2 Small No 17.1%
7.90 17.1%
1.91 Moderate No 1.6%
0.73 2.0%
0.22 OCP3 Small No 42.0%
24.20 51.2%
0.73 Moderate No 0.7%
0.39 0.7%
0.01 25 26 Table H-28 Summary of Release Results for Low-Density Configurations 27 Low-Density Case No.
Scenario Characteristics Release Characteristics SFP Leakage 50.54(hh)(2)
Equipment?
Cesium Release at 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br /> Cs-137 Released (MCi)
Iodine Release at 72 hours8.333333e-4 days <br />0.02 hours <br />1.190476e-4 weeks <br />2.7396e-5 months <br /> I-131 Released (MCi)
OCP1 Small No 3.1%
0.33 4.6%
0.36 Moderate Yes 1.8%
0.19 7.0%
0.55 Moderate No 0.5%
0.05 1.7%
0.13 OCP2 Small No 1.7%
0.28 3.3%
0.37 Moderate No 0.4%
0.07 0.7%
0.08 OCP3 Small No 0.6%
0.10 1.2%
0.02 Moderate No 0.1%
0.02 0.2%
0.00
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-120 Unmitigated moderate leaks for high-density configurations in OCP1, OCP2, and OCP3 did not 1
lead to hydrogen deflagration, and the releases were relatively low since oxygen depletion 2
limited clad oxidation and fuel heatup. Similarly, none of the scenarios for the low-density 3
configurations led to hydrogen deflagration, and the release fractions were typically low and 4
comparable to the analogous scenario for the high-density loading configuration. One exception 5
to this trend is the low-density OCP1 scenario for mitigated moderate leaks. In this case, the 6
low-density case has slightly higher releases than the high-density cases because there was 7
higher and faster heatup of the most recently discharged assemblies in the low-density cases.
8 The higher initial fuel temperatures in the low-density case led to slightly higher releases.
9 Notably, the highest release fractions for cesium and iodine were observed for scenarios that 10 led to hydrogen combustion; namely, unmitigated small leaks for high-density configurations in 11 OCP2 and OCP3.
12 13 The release data in the tables above were used as input for the accident consequence 14 analyses, as described in the following section.
15 16 MACCS Consequence Analyses 17 18 Based on results from the MELCOR modeling of SFP accident progression scenarios, the staff 19 used Version 2 of the MELCOR Accident Consequence Code System (MACCS, Revision 3.7.0) 20 to model offsite consequence analyses. MACCS can evaluate the impacts of atmospheric 21 releases of radioactive aerosols and vapors on human health and on the environment by using 22 site-specific weather conditions, population data, and evacuation plans. Quantification of the 23 effects of offsite radioactive releases on human health is accomplished by modeling and 24 evaluating the relevant dose pathways; namely, cloudshine, inhalation, groundshine, and 25 ingestion. Enclosure H-1 to this appendix describes the MACCS suite of codes.
26 27 A source term definition was created for each accident consequence evaluation as described 28 below. The ORIGEN code calculated the activity levels of the different radionuclides of the fuel 29 in the SFP, while the plume characteristicsincluding chemical group release rates, aerosol 30 size distributions, density, and mass flow rateswere obtained from the MELCOR analyses 31 described in the previous section. The 14 MELCOR sequences that led to release (see 32 Tables H-27 and H-28 above) were binned by their cesium (Cs)-137 and iodine (I)-131 release 33 activities to lessen the computational cost of the MACCS calculations. Sequences were first 34 grouped into three bins based on their Cs-137 release activities (i.e., 0-0.25, 0.25-0.55, and 35 greater than 0.55 megacuries (MCi) of Cs-137 released) because Cs-137 is the most significant 36 contributor to long-term consequences and groundshine dose. The sequences were then 37 binned based on I-131 release (i.e., 0-0.5, 0.5-5, and greater than 5 MCi of I-131 released) 38 because I-131 is a good indicator for short-lived radionuclides that may be released from 39 recently discharged fuel. In this manner, the 14 release sequences were ultimately binned into 40 nine radiological release categories (RCs), with only four RCs containing at least two release 41 sequences. The staff chose one sequence from each of the four RCs to represent the entire 42 RC except for RC33. The study analyzed both release sequences in RC3 because these 43 release sequences had the highest releases of all sequences. The binning of the 14 MELCOR 44 sequences that led to release is illustrated in Tables H-29 and H-30 for high-density and 45 low-density loading cases with and without mitigation. The sequences that were selected for 46 further analysis are indicated in Tables H-29 and H-30 with bold text for emphasis.
47 48
H-121 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-29 Binning of MELCOR Release Sequences into Release Categories for 1
High-Density Configurations 2
High-Density Case No.
Scenario Characteristics Release Characteristics SFP Leakage 50.54(hh)(2)
Equipment Deployed Cs-137 Released (MCi)
I-131 Released (MCi)
Release Category Sequence Analyzed in MACCS OCP1 Small**
No 0.33 0.27 RC12 Yes Moderate Yes 0.26 0.39 RC12 No Moderate No 0.8 0.16 RC21 No OCP2 Small No 7.90 1.91 RC33 Yes*
Moderate No 0.73 0.22 RC21 Yes OCP3 Small No 24.20 0.73 RC33 Yes*
Moderate No 0.39 0.01 RC11 No
- The release scenarios for both sequences in RC33 were evaluated in MACCS because of the comparatively higher 3
releases compared to other scenarios.
4
- The sequences that were selected for further analysis are indicated with bold font.
5 6
Table H-30 Binning of MELCOR Release Sequences into Release Categories for 7
Low-Density Configurations 8
Low-Density Case No.
Scenario Characteristics Release Characteristics SFP Leakage 50.54(hh)(2)
Equipment Deployed Cs-137 Released (MCi)
I-131 Released (MCi)
Release Category Sequence Analyzed in MACCS OCP1 Small No 0.33 0.36 RC12 No Moderate Yes 0.19 0.55 RC12 No Moderate No 0.05 0.13 RC11 No OCP2 Small No 0.28 0.37 RC12 No Moderate No 0.07 0.08 RC11 No OCP3 Small No 0.10 0.02 RC11 Yes Moderate No 0.02 0.00 RC11 No 9
- The sequence that was selected for further analysis is indicated with bold font.
10 11 The release data described above were used in MACCS for subsequent atmospheric transport 12 and dispersion modeling; exposure, dosimetry, and health effects modeling; emergency 13 response modeling; and long-term protective action modeling, as described in the next section.
14 15 MACCS Model Descriptions 16 17 Atmospheric Transport and Dispersion Modeling 18 19 The MACCS straight-line Gaussian plume segment dispersion model was used to model the 20 atmospheric transport and dispersion of radionuclides released for a given accident scenario.
21 The study divided radionuclides released into the atmosphere into plume segments that are 22 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> or less to match the resolution of the dispersion models to that of the weather data. In 23 addition, the aerosol size distributions obtained from MELCOR, combined with the aerosol 24 velocity data obtained from NUREG/CR-7161, Synthesis of Distributions Representing 25 Important Non-Site-Specific Parameters in Off-Site Consequence Analyses, issued April 2013, 26 were used to model deposition rates of aerosols from the plume to the ground.
27 28
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-122 One year of hourly meteorological data from onsite meteorological tower observations 1
documented in NUREG-1935, State-of-the-Art Reactor Consequence Analyses (SOARCA) 2 Report, was used for atmospheric modeling in this study. Specifically, the study used 3
meteorological data from the year 2006 at the reference plant site was used. Since the exact 4
weather conditions for a potential future accident are unknown, MACCS accounts for weather 5
variability by analyzing a statistically significant set of weather trials. In this way, the modeled 6
results are an ensemble that represents the full spectrum of meteorological conditions. The 7
nonuniform weather binning strategy used to sample sets of weather data is based on the 8
approach used in NUREG/CR-7009, MACCS Best Practices as Applied in the State-of-the-Art 9
Reactor Consequence Analyses (SOARCA) Project, issued August 2014.
10 11 Exposure, Dosimetry, and Health Effects Modeling 12 13 Groundshine, cloudshine, inhalation, and ingestion are exposure pathways considered in 14 MACCS to calculate population dose and health effects. In general, food ingestion parameters 15 in NUREG/CR-6613, Volume 1, Code Manual for MACCS2: Users Guide, issued May 1998, 16 were used to calculate ingestion dose. Shielding factors applied to evacuation, normal activity, 17 and sheltering for each dose pathway were obtained from NUREG/CR-7009.
18 19 The Federal Guidance Report 13, Cancer Risk Coefficients for Environmental Exposures to 20 Radionuclides, issued September 1999, provided the dose coefficients, risk factors, and 21 relative biological effectiveness. As implemented in MACCS, the Federal Guidance Report 22 13 dose coefficients along with the dose and dose rate effectiveness factors were incorporated 23 in the dose response modeling for the early phase for doses less than 20 rem and in the 24 long-term phase of the offsite consequences. The risk factors were implemented in MACCS for 25 seven organ-specific cancers, as well as residual cancers that were not accounted for directly.
26 NUREG/CR-7161 provided parameters related to health effects, as well as other 27 non-site-specific data used for consequence analysis.
28 29 The NRC used SECPOP2000 to create a MACCS site file containing population and economic 30 data for 16 compass sectors. The site file was then interpolated onto a 64-compass sector grid 31 to improve spatial resolution for the consequence analysis. Site population data were 32 extrapolated to the year 2011 using census data from the year 2000 and a multiplier of 1.1051 33 from the U.S. Census Bureau to account for the average population growth in the United States 34 between 2000 and 2011. Similarly, economic values from the SECPOP2000 database, whose 35 values are based on year 2002 economic data, were scaled by 1.250 derived, based on the 36 consumer price index to account for price escalation (i.e., increasing value of the dollar) 37 between 2002 and 2011.
38 39 Emergency Response Modeling 40 41 The MACCS models for the emergency phase, which is the 7-day period following the start of a 42 release, calculated the dose and associated health effects to the public as well as the effects of 43 emergency preparedness actions that protect the public. To model emergency response the 44 staff developed three evacuation models based on whether 4-day dose projections were 45 expected to exceed 1 rem for a member of the public, at which point the protective action 46 guideline (PAG) was considered to be exceeded(1) a small projected dose that does not 47 exceed the PAG at the emergency planning zone (EPZ), (2) a large projected dose (within 48 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br />) that exceeds the PAG at the EPZ, and (3) a large projected dose (within 24 hours2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />) 49 that exceeds the PAG at the EPZ. For each model, specific protective actions (e.g., general 50 public evacuation, hotspot relocation, shadow relocation) were included for populations within 51
H-123 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 and beyond the EPZ. To model population evacuation in these models, the population was 1
divided into cohorts, which are population groups that move differently from other groups. The 2
cohorts were loaded onto the roadway network at a specified time, and a set of speed values 3
were applied per cohort for the early, middle, and late periods of the evacuation. The last 4
10 percent of the population to evacuate (i.e., the evacuation tail) was modeled as a separate 5
cohort. For residents within the EPZ, the MACCS potassium iodide model used in the analysis 6
assumes that potassium iodide would only be distributed within the EPZ, and 50 percent of the 7
population within the EPZ would have access to and take it as directed.
8 9
Long-term Protective Action Modeling 10 11 MACCS was also used to model the long-term protective action phase (i.e., the 50-year period 12 following the 7-day emergency phase). Three protective actions were modeled for 13 contaminated land during the long-term phase: interdiction, decontamination, and 14 condemnation. In the MACCS model, interdiction and condemnation are defined in terms of 15 habitability. Interdiction is a temporary relocation during which land contamination levels are 16 reduced by decontamination, natural weathering, and radioactive decay to restore habitability. If 17 contamination levels cannot be adequately reduced to restore habitability within 30 years, the 18 land is considered condemned, and the population is modeled not to return during the long-term 19 phase (i.e., permanently relocated). Based on the location of the reference plant in 20 Pennsylvania, this study used a habitability criterion of 500 millirem (mrem) per year beginning 21 in the first year. Two levels of decontamination with decontamination factors of 3 and 15 were 22 modeled for a 1-year timespan. The cost of decontamination during this period was determined 23 using values in NUREG/CR-7009.
24 25 This study also considered land suitable for farming (farmability). Values used to define 26 farmability were taken from NUREG-1150, Severe Accident Risks: An Assessment for Five 27 U.S. Nuclear Power Plants, issued December 1990. Agricultural land with contamination 28 levels in excess of the farmability criteria was considered unfarmable, and no farming was 29 allowed until the farmability criteria were satisfied.
30 31 MACCS Consequence Analysis Results 32 33 Table H-31 summarizes the mean reduction in offsite consequence results in terms of averted 34 population dose (person-rem) and averted economic costs (2012 dollars) associated with 35 implementing Option 2 (expedited spent fuel transfer to achieve low-density SFP storage). The 36 reported consequence metrics represent averted consequences that were calculated by taking 37 the difference between consequences for Option 1 (regulatory baseline) and consequences for 38 Option 2.
39 40 Table H-31 Mean Reduction in Offsite Consequence Results Associated with Option 2 41 Consequence Metrica Best Estimate Low Estimate High Estimate Averted 50-mile Population Dose (person-rem) 124 60 1260 Averted 50-mile Economic Costs (2012 dollars)
$723,300
$1,073,300
$4,587,800 a The reported consequence metrics represent averted consequences that were calculated by taking the difference 42 between consequences for Option 1 (regulatory baseline) and consequences for Option 2 (expedited spent fuel 43 transfer to achieve low-density SFP storage).
44 45 The consequence metrics for population dose and economic costs can vary significantly with 46 the criterion used to measure or estimate the level of land contamination and to inform decisions 47 about when to allow relocated populations to return to contaminated land areas. The offsite 48
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-124 consequence analysis performed in support of SECY-13-0112 and NUREG-2161 used three 1
PAG levels based on annual dose to calculate the estimates of averted population dose and 2
averted economic costs within 50 miles: (1) the U.S. Environmental Protection Agency (EPA) 3 intermediate phase PAG level of 2 rem in the first year, and 500 mrem annually thereafter, was 4
used to calculate the best estimate, (2) the more stringent Pennsylvania PAG level of 500 mrem 5
annually starting with the first year was used to calculate the low estimate, and (3) the less 6
stringent 2 rem annually was used to calculate the high estimate. The analysis calculated all 7
estimates assuming a remaining licensed term of 22 years (until 2034) for the reference plant 8
and using the reference sites offsite population density within a 50-mile radius from the site 9
(approximately 722 people per square mile).
10 11 The study included a limited treatment of uncertainty by describing results for a range of 12 sensitivity analyses performed to evaluate the effect of certain assumptions on results and 13 insights. Factors addressed in these sensitivity analyses included the following:
14 15 using a more favorable 1x8 fuel assembly pattern 16 17 using an unfavorable uniform fuel assembly pattern 18 19 radiative heat transfer 20 21 hydrogen combustion ignition criterion 22 23 occurrence of concurrent events involving the reactor or multiunit events 24 25 molten core-concrete interaction 26 27 alternative accident scenario truncation times 28 29 effects of reactor building leakage on hydrogen combustion and accident progression 30 31 Risk Evaluation 32 33 This study was a limited scope consequence analysis supplemented with probabilistic insights 34 to provide additional context and perspectives about the relative likelihood of events and 35 consequences. This analysis considered the following as examples of probabilistic insights:
36 37 risk information from past studies for accident scenario selection 38 39 initiating event frequency information 40 41 initiating event timing effects (e.g., the relative likelihood of an event occurring during 42 each OCP and the likely configurations incurred) 43 44 relative likelihoods of damage state characteristics 45 46 probabilistic consequence analysis to account for effects of statistical variability in offsite 47 weather conditions on offsite radiological consequences 48 49
H-125 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 While these elements provided some of the benefits of PRA, this study did not perform several 1
elements of a traditional PRA. The following are examples of traditional PRA elements that 2
were excluded from this study:
3 4
failure modes and effects analysis (except for certain structures, systems, or 5
components specifically identified in the study) 6 7
data analysis and component reliability estimation 8
9 dependency analysis 10 11 human reliability analysis as part of the accident progression and recovery (except the 12 limited scope human reliability analysis that was performed as described above) 13 14 system fault tree and accident sequence event tree development and quantification 15 16 Figure H-20 illustrates the conditional probability of SFP liner leakage and magnitude of release 17 from the SFPconditioned on the assumed occurrence of the beyond-design-basis earthquake 18 considered in the studyfor postulated accident scenarios that occur in different phases of the 19 operating cycle. The figure shows the results for both the high-density and low-density loading 20 configurations, as well as for the mitigated and unmitigated cases.
21 22 The inclusion of probabilistic insights allowed analysts to consider some aspects of likelihood 23 but could not support making definitive statements about SFP risk. This study focused on a 24 specific portion of the overall risk profileSFP accidents caused by large seismic events 25 between 0.5g and 1g. This study can therefore be used to corroborate or challenge the 26 continued applicability of estimates for this part of the risk profile based on previous studies. In 27 addition, since large seismic events have been shown in the past to be a dominant contributor 28 to SFP risk, this comparison helps to predict whether a full-scope PRA would be expected to 29 result in an overall decrease or increase in estimated risk. Therefore, the results of this study 30 can draw supportable, but not definitive, conclusions about overall SFP risk.
31 32
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-126 1
Figure H-20 Conditional Probability of SFP Liner Leakage and SFP Release Magnitude 2
3 Cost-Benefit Analysis Results 4
5 Table H-32 summarizes the results of the quantitative cost-benefit analysis for the best estimate 6
and low-and high-estimate cases for Option 2, documented in NUREG-2161, Appendix D. At 7
the time this regulatory analysis was prepared, returns on investments were well below the 8
3 percent and 7 percent discount rates described in the Office of Management and Budget 9
(OMB) Circular No. A-4, Regulatory Analysis, dated September 17, 2003. A sensitivity 10 analysis was performed using a 0 percent discount rate that produced undiscounted values in 11 constant dollars. Although it was common practice to provide undiscounted values for costs 12 and benefits for information purposes within regulatory analyses, it was not common practice to 13 report such results as part of a sensitivity analysis. However, the staff chose to report the 14 undiscounted costs and benefits as part of a sensitivity analysis for this regulatory analysis to 15 account for current market trends and future predictions. Note that this enclosure34 only 16 discusses the calculation of public health and offsite property attributes, which is based on the 17 detailed severe accident analysis using MELCOR and MACCS.
18 19 34 Methods for calculating occupational health, onsite property, and implementation costs are discussed elsewhere in NUREG-2161.
H-127 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 In addition to the sensitivity analysis described above to evaluate the effect on results of using a 1
0 percent discount rate, the staff performed sensitivity analyses to account for the effect on the 2
results of (1) using an alternative dollar per person-rem conversion factor ($4,000 per 3
person-rem instead of $2,000 per person-rem), (2) extending the analysis of consequences 4
beyond a 50-mile circular radius around the site, and (3) combining the effects of using the 5
$4,000 per person-rem conversion factor and extending the analysis of consequences beyond 6
50 miles from the site. Tables H-32 and H-33 summarize the results of these sensitivity 7
analyses.
8 9
As shown in Table H-33, requiring the expedited transfer of spent fuel from the SFP to dry cask 10 storage to achieve low-density SFP storage at the reference plant did not achieve a positive net 11 benefit for eight of the nine cases presented. The undiscounted high-estimate casewhich 12 reflects the costs and benefits at the time in which they are incurred with no present worth 13 conversion and which assumes the least stringent habitability criterionresulted in a positive 14 net benefit of about $27.1 million. However, the other high-estimate cases resulted in negative 15 net benefits of about ($10.6 million) and ($25.1 million), which differed from this case by 16 adjusting future costs and benefits into 2012 dollars using 3 percent and 7 percent discount 17 rates, respectively.
18
Table H-32 Summary of Benefits and Costs within 50 Miles for Option 2 1
Attribute Best Estimatea Low Estimatea High Estimatea Undiscounted 3% NPV 7% NPV Undiscounted 3% NPV 7% NPV Undiscounted 3% NPV 7% NPV Public Health (Accident)
$247,700
$179,500
$124,600
$119,700
$86,700
$60,200
$2,520,000
$1,825,500
$1,267,000 Occupational Health (Accident)
$1,300
$900
$700
$700
$500
$300
$21,300
$15,400
$10,700 Offsite Property
$723,300
$524,000
$363,700
$1,073,300
$777,500
$539,700
$4,587,800
$3,323,400
$2,306,700 Onsite Property
$10,400
$6,900
$4,300
$4,480
$2,950
$1,830
$378,600
$249,600
$155,800 Total Benefits
$982,700
$711,300
$493,300
$1,198,200
$867,700
$602,000
$7,507,700
$5,413,900
$3,740,200 Occupational Health (Routine)
($9,000)c
($24,000)
($27,000)
($9,000)
($24,000)
($27,000)
($9,000)
($24,000)
($27,000)
Industry Implementation
($15,660,000)
($41,820,000)
($46,770,000)
($15,660,000)
($41,820,000)
($46,770,000)
($15,660,000)
($41,820,000)
($46,770,000)
Industry Operation
($730,000)
($252,000)
($64,000)
($730,000)
($252,000)
($64,000)
($730,000)
($252,000)
($64,000)
NRC Implementation NCb NCb NCb NCb NCb NCb NCb NCb NCb NRC Operation NCb NCb NCb NCb NCb NCb NCb NCb NCb Total Costs
($16,399,000)
($42,096,000)
($46,861,000)
($16,399,000)
($42,096,000)
($46,861,000)
($16,399,000)
($42,096,000)
($46,861,000)
Net Benefit
($15,416,000)
($41,385,000)
($46,368,000)
($15,200,800)
($41,228,300)
($46,259,000)
($8,891,300)
($36,682,100)
($43,120,800) a Discounted net present value (NPV) results are expressed in 2012 dollars. Undiscounted results are expressed in constant dollars.
2 b NC: Not calculated 3
c Negative values are shown using parentheses (e.g., negative $9,000 is displayed as ($9,000)).
4 5
Table H-33 Combined Effect of $4,000 per Person-Rem Conversion Factor and Consequences Beyond 50 Miles for 6
Option 2 7
Attribute Best Estimatea Low Estimatea High Estimatea Undiscounted 3% NPV 7% NPV Undiscounted 3% NPV 7% NPV Undiscounted 3% NPV 7% NPV Public Health (Accident)
$3,566,900
$2,583,800
$1,793,400
$2,162,500
$1,566,500
$1,087,300
$31,471,600
$22,798,200
$15,823,400 Occupational Health (Accident)
$2,500
$1,900
$1,400
$1,300
$1,000
$700
$42,700
$30,900
$21,400 Offsite Property
$2,139,300
$1,549,700
$1,075,600
$4,968,300
$3,599,100
$2,498,000
$11,586,600
$8,393,400
$5,825,500 Onsite Property
$10,400
$6,900
$4,300
$4,680
$3,150
$2,030
$378,600
$249,600
$155,800 Total Benefits
$5,719,100
$4,142,300
$2,874,700
$7,136,800
$5,169,800
$3,588,000
$43,479,500
$31,472,100
$21,826,100 Occupational Health (Routine)
($18,000) c
($49,000)
($54,000)
($18,000)
($49,000)
($54,000)
($18,000)
($49,000)
($54,000)
Industry Implementation
($15,660,000)
($41,820,000)
($46,770,000)
($15,660,000)
($41,820,000)
($46,770,000)
($15,660,000)
($41,820,000)
($46,770,000)
Industry Operation
($730,000)
($252,000)
($64,000)
($730,000)
($252,000)
($64,000)
($730,000)
($252,000)
($64,000)
NRC Implementation NCb NC NC NC NC NC NC NC NC NRC Operation NC NC NC NC NC NC NC NC NC Total Costs
($16,408,000)
($42,121,000)
($46,888,000)
($16,408,000)
($42,121,000)
($46,888,000)
($16,408,000)
($42,121,000)
($46,888,000)
Net Benefit
($10,689,000)
($37,979,000)
($44,013,000)
($9,271,200)
($36,951,200)
($43,300,000)
$27,071,500
($10,648,900)
($25,061,900) 8 9
a Discounted net present value (NPV) results are expressed in 2012 dollars. Undiscounted results are expressed in constant dollars.
b NC: Not calculated c Negative values are shown using parentheses (e.g., negative $18,000 is displayed as ($18,000)).
10 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-128
H-129 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Summary and Conclusion 1
2 Table H-32 shows that requiring the expedited transfer of spent fuel from the SFP to dry cask 3
storage to achieve low-density SFP storage does not achieve a cost-beneficial increase in 4
public health and safety for the reference plant using the current regulatory framework. In 5
addition, three sensitivity analyses (Table H-33) also showed that the regulatory alternative 6
represented by Option 2 was not cost-beneficial for any cases in which costs and benefits 7
incurred in the future were discounted to their present worth using 3 percent and 7 percent 8
discount rates consistent with OMB guidance. Moreover, the staff identified other 9
considerations that would further reduce the quantified benefits, thereby making Option 2 even 10 less justifiable. These other considerations included (1) the costs and risks associated with the 11 handling and movement of spent fuel casks in the reactor building, (2) the post-Fukushima 12 mitigation strategies required under Order EA-12-049 and the reliable SFP instrumentation 13 required under Order EA-12-051, which significantly enhance the likelihood of successful 14 mitigation, and thereby reduce the conditional probability of radiological release, and (3) the 15 possibility of other favorable SFP loading configurations.
16 17 Based on its quantitative cost-benefit analysis, the staff concluded that the added costs involved 18 in expediting the transfer of spent fuel from the SFP to dry cask storage to achieve low-density 19 SFP storage at the reference plant were not warranted. In addition, based on the results of its 20 safety goal evaluation, the staff concluded that this regulatory alternative could not result in a 21 substantial increase in overall protection of public health and safety. Together, these analyses 22 indicated thatfor the reference plantrequiring the expedited transfer of spent fuel from the 23 SFP to dry cask storage to achieve low-density SFP storage was not justified.
24 25 However through its analysis, the staff discovered that an alternative 1x8 high-density fuel 26 configuration may have significantly lower implementation costs and potentially similar benefits 27 to the low-density configuration. The staff therefore recommended that this alternativein 28 addition to other possible SFP loading configurationsbe evaluated further as part of a 29 subsequent regulatory analysis that would be performed to more broadly assess whether any 30 significant safety benefits (or detriments) would occur from requiring expedited spent fuel 31 transfer from SFPs to dry storage casks for the range of SFP designs at existing and new 32 (future) nuclear power plants. In SECY-12-0095, Tier 3 Program Plans and 6-Month Status 33 Update in Response to Lessons Learned from Japans March 11, 2011, Great Tohoku 34 Earthquake and Subsequent Tsunami, dated July 13, 2012, the staff provided a five-step plan 35 to evaluate whether regulatory action is warranted for the expedited transfer of spent fuel from 36 SFPs into dry cask storage. Enclosure H-6 to this appendix summarizes the subsequent 37 regulatory analysis that addresses this issue and that is documented in COMSECY-13-0030.
38 39 Commissions Response to the Staffs Analysis and Recommendations 40 41 The staff provided SECY-13-0112 to the Commission as an information paper instead of a 42 notation vote paper. Therefore, the Commission did not vote on the staffs analysis and its 43 recommendations provided therein. However, after receiving the Tier 3 program plan 44 documented in SECY-12-0095, the Commission directed the staff in several related SRMs.
45 Enclosure H-6 to this appendix summarizes this Commission direction.
46 47
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-130 ENCLOSURE H-6:
SUMMARY
OF DETAILED ANALYSES IN 1
COMSECY-13-0030, ENCLOSURE 1, REGULATORY ANALYSIS FOR 2
JAPAN LESSONS-LEARNED TIER 3 ISSUE ON EXPEDITED 3
TRANSFER OF SPENT FUEL 4
5 This enclosure summarizes the U.S. Nuclear Regulatory Commission (NRC) staffs regulatory 6
analyses of whether expedited transfer of spent fuel to dry cask storage is warranted, as 7
documented in COMSECY-13-0030, Staff Evaluation and Recommendation, Enclosure 1, 8
Regulatory Analysis for Japan Lessons-Learned Tier 3 Issue on Expedited Transfer of Spent 9
Fuel, dated November 12, 2013. These analyses used insights from and expanded upon the 10 staffs previous evaluations described in NUREG-2161, Consequence Study of a 11 Beyond-Design-Basis Earthquake Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water 12 Reactor, issued September 2014, and SECY-13-0112, Enclosure 1, Consequence Study of a 13 Beyond-Design-Basis Earthquake Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water 14 Reactor, dated October 9, 2014, and summarized in Enclosure H-5, Summary of Detailed 15 Analyses for SECY-13-0112 and NUREG-2161, Consequence Study of a Beyond-Design-Basis 16 Earthquake Affecting the Spent Fuel Pool for a U.S. Mark I Boiling-Water Reactor, of this 17 appendix. As such, this enclosure should be considered with the content of Enclosure H-5.
18 Problem Statement and Regulatory Objectives 19 20 The March 11, 2011, Great Thoku earthquake and subsequent tsunami in Japan caused 21 extensive damage to the nuclear reactors at the Fukushima Dai-ichi nuclear power plant.
22 Although the spent fuel pools (SFPs) and spent fuel assemblies remained intact, the event led 23 to questions about the safe storage of spent fuel in SFPs and whether expedited transfer of 24 spent fuel to dry cask storage was necessary. The event also generated increased interest in 25 understanding the consequences of SFP accidents. On March 23, 2011, the NRC, in response 26 to the accident at Fukushima Dai-ichi, on March 23, 2011, the NRC established a Near-Term 27 Task Force (NTTF) to determine whether the NRC should make any near-or long-term 28 improvements to its regulatory system, based on insights obtained from the Fukushima Dai-ichi 29 accident. Nearly 4 months later, the NTTF provided its recommendations for regulatory 30 improvements, including those to enhance SFP safety, in a Task Force Report to the 31 Commission (NRC, 2011b). Around the same time, the NRC Office of Nuclear Regulatory 32 Research initiated a project evaluating the consequences of a beyond-design-basis earthquake 33 affecting an SFP at a Mark I boiling-water reactor in the United States. The results of this study, 34 hereafter referred to as the Spent Fuel Pool Study (SFP study), were later documented in 35 NUREG-2161 and SECY-13-0112, Enclosure 1, and are summarized in Enclosure H-5 of this 36 appendix.
37 38 In accordance with Commission direction, the staff prioritized its recommendations in 39 SECY-11-0137, Prioritization of Recommended Actions to Be Taken in Response to 40 Fukushima Lessons Learned. The staff identified expedited transfer of spent fuel to dry cask 41 storage as an additional issue that was not identified in the Task Force Report but may warrant 42 further consideration. In SECY-12-0025, Proposed Orders and Requests for Information in 43 Response to Lessons Learned from Japans March 11, 2011, Great Thoku Earthquake and 44 Tsunami, dated March 9, 2012, the staff prioritized this issue in the Tier 3 category, since it 45 required further staff study to determine whether it warranted regulatory action. The staff also 46 proposed two orders to the Commission that would increase SFP safety by (1) requiring 47 installation of enhanced SFP instrumentation and (2) developing additional strategies and 48
H-131 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 guidance to mitigate beyond-design-basis phenomena by maintaining or restoring SFP cooling, 1
core cooling, and containment capabilities.
2 3
The Commission approved these orders aimed at improving spent fuel safety:
4 5
- 1)
Order EA-12-049, Order Modifying Licenses with Regard to Requirements for Mitigation 6
Strategies for Beyond-Design-Basis External Events, dated March 12, 2012 7
8 This Order requires licensees to develop, implement, and maintain guidance and 9
strategies to maintain or restore SFP cooling capabilities, independent of alternating 10 current power, following a beyond-design-basis external event.
11 12
- 2)
Order EA-12-051, Issuance of Order to Modify Licenses with Regard to Reliable Spent 13 Fuel Pool Instrumentation, dated March 12, 2012 14 15 This Order requires licensees to install reliable means of remotely monitoring wide-range 16 SFP levels to support effective prioritization of event mitigation and recovery actions in 17 the event of a beyond-design-basis external event.
18 19 In SECY-12-0095, Tier 3 Program Plans and 6-Month Status Update in Response to Lessons 20 Learned from Japans March 11, 2011, Great Tohoku Earthquake and Subsequent Tsunami, 21 dated July 13, 2012, the staff outlined a five-step plan to evaluate the Tier 3 issue of whether 22 regulatory action to expedite the transfer of spent fuel to dry cask storage was needed.
23 24 In a memorandum to the Commission entitled, Updated Schedule and Plans for Japan 25 Lessons-Learned Tier 3 Issue on Expedited Transfer of Spent Fuel, dated May 7, 2017, the 26 staff provided a shortened three-phase plan for resolving the Tier 3 Issue on expedited transfer 27 of spent fuel. The first phase of the plan was to conduct a regulatory analysis, leveraging 28 results and insights from the ongoing SFP study, to determine whether a substantial increase in 29 public health and safety can be achieved through an expedited transfer to dry storage casks.
30 Then, if the results of the regulatory analysis indicated that it warranted additional study, the 31 staff would proceed to Phases 2 and 3 of the plan and perform more detailed analyses using 32 refined assumptions to confirm the need for regulatory action. The staff provided its findings 33 from the Phase 1 study to the Commission in COMSECY-13-0030, which are summarized 34 below.
35 36 Regulatory Alternatives 37 38 The staff considered two regulatory alternatives in its analysis:
39 40 Option 1: Maintain the existing spent fuel storage requirements (regulatory baseline).
41 This option, hereafter referred to as the regulatory baseline, refers to the case in which 42 the Commission opts to continue with the existing licensing requirements for spent fuel 43 storage rather than require the expedited transfer of spent fuel from SFPs to dry storage.
44 The existing regulations require that spent fuel, which is stored in SFPs in high-density 45 racks, be moved from SFPs into dry cask storage only when necessary to accommodate 46 spent fuel being offloaded from the core. In addition, the SFP must always allocate 47 enough space to accommodate at least one full core of reactor fuel in case of 48 emergencies or other operational contingencies. The regulatory baseline assumed that 49 all applicable requirements and guidance to date have been implemented, but it 50 assumed no implementation for any related generic issues or other staff requirements or 51
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-132 guidance that were unresolved or still under review. For the regulatory analysis, the 1
baseline condition assumed that spent fuel was stored in high-density racks in a 2
relatively full SFP, and that there was full compliance with all regulatory requirements, 3
including those outlined in Title 10 of the Code of Federal Regulations (10 CFR) 4 50.54(hh)(2) with respect to spent fuel configuration and SFP preventive and mitigative 5
capabilities. To increase conservatism in the analysis, for the regulatory baseline it was 6
assumed that there was no successful mitigation of the SFP accident. In addition, 7
because SFPs are relatively full even after using high-density storage racks, the current 8
practice of transferring spent fuel to dry storage in accordance with 10 CFR Part 72, 9
Licensing Requirements for the Independent Storage of Spent Nuclear Fuel, High-Level 10 Radioactive Waste, and Reactor-Related Greater Than Class C Waste, is assumed to 11 continue. Lastly, although the it was assumed that licensees had implemented the 12 requirements of Order EA-12-049 and Order EA-12-051 to enhance their ability to 13 respond to beyond-design-basis events, the staffs evaluation did not quantitatively 14 consider the capabilities implemented to satisfy these requirements. The regulatory 15 baseline represents the status quo against which the second alternative is compared.
16 17 Option 2: Expedite the transfer of spent fuel from SFPs to dry cask storage (low-density 18 SFP). For this alternative, spent fuel assemblies that have been cooled in the SFP for at 19 least 5 years after discharge would be expeditiously moved from the SFP to dry cask 20 storage beginning in 2014 to achieve and maintain low-density loading of spent fuel in 21 the existing high-density racks. For this option, the SFP would have a lower long-lived 22 radionuclide inventory, a lower overall heat load, and a slightly higher water inventory 23 because of the removed spent fuel assemblies. On the other hand, loading, handling, 24 and moving casks to achieve this configuration increase the cost and risk impacts 25 associated with this alternative. Therefore, to maximize the delta benefit of this 26 alternative relative to the status quo (i.e., Option 1), the staffs analysis conservatively 27 did not include these additional costs and risks associated with transferring and handling 28 casks in their analyses. The staff also assumed that mitigative actions in accordance 29 with 10 CFR 50.54(hh)(2) were successful to further increase the regulatory benefit of 30 this alternative, and, similar to Option 1, did not quantitatively consider the requirements 31 of Order EA-12-049 and Order EA-12-051 in the evaluation.
32 33 Safety Goal Evaluation 34 35 As part of its two-part regulatory analysis, the staff performed a safety goal screening evaluation 36 to determine whether requiring the expedited transfer of spent fuel to dry cask storage would 37 provide a significant safety benefit compared to the regulatory baseline, regardless of whether 38 the action would be cost-beneficial. The staff performed the safety goal screening evaluation by 39 comparing the calculated risks to the public from the severe accidents at the plants considered 40 in this study to the two quantitative health objectives (QHOs) for average individual prompt 41 fatalities and average individual latent cancer fatalities, as outlined in the NRCs Safety Goals 42 Policy Statement (NRC, 1986). These QHOs, which are subsequently used to determine 43 whether the NRCs safety goals are met, are as follows:
44 45 (1)
The risk to an average individual near a nuclear power plant of prompt fatalities that 46 might result from reactor accidents should not exceed 1/10 of 1 percent (0.1 percent) of 47 the sum of prompt fatality risks resulting from other accidents to which members of the 48 U.S. population are generally exposed.
49 50
H-133 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 (2)
The risk to the population in the area near a nuclear power plant of cancer fatalities that 1
might result from nuclear power plant operation should not exceed 1/10 of 1 percent 2
(0.1 percent) of the sum of cancer fatality risks resulting from all other causes.
3 4
For an average individual within 1.6 kilometers (1 mile), the prompt fatality QHO is 5
5x10-7 per year as estimated in NUREG-0880, Revision 1, Safety Goals for Nuclear Power 6
Plant Operation, issued May 1983. The staffs analysis for expedited transfer of spent fuel 7
showed that there are no offsite early fatalities from acute radiation effects, despite the large 8
releases for some low-probability accident progressions analyzed.
9 10 The cancer fatality QHO listed in NUREG-0880, Revision 1, is 2x10-6 per year for an average 11 individual living within 16 kilometers (10 miles) of a nuclear power plant site. The staff 12 calculated an updated QHO value for comparison, using the most up-to-date estimate of the 13 number of cancer fatalities and the total U.S. population at the time, which yielded a risk of 14 1.84x10-3 per year. One-tenth of 1 percent of this value results in a QHO of 1.84x10-6 per year, 15 which is lower than the value listed in NUREG-0880.
16 17 The staff determined the risk of latent cancer fatalities to a population living near a nuclear 18 power plant by multiplying the bounding frequency of damage to spent fuel (3.46x10-5 per year) 19 with the estimate from the SFP study for conditional individual latent cancer fatality risk within a 20 16-kilometer (10-mile) radius (4.4x10-4 per year). This yielded a conservative high estimate of 21 individual latent cancer fatality risk of 1.52x10-8 cancer fatalities per year for an SFP accident, 22 which is less than one percent of the 1.84x10-6 per year QHO calculated above.
23 24 The staff noted three important limitations to the above evaluation:
25 26 (1)
The safety goals outlined in the Safety Goal Policy Statement are intended to 27 encompass all accident scenarios at a nuclear power plant site, while this analysis only 28 considered initiating events that challenge the integrity or cooling of the SFP, which are 29 the most important contributors to SFP risk.
30 31 (2)
Although an SFP accident might affect larger areas and more people than a reactor 32 accident, protective actions, such as relocation of the public, would result in the risks to 33 individuals beyond 16 kilometers (10 miles) being similar to the risk to individuals located 34 closer to the plant.
35 36 (3)
The total or cumulative radiation dose to the population might be higher for an SFP 37 accident than for a reactor accident, even though the risk to individuals living near or far 38 from the plant remains below the QHOs.
39 40 Based on these results, the staff concluded that the continued use of high-density loadings in 41 SFPs at nuclear power plants does not challenge the NRCs safety goals. Expediting transfer of 42 spent fuel into dry cask storage would provide no more than a minor safety improvement.
43 44
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-134 Technical Evaluation 1
2 Description of Representative Plants 3
4 The staff organized U.S. SFPs into seven groups based on spent fuel configuration, rack 5
designs, and SFP capacities, as shown in Table H-34.
6 7
Table H-34 SFP Groupings Used for the Staff's Technical and Cost-Benefit Analyses 8
SFP Group No.
Description No. of Reactor Units No. of SFPs Average Year When Reactor Operating License Expires 1
Boiling-water reactors (BWRs) with Mark I and Mark II containments and with nonshared SFPs 31 31 2037 2
Pressurized-water reactors (PWRs) and BWRs with Mark III containments with nonshared SFPs 49 49 2040 3
AP1000 SFPs 4
4 2078 4
Reactor units with shared SFPs 20 10 2038 5
SFPs located below grade1 (these are included in group 2) 6 Decommissioned plants with spent fuel stored in pool2,3 7
6 N/A 7
Decommissioned plants with fuel stored in an ISFSI using dry casks 21 N/A N/A
- 1. Group 5 is a special set of currently operating PWRs for which damage to the pool structure would not result in a rapid loss of water inventory.
2 The Zion 1 and 2 decommissioned reactor units share a single SFP.
3 Group 6 includes the GE-Hitachi Morris wet independent spent fuel storage installation (ISFSI) site.
9 The technical evaluations discussed in this section and the cost-benefit analyses focused on 10 Group 1 through Group 4 in Table H-34; the analyses excluded Group 5 through Group 7 for the 11 following reasons:
12 13 Group 5 SFPs are less susceptible to the formation of small or medium leaks because 14 there is no open space around the pool liner and concrete structure.
15 16 Group 6 SFPs are no longer receiving spent fuel discharged from the reactor following 17 decommissioning, and several plants had extended plant outages before announcing 18 cessation of plant operation.
19 20 The spent fuel in Group 7 is already in dry cask storage.
21 22 The analyses also included operational strategies such as those used to expand onsite storage.
23 24 Spent Fuel Pool Accident Modeling 25 26 The analyses described relied heavily on the models and data used in the SFP study.
27 NUREG-2161 and SECY-13-0112, Enclosure 1, provide more detailed information about the 28 models developed for the SFP study. This subsection focuses on the most relevant technical 29 information that will enable comprehension of the cost-benefit analyses described in the next 30 section.
31 32
H-135 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Seismic Hazard Model and Characterization of Seismic Event Likelihood 1
2 The analyses used the 2008 U.S. Geological Survey seismic hazard model that was available at 3
the time (and used for the SFP study) to evaluate seismic hazards at central and eastern 4
U.S. nuclear plants. Although this model considered hazards at western U.S. sites (e.g., Diablo 5
Canyon), the accident analyses did not include western sites because they were not addressed 6
in Generic Issue 199,35 which only focused on central and eastern U.S. sites. Using peak 7
ground acceleration and hazard exceedance frequency data from the U.S. Geological Survey, 8
the staff determined that the hazard exceedance frequency curves of the Peach Bottom Atomic 9
Power Station (Peach Bottom), the reference plant used for the SFP study, bound those of 10 reactors in SFP Group 1 through Group 4 over a wide peak ground acceleration range.
11 12 To translate hazard exceedance frequencies into seismic initiating event frequencies, the staff 13 also partitioned the peak ground acceleration ranges for Peach Bottom and for sites in SFP 14 Group 1 through Group 4 into four discrete bins. Since the SFP study demonstrated that 15 damage to the SFP and other related structures was not credible for seismic bins 1 and 2, the 16 staff only used seismic initiator event frequencies from bins 3 and 4 of each SFP group (and 17 Peach Bottom). Specifically, the analyses used seismic initiating event frequencies from bins 3 18 (1.7x10-5 per year) and 4 (4.9x10-6 per year) for Peach Bottom for both the low-and base-case 19 analyses because these hazard exceedance frequencies bound most of the other reactor sites.
20 To account for some reactor site hazard exceedance frequencies exceeded those of Peach 21 Bottom for bins 3 and 4, for each SFP group, the analyses used the site with the largest plant 22 exceedance frequencies in bins 3 and 4 to generate high-estimate seismic initiating event 23 frequencies for subsequent sensitivity analyses (see Table H-35).
24 25 Consequence Analyses 26 27 The MELCOR Accident Consequence Code System (MACCS36) code was used to model 28 atmospheric transport and dispersion, emergency response, and long-term consequences. The 29 atmospheric transport and dispersion model used for these analyses was based on the Peach 30 Bottom MACCS results described in the SFP study. The MACCS model for Peach Bottom used 31 a straight-line Gaussian plume segment model. For both the SFP study and this study, the 32 atmospheric release of radionuclides was discretized into up to 1-hour plume segments to 33 account for variations in the release rate and the changes in wind direction. Meteorological data 34 used for the MACCS analyses consisted of 1 year of hourly meteorological data (i.e., 8,760 data 35 points for each meteorological parameter) for Peach Bottom evaluated in the SFP study. The 36 specific year of meteorological data chosen for Peach Bottom was 2006, and stability class data 37 were derived from temperature measurements at two elevations on the site meteorological 38 towers.
39 40 The study used population densities and site distribution characteristics for SFPs in the United 41 States to generate the site population and economic data required for MACCS and cost-benefit 42 analyses. The SFP sites were binned based on average population densities within 43 80 kilometers (50 miles) of the sites, and representative sites were selected to represent various 44 population densities. Peach Bottom, Surry Power Station, Palisades Nuclear Plant, and Point 45 Beach Nuclear Plant represented population densities in the 90th percentile, the mean, the 46 35 https://www.nrc.gov/about-nrc/regulatory/gen-issues/dashboard.html#genericIssue/genericIssueDetails/3 36 At the time of this analysis, the MACCS code was called the MACCS2 code, a leftover notation from the time that the original MACCS code was substantially upgraded to Version 2. Since then, the staff has referred to the code as the MACCS code and notes the version number of the code used in a particular analysis since code development and maintenance continues.
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-136 median, and the 20th percentiles, respectively. For each representative site, site population and 1
economic data were created for 16 compass sectors and interpolated onto a 64-compass sector 2
grid for better spatial resolution for consequence analyses. The staff escalated 2000 census 3
data and 2002 economic data to 2011 values.
4 5
Population densities and distributions near SFP locations representing the 90th, mean, median, 6
and 20th percentiles were used for respective high-, base-, median-, and low-estimate 7
sensitivity studies of site population demographics. The study used these data as additional 8
inputs into MACCS calculations to assess the effect of population density on the averted public 9
health (accident) attribute. Since an SFP fire could affect public health consequences beyond 10 80 kilometers (50 miles), sensitivity analyses were also conducted using base-case 11 assumptions and the standard value ($2,000 per person-rem), along with a sensitivity value 12
($4,000 per person-rem) for the person-rem conversion factor. The study used the $4,000 per 13 person-rem sensitivity value because the staff was reassessing the dollar per person-rem factor 14 at the time as part of its efforts to update NUREG-1530, Reassessment of NRCs Dollar Per 15 Person-Rem Conversion Factor Policy, issued December 1995, and Revision 1, issued 16 August 2015 (NRC, 1995b; NRC, 2017b).
17 18 The study evaluated the relationship between population densities, distribution characteristics, 19 and offsite property values near SFP sites by conducting sensitivity analyses in which the site 20 population densities and distributions were varied. The site populations, distributions, and 21 economic data for the high-, base-, median-, and low-estimate cases described above served 22 as additional input into the MACCS calculations that otherwise used values specific to the 23 reference plant. The staff also evaluated the impact on offsite property costs as a result of 24 extending offsite consequences beyond 80 kilometers (50 miles). In this case, the base-case 25 assumptions and the intermediate protective action guidelines criterion were used, as explained 26 below.
27 28 The SFP study used the emergency response model in MACCS to model doses, health effects, 29 and emergency response during the 7-day period following the start of a release during a 30 severe accident. The long-term phase, which is the period following the 7-day emergency 31 phase, was modeled for 50 years to calculate consequences from exposure of an average 32 person. The habitability criterion used in MACCS, to determine whether land is inhabitable after 33 decontamination, was 2 rem in the first year and 500 millirem (mrem) each year thereafter for 34 the base-case evaluations. This criterion was based on the U.S. Environmental Protection 35 Agencys protective action guidelines as outlined in EPA-400/R-17/001, PAG Manual:
36 Protective Action Guides and Planning Guidance for Radiological Incidents, issued 37 January 2017 (EPA, 2017). However, for habitability, some States (e.g., Pennsylvania) have 38 adopted a habitability criterion of 500 mrem annually. To account for the uncertainties in the 39 way in which States define their habitability criteria, the staff also performed sensitivity studies in 40 which the low estimate case used 500 mrem per year, while the high-estimate case used a 41 conservative 2 rem per year.
42 43 Cost-Benefit Analysis 44 45 A cost-benefit analysis informed the Commissions decision whether to expedite spent fuel 46 transfer to dry cask storage. This analysis was more expansive than that performed for the SFP 47 study, as it evaluated SFP configurations at all U.S. nuclear power plants and it incorporated 48 insights from the SFP study and other previous studies, where possible.
49
H-137 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Methodology 1
2 The staff first identified the attributes that would be impacted by expedited fuel transfer and 3
performed quantitative and qualitative analyses on those attributes, including public health 4
(accident) and occupational health (routine and accident), onsite property, offsite property, 5
industry implementation and operational activities, and NRC implementation and operational 6
activities. The analysis did not include the NRCs implementation and operational activity costs; 7
this simplification is acceptable because it is consistent with the approach to maximize the 8
benefit of the alternative.
9 10 The staff determined the costs and benefits associated with each attribute for each alternative, 11 converting them into monetary values where practicable and discounting them to a net present 12 value. Specifically, the staff used a constant 7 percent discount rate as a base-case value and 13 used 3 percent as a sensitivity value to approximate the real rate of return on long-term 14 government debt, which is a proxy for the real rate of return on savings. In addition, the Office 15 of Management and Budget (OMB) Circular No. A-4, Regulatory Analysis, dated 16 September 17, 2003, suggests using a lower but positive discount rate, in addition to the 17 discount rates of 3 percent and 7 percent, if the decisionmaking will have important 18 intergenerational benefits. Therefore, for this study, the staff included a 2 percent discount rate 19 to represent the lower bound for the certainty-equivalency rate in 100 years. The staff analyzed 20 the total discounted quantitative costs and benefits for each alternative to determine whether 21 there was a positive benefit for expedited transfer. The staff also considered qualitative costs 22 and benefits in assessing whether there was a positive benefit.
23 24 The staff performed a sensitivity analysis to identify key input parameters that have the greatest 25 impact on the results. Starting with the parameters for the base case, it varied the input 26 parameters to generate low-and high-estimates that it compared with the base-case results to 27 determine the sensitivity of the results to the input parameter. The results of these analyses 28 indicated that, in addition to discount values used for present value calculations, dollar 29 per person-rem conversion factors, calculated consequences from the site, habitability criteria, 30 and seismic initiator frequency were also key input parameters that strongly affected the net 31 results. Table H-35 summarizes the base-case and sensitivity values used for the key input 32 parameters.
33 34 Table H-35 Key Input Parameters Used for Sensitivity Analyses 35 Input Parameter Methodology Base Case Value Sensitivity Value(s)
Net Present Value (NPV) 7% NPV 2 and 3% NPV Dollar per person-rem Conversion Factor
$2,000
$4,000 Calculated Consequences from Site 50 miles Beyond 50 miles Habitability Criteria 2 rem in the first year and 500 mrem each year thereafter 500 mrem per year and 2 rem per year Seismic Initiator Frequencya Bin 3: 1.65x10-5 per year Bin 4: 4.90x10-6 per year Bin 3: 2.24x10-5-5.64x10-5 per year Bin 4: 7.09x10-6-2.00x10-5 per year a As discussed in the SFP study, damage to the SFP and other relevant structures, systems, and components is 36 not credible for events in bins 1 and 2.
37 38
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-138 The staff made its recommendation on the implementation of each alternative based on 1
qualitative attributes, uncertainties, sensitivities, and the quantified costs and benefits taken 2
from quantitative attributes. If the quantified and qualified benefits were greater than the 3
quantified and qualified costs, then the staff recommended the alternative be implemented.
4 Otherwise, the staff recommended that the alternative not be implemented.
5 6
Cost-Benefit Analysis Results 7
8 Table H-36 summarizes the net benefits (i.e., the sum of total benefits and total costs) for each 9
SFP group. The table includes the corresponding values obtained from additional sensitivity 10 analyses in which the discount rate of 7 percent, which the NRC uses for regulatory 11 decisionmaking, was varied to 2 percent and 3 percent in accordance with the 12 recommendations in OMB Circular A-4. In addition to the conservative assumptions used to 13 generate the base-case values, low-and high-estimates are provided that combine the range of 14 expected SFP attributes to model the range of pool accidents postulated.
15 16 Table H-36 Summary of Net Benefits for Each Spent Fuel Pool Group*
17 SFP Group No.
Low Estimate (2012 million dollars)
Base Case (2012 million dollars)
High Estimate (2012 million dollars) 2% NPV 3% NPV 7% NPV 7% NPV 2% NPV 3% NPV 7% NPV 1
($53)**
($55)
($52)
($45)
$70
$54
$21 2
($51)
($54)
($51)
($45)
$86
$67
$26 3
($42)
($36)
($17)
($12)
$66
$45
$17 4
($49)
($50)
($49)
($39)
$160
$130
$74
- Note: The values listed in COMSECY-13-0030, Enclosure 1, have been rounded to two significant figures here.
18
- Negative values are shown using parentheses (e.g., negative $53 is displayed as ($53)).
19 20 Attributes that led to net costs for SFP Group 1 through Group 4 are industry implementation 21 and occupational health (routine) costs, with implementation costs far surpassing routine 22 occupational health costs. For Group 1, Group 2, and Group 4, these costs are dominated by 23 the additional capital costs for the dry storage containers (DSCs) and loading costs for the 24 storage systems to achieve low-density storage in the SFP above that required for the 25 regulatory baseline. Since the spent fuel stored in Group 3 SFPs is not expected to require dry 26 storage until 2038, additional costs beyond the DSC capital costs and loading costs include 27 ISFSI annual operation and maintenance costs required to establish the ISFSI and store spent 28 fuel there 15 years earlier than in the regulatory baseline.
29 30 Positive attributes (i.e., benefits and cost offsets) that offset the net costs described above are 31 public health (accident), occupational health (accident), offsite property, and onsite property.
32 For all groups, the offsite property cost offset is the largest contributor to the benefits, the 33 majority of which occur during the long-term phase. However, as Table H-37 illustrates, these 34 benefits and cost offsets do not create a positive net benefit for low-, high-, or 35 base-case-estimates with any of the discount rates applied.
36 37 The staff performed sensitivity analyses to provide additional consideration for the safety goal 38 screening evaluation. Table H-37 summarizes the results of the sensitivity analyses considering 39 the combined effects of adjusting the dollar per person-rem conversion factor from $2,000 to 40
$4,000 and of extending consequence analyses beyond 80 kilometers (50 miles) from the site.
41 42
H-139 NUREG/BR-0058, Rev. 5, App. H, Rev. 0 Table H-37 Net Benefits for Low-Density SFP Storage for Groups 1-4 from Combined 1
Sensitivity Analyses that Analyzed Consequences Beyond 80 kilometers (50 2
Miles) and Using an Adjusted Dollar per Person-Rem Conversion Factor 3
SFP Group No.
Low Estimate (2012 million dollars)*
Base Case (2012 million dollars)*
High Estimate (2012 million dollars)*
2% NPV 3% NPV 7% NPV 2% NPV 3% NPV 7% NPV 2% NPV 3% NPV 7% NPV 1
($51)**
($54)
($51)
$9.5
$0.17
($15)
$880
$779
$506 2
($48)
($51)
($49)
$19
$7.7
($12)
$1,100
$916
$569 3
($39)
($33)
($16)
$32
$21
$6.8
$749
$563
$233 4
($45)
($47)
($44)
$40
$28
$5.8
$1,900
$1,600
$1,100
- Note: the original values for this analysis listed in COMSECY-13-0030, Enclosure 1, have been rounded to two 4
significant figures.
5
- Negative values are shown using parentheses (e.g., negative $51 is displayed as ($51)).
6 7
The sensitivity results provided in Table H-37 show that there are cases using conservative 8
assumptions for each SFP group in which the low-density spent fuel storage alternative was 9
cost-justified. However, after considering the analysis results, operating history, and limited 10 safety benefits of possible plant changes, the staff concluded that further study would be 11 unlikely to support future actions requiring expedited transfer.
12 13 Summary and Conclusion 14 15 The staff performed a regulatory analysis that included all U.S. SFPs to determine whether 16 expedited transfer of spent fuel from SFPs to dry cask storage was warranted. As part of the 17 regulatory analysis, the staff conducted a technical evaluation using insights from recently 18 completed SFPs, a safety goal screening evaluation, and a cost-benefit analysis. The results of 19 the technical evaluation of the consequences of seismic events impacting four different 20 categories of SFPs indicated that no offsite fatalities were expected to occur, similar to the 21 results obtained from the SFP study and other studies, and that the predicted long-term 22 exposure of the population, which could result in latent cancer fatalities, was low.
23 24 The safety goal screening evaluation revealed that SFP accidents are a small contributor to the 25 overall risks for public health and safety (less than 1 percent of the QHOs), and therefore any 26 reductions in risk associated with expedited transfer of spent fuel only would have a marginal 27 safety benefit. In addition, the cost-benefit analysis demonstrated that the added costs of 28 expediting transfer of spent fuel to dry cask storage were not warranted considering the 29 marginal safety benefits that would result. As part of the analysis, the staff identified attributes 30 affected by expedited transfer and analyzed them quantitatively and qualitatively, where 31 possible. When considering the discount rates combined with very conservative SFP 32 assumptions, the costs of implementing expedited transfer greatly outweighed the benefits of 33 doing so. However, the combination of high estimates for important parameters used in 34 subsequent sensitivity analyses resulted in large economic consequences, such that the 35 calculated benefits from expedited transfer of spent fuel to dry cask storage for those cases 36 outweighed the associated costs. For those cases, the staff concluded that there was only a 37 marginal safety improvement in terms of public health and safety, asserting that the 38 assumptions made in the analyses were selected in a generally conservative manner such that 39 the base case is the primary basis for the staffs recommendation.
40 41 Based on the analyses presented in COMSECY-13-0030, the staff concluded that additional 42 studies were not needed to reasonably conclude that the expedited transfer of spent fuel to dry 43
NUREG/BR-0058, Rev. 5, App. H, Rev. 0 H-140 cask storage would provide only a marginal increase in the overall protection of public health 1
and safety. The staff also informed the Commission that it recommended no further regulatory 2
action for the resolution of this Tier 3 issue.
3 4
Staff Non-concurrence 5
6 In accordance with Management Directive 10.158, NRC Non-Concurrence Process, dated 7
March 14, 2014, a member of the NRC technical staff submitted a non-concurrence on 8
COMSECY-13-0030. Enclosure 2 to COMSECY-13-0030 provides documentation associated 9
with this non-concurrence.
10 11 The non-concurrence raised several issues with the detailed analyses performed in support of 12 COMSECY-13-0030, including (1) other potentially cost-beneficial approaches to improving the 13 safety of SFPs should have been evaluated, in addition to Option 2, (2) the base case analysis 14 should have used different assumptions for factors that were ultimately evaluated only as 15 sensitivity analyses (e.g., the dollar per person-rem conversation factor, the region over which 16 offsite radiological consequences are aggregated), (3) the staff should acknowledge the 17 limitations of using safety goals and QHOs that were developed for reactor accidents to 18 determine whether a proposed regulatory action pertaining to SFP safety would constitute a 19 substantial safety enhancement, and (4) the presentation of results should have provided a 20 more balanced and neutral view of the range of findings that were obtained by using the 21 high-estimate cases and sensitivity analyses.
22 23 The staff made several improvements to COMSECY-13-0030 in response to the concerns 24 raised in the non-concurrence. However, after considering the analysis results, operating 25 history, and limited safety benefits of possible plant changes, the staff ultimately concluded that 26 additional studies would be unlikely to support a requirement to expedite transfer of spent fuel 27 from SFP storage to dry cask storage to achieve a low-density SFP loading configuration.
28 29 Commissions Response to the Staffs Analysis and Recommendations 30 31 In the staff requirements memorandum for Staff Requirements Memoranda 32 (SRM)-COMSECY-13-0030, dated May 23, 2014, Staff Evaluation and Recommendation for 33 Japan Lessons-Learned Tier 3 Issue on Expedited Transfer of Spent Fuel, the Commission 34 approved the staff's recommendation that the Tier 3 Japan lessons-learned activities for 35 expedited transfer be closed, and that no further generic assessments be conducted. The 36 Commission also directed the staff to perform several other related activities for completeness 37 and closure of the Tier 3 issue, including modifying the regulatory analysis provided in 38 COMSECY-13-0030 to explain why the 1x8 configuration would not provide a substantial 39 increase in safety. The staff addressed the above issues in SECY-15-0059, Seventh 6-Month 40 Status Update on Response to Lessons Learned from Japans March 11, 2011, Great Tohoku 41 Earthquake and Subsequent Tsunami, Enclosure 3, dated April 9, 2015 (NRC, 2015e).
42