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{{#Wiki_filter:PRA and Risk-Informed Decision Making NRC at  thePerspective NRC: Someon                    Nuclear Trends          andSafetyChallenges*
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Nathan Siu Senior Technical Advisor for PRA Office of Nuclear Regulatory Research July 27, 2020 14:00-14:45
              *The views expressed in this presentation are not necessarily those of the U.S. Nuclear Regulatory Commission
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Acknowledgments Thanks to J. DeJesus, C. Hunter and S. Mehta for their technical support, to J. Xing and J. Chang for their linguistic support, and to S. Weerakkody for his useful suggestions.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School 2
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Table of Contents
* Use of risk information at NRC
* Trends and PRA/RIDM challenges
* Thoughts on MeV
* Closing remarks, knowledge check, essay problems
* Additional slides
  - NRC background
  - Example NRC uses of risk information
  - Potential benefits of MeV advances 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 3
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 It is of the highest importance in the art of decision making to be able to recognize, out of a number of facts, which are incidental and which vital. Otherwise your energy and attention must be dissipated instead of concentrated.
                                          - With apologies to Sherlock Holmes (The Hound of the Baskervilles)
NRC USE OF RISK INFORMATION 11th Annual Modeling, Experimentation and Validation (MeV) Summer School        4
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Use of risk information Triplet Definition of Risk (Kaplan and Garrick, 1981)*
Risk  { i ,                                                                                              Features i,            i}
* Vector, not scalar
* What can go wrong?
* Qualitative and quantitative
* What are the consequences?
* Differences
* How likely is it?                                                                                    across accident spectrum
  *See:
    - White Paper on Risk-Informed and Performance-Based Regulation (Revised), SRM to SECY-98-144, March 1, 1999
    - Glossary of Risk-Related Terms in Support of Risk-Informed Decisionmaking, NUREG-2122, May 2013
    - Probabilistic Risk Assessment and Regulatory Decisionmaking: Some Frequently Asked Questions, NUREG-2201, September 2016 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                    5
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Use of risk information                                                                            Revised Reactor Oversight A PRA/RIDM Timeline                                                                        RG 1.174 Safety Atomic Energy Act                                    Goal              PRA              ASME/ANS No undue risk                                      Policy            Policy            PRA Standard Price-Anderson                            Indian                              IPE/ Modern (non-zero risk)                            Point                              IPEEE Applications UKAEA SGHWR Farmer                                    Expansion Curve                German Risk Study                                    EU Stress Tests WASH-740 Early WASH-1400                  NUREG-1150                            Level 3 PRA PRAs Windscale                            TMI          Chernobyl                              Fukushima Hanford to AEC          WASH-1400                  NRC created                                  created 1940          1950      1960            1970              1980              1990            2000        2010        2020 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                            6
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Use of risk information NRC Uses of Risk Information PRA Policy Statement (1995)
Regulations
* Increase use of PRA technology in and all regulatory matters Guidance
                                                                                - Consistent with PRA state-of-the-art
                                                                                - Complement deterministic approach, Licensing                              support defense-in-depth philosophy Operational        Decision and Experience          Support Certification
* Benefits:
(1) Considers broader set of potential challenges (2) Helps prioritize challenges Oversight (3) Considers broader set of defenses USNRC, Use of Probabilistic Risk Assessment Methods in Nuclear Activities; Final Policy Statement, Federal Register, 60, p. 42622 (60 FR 42622), August 16, 1995.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                    7
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Use of risk information Risk-Informed Decisionmaking (RIDM) a philosophy whereby risk insights are considered Defense-in-                                                    together with other factors to Current              depth                          Safety                        establish requirements that regulations                                          margins                        better RecentfocusApplication licensee and(2019) regulatory attention on design Integrated                                                        In operational and  any licensing issues review or other regulatory decision, commensurate                thetheir with    staff should Decision                                                        apply risk-informed principles when Making                                                        importance          to public health strict, prescriptive application of and    safety. [Emphases deterministic      criteria such as  added]
the single failure criterion is unnecessary Monitoring                                              Risk                      White    Paperfor to provide      onreasonable Risk-Informed        and of assurance Performance-Based adequate protection      Regulation, of public health Adapted from RG 1.174                                                                SECY-98-144, and safety.      January    22, 1998.
Staff Requirements - SECY-19-0036 -
Application of the Single Failure Criterion to NuScale Power LLCs Inadvertent Actuation Block Valves, SRM-SECY-19-0036, July 2, 2019.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                        8
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Use of risk information In Addition to Immediate Decision Support Adapted from NUREG-2150 Risk Information
* Results
* Insights
* Explanations
* Uncertainties
* Qualifications 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                        9
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Its tough to make predictions, especially about the future.
                                                                                        - Yogi Berra SOME TRENDS AND CHALLENGES 11th Annual Modeling, Experimentation and Validation (MeV) Summer School              10
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and challenges Drive to RIDM: Transformation Evolving situation: market forces, new nuclear technologies, new analytical methods and data, new professionals
* Vision: make safe use of nuclear technology possible
* Continuing standard: reasonable assurance of adequate protection
* Attitude: recognize potentially different ways of achievement - embrace change Applying the Principles of Good Regulation as a Risk-Informed Regulator, October 15, 2019 (ADAMS ML19260E683) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 11
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and challenges Market Forces Operating Rx - More use of PRA models                                              New Rx - Early use of PRA in design Risk-Informed LARS Received*
50 Miscellaneous 40 Risk Insights TMRE Number 30                                  Fire Seismic GSI-191 20 EPU 50.69 10                                  TSTF-XXX RI TS Comp Time RI-ISI 0
ILRT FY-17 FY-18 FY-19 FY-20 Fiscal Year
                                              *As of June 8, 2020 "Risk-Informed Performance-Based Technology-Inclusive Guidance for Non-Light Water Reactors," NEI 18-04, Rev. 1, August 29, 2019.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                      12
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and challenges New Technologies
* New designs
* Smart reactor systems
* New operational concepts
* Improved analysis tools Im worried about the mission, Dave.
Cmon HAL, open the pod bay door Photo courtesy of NEA Halden Reactor Project 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                  13
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and challenges New Professionals Changing
* Experiences, knowledge
* Information content and delivery preferences
* Comfort with analytics, risk, probability
* Mobility Adapted from: https://www.nrc.gov/reading-rm/doc-collections/commission/slides/2019/20190618/staff-20190618.pdf 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                            14
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and challenges Trends and Impacts: A Two-Way Street Decision Making
* Issue Identification
* Option Identification Trends
* Analysis
* Increasing # RI-applications
* Deliberation
* New licensing approaches
* Implementation
* Monitoring
* New designs
* New operational concepts
* New technologies PRA Technology
* New analytical methods
* Methods
* New professionals
* Models
    *
* Tools
* Data 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                15
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 SOME RISK-ORIENTED                                                Many calculations bring THOUGHTS ON MeV                                                    success; few calculations bring failure. No calculations at all spell disaster!
                                                                                - Sun-Tzu (The Art of War) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 16
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Thoughts on MeV A PRA Perspective on MeV What: System of Systems                                  Why: Decision Support Adapted from NUREG-2150 mod*el, n. a representation of reality created with a specific objective in mind.
A. Mosleh, N. Siu, C. Smidts, and C. Lui, Model Uncertainty: Its Characterization and Quantification, Center for Reliability Engineering, University of Maryland, College Park, MD, 1995. (Also NUREG/CP-0138, 1994) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                    17
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Thoughts on MeV Potential Benefits of Improved MeV
* Improved realism
      - Finer resolution
      - Fewer simplifications
      - Address sources of completeness/model uncertainty
* Improved decision support
      - Improved insights (not just the numbers)
      - Better use of available information
* Broader stakeholder acceptance
      - Facilitated integration of disciplines
      - Consistency with current engineering trends 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 18
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Thoughts on MeV Some General Challenges*
* Trustworthiness
              - breadth/completeness
              - integration and balance
              - uncertainty characterization**
              - good enough
* Transparency
* Explainability
              - complexity
              - uncertainties**
* Building on framework of Artificial Intelligence/Machine Learning (AI/ML) community:
see Idaho National Engineering Laboratory AI/ML Symposium 2.0, July 9, 2020.
  **See ML20080N774 for additional thoughts on the characterization and communication of uncertainties.                                                                                  https://earthquake.usgs.gov/earthquakes/eventpage/official201103 11054624120_30/shakemap/intensity 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                      19
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Thoughts on MeV A Matter of Perspective Developer                                                                              Decision Maker
* Method/model/tool
* Results (including user effect)
* Validity
* Acceptability (for intended use)
* Best-Estimate [Plus Uncertainty]
* Community state-of-knowledge 1.0 Human Error Probability 1E-1 Hurricane Andrew 8/22/1992, 1200 UTC (about 2 days before FL landfall)                                            1E-2 1E-3 1E-4 Adapted from NUREG-2156 90W            85W            80W            75W              70W            65W          60W                                    1E-5 Adapted from University of Wisconsin-Milwaukee 2A        1C            1A  3A (https://web.uwm.edu/hurricane-models/models/archive/)                                                                                                    Action 11th  Annual Modeling, Experimentation and Validation (MeV) Summer School                                                        20
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Final Stuff Thats so cool Closing Remarks Are we there yet?
* NRC has long used risk information to support decision making
* Ongoing trends are shaping current use
* Improvements in MeV developments and applications are welcome and inevitable
* MeV challenges Are amenable to technical solutions Depend on perspective 11th Annual Modeling, Experimentation and Validation (MeV) Summer School              21
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Final Stuff Knowledge Checks
* What is the triplet definition of risk?
* What are some of the NRC regulatory functions supported by Folks, clearly we have risk information?                                                                        a TEP vulnerability
* What are some of the current                                              Thermal trends affecting NRCs use of risk                                        Exhaust Port information?
* What are some of the ways in which a decision makers views on MeV development needs can differ from a developers?
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                        22
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Final Stuff Essay Questions
* Is airplane flight less risky than                                                                                                  OTOH automobile travel?
* How do advances in MeV support NRCs risk-informed approach to regulatory decision making?
* In your field of interest, should there be more support for the development of diverse modeling approaches? Why or why not?                                            Will somebody find me a one-handed scientist?!
                                                                                                                - Senator Edmund Muskie (Concorde hearings, 1976)
I. Flatow, Truth, Deception, and the Myth of the One-Handed Scientist, October 18, 2012. Available from:
https://thehumanist.com/magazine/november-december-2012/features/truth-deception-and-the-myth-of-the-one-handed-scientist 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                        23
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 ADDITIONAL SLIDES 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 24
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview NRC Organization
* Headquarters + 4 Regional Offices
* 5 Commissioners
  *  ~3100 staff (FY 2019)
* Annual budget ~$930M
* Website: www.nrc.gov
* Information Digest: NUREG-1350 V31 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 25
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview Regulated Facilities At A Glance*
* Operating Reactors
        - 97 plants (58 sites)
        - 65 PWR, 32 BWR
        - 19% U.S. (2019)
        - Shutting down: 12
        - License Renewal: 89
        - Subsequent License Renewal: 8 (in process)
* New Reactors
        - Early Site Permits: 5 approved, 1 under review
        - Combined Licenses: 18 received, 8 issued and active
        - Design Certifications: 6 issued, 3 under review
* Research and Test Reactors
        - 31 operating (21 States)
        - 2 medical isotope production facilities authorized for construction
* Nuclear Materials
        - 19,300 licensees
        - 3 Uranium recovery facilities
        - 10 fuel cycle facilities
  *As of early 2019, from NUREG-1350 V31 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 26
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview NRC Mission The U.S. Nuclear Regulatory Commission licenses and regulates the Nations civilian use of radioactive materials to protect public health and safety, promote the common defense and security, and protect the environment.
                                        - NUREG-1614 (NRC Strategic Plan) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 27
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview How We Regulate Functions                      Standard*                                          Principles**
Reasonable assurance of
* Independence adequate protection
* Openness
* Efficiency
* Clarity
* Reliability
* When granting, suspending,                        **NRC Strategic Plan revoking, or amending licenses                      (NUREG-1614) or construction permits. (Atomic Energy Act of 1954, as amended
                                    - see NUREG-0980, v1, n7, 2005) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 28
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview RIDM and NRCs Principles of Good Regulation Readily                  Defense-                          Efficiency Logical Understood
* Independence In-Depth Acceptable Safety                                                          Risk            Best
* Openness Margins          Integrated                                                  Information
* Efficiency Openness Decision Reliability
* Clarity Coherent                Making                                            Performance
* Reliability Current                                                      Monitoring Regulations                            Practical                                                    U.S. Nuclear Regulatory Commission, Independence                                  Candid        Principles of Good Regulation Clarity          Public (ADAMS ML14135A076)
Highest                                                    Competence Standards 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                        29
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview The Role of Regulatory Research (1/2) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 30
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview The Role of Regulatory Research (2/2)
Typical products (regulatory research)
Decision
* Ways to look at and/or approach problems (e.g., frameworks, methodologies)
* Points of comparison (e.g., reference calculations, experimental results)
* Job aids (e.g., computational tools, databases, standards, guidance: best practices, procedures)
Specific
* Problem-specific information (e.g., results, insights, uncertainties)
Analyses                                            Side benefits
* Education/training of workforce
* Networking with technical community Methods, Models, Tools,                          R&D            Prioritization considerations (subject to change)
Databases, Standards,
* Mission
                                                                                        -    Potential Risk Impact Guidance,                                                      -    Business Line Safety Priorities
                                                                                        -    Deterministic Evaluations
                                                                                        -    Improving Uncertainty and/or State of Knowledge
                                                                                        -    Generic Fleet Applicability
* Demand Foundational Knowledge                                                        -    Level (Internal Driver)            Resources, 17%
                                                                                        -    Function (Internal Driver)
                                                                                        -    External Drivers Mission, 66%
* Resources                                Demand, 17%
                                                                                        -    Leverage Regulatory Decision Support                                                    -    Anticipated Completion re*search, n. diligent and systematic inquiry or investigation in order to discover or revise facts, theories, applications, etc.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                          31
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview Different Communities, Different Challenges
* Understanding
* Data
* Confidence
* Bounding/screening                                                                                  o Uncertainties
* Guidance
* Holes                Analysts/                                                Users o Heterogeneity and aggregation
* Integration          Reviewers
* Other Factors (e.g.,
* Imagination                                                                                          DID, safety margins)
* Stakeholders
* New science/engineering
* Operational experience
* Time
* Intended users/applications
* Computational limits
* Resources                                  Developers
* Rewards
* Biases/heuristics
* Communication 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                              32
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Overview An Evolving Budgetary Environment 700 NRC Research Budget (FY 1976 - FY 2019)                                                                50 45 600 Contracting Budget ($M)
Actual ($M)              40 500                                                                                Inflation Adjusted ($M) 35
                                                                                                                                                  % NRC Total
                                                                                                                  % NRC Total 30 400 25 300 20 200                                                                                                          15 10 100 5
0                                                                                                          0 Year Budget data from NUREG-1350 (NRC Information Digest) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                33
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Regulation: Risk-informed fire protection (1/2)
* Browns Ferry Nuclear Power Plant fire (3/22/75)
Adapted from NUREG-0050
* Candle ignited foam penetration seal, initiated cable tray fire; water suppression delayed; complicated shutdown 11.5m
* Second-most challenging event in U.S. nuclear                                                                                  8.5m power plant operating history
* Spurred changes in requirements and analysis                                                                  TVA File Photo 3m 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                          34
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Regulation: Risk-informed fire protection (2/2)
* Post-Browns Ferry deterministic fire protection (10 CFR Part 50, Appendix R) hour fire barrier, OR
      - 20 feet separation with detectors and auto suppression, OR hour fire barrier with detectors and auto suppression
* Risk-informed, performance-based fire protection (10 CFR 50.48(c), NFPA 805)
      - Voluntary alternative to Appendix R
      - Deterministic and performance-based elements
      - Changes can be made without prior approval; risk must be acceptable
      - More than 1/3 U.S. fleet has completed transition
* Methods adopted by international organizations                                                  From Cline, D.D., et al., Investigation of Twenty-Foot Separation Distance as a Fire Protection Method as Specified in 10 CFR 50, Appendix R, NUREG/CR-3192, 1983.
11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                                      35
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Licensing: Changes in plant licensing basis
* Voluntary changes: licensee requests, NRC reviews
* Small risk increases may be acceptable
* Change requests may be combined
* Decisions are risk-informed 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 36
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Oversight - Reactor Oversight Program (ROP)
* Inspection planning                                                                            CDF < 1E-6 LERF < 1E-7
* Determining significance of findings
      - Characterize performance deficiency                                                      1E-6 < CDF < 1E-5 1E-7 < LERF < 1E-6
      - Use review panel (if required)
      - Obtain licensee perspective                                                              1E-5 < CDF < 1E-4
      - Finalize                                                                                1E-6 < LERF < 1E-5
* Performance indicators                                                                        CDF > 1E-4 LERF > 1E-5 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                    37
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information OpE - Accident Sequence Precursor (ASP) Program (1/2)
* Program recommended by WASH-1400 review group (1978)                                                                                          significant
* Provides risk-informed view of nuclear                                                                        precursor plant operating experience
      - Conditional core damage probability                                                                                    precursor (events)
      - Increase in core damage probability (conditions)                                                                      Licensee Event Reports 1969-2018
* Supported by plant-specific Standardized                                            (No significant precursors since 2002)
Plant Analysis Risk (SPAR) models 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                          38
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information OpE - Accident Sequence Precursor (ASP) Program (2/2) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 39
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Decision Support - Research (Frameworks/Methodologies)
NRC-sponsored Fire                                                      Technology Neutral PRA R&D (universities)                                                  Framework
* Started after Browns
* Explored use of risk Ferry fire (1975)                                                    metrics to identify
* Developed fire PRA                                                    licensing basis approach first used in                                                events industry Zion and
* Inspiration and part Indian Point PRAs                                                    basis for current (early 80s), same                                                    Licensing basic approach today                                                  Modernization
* Started path leading to                                              Program risk-informed fire protection (NFPA 805) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                        40
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Decision Support - Research (Reference Points)
NUREG-1150                                                        SOARCA
* Continuing point
* Detailed analysis of of comparison for                                              potential severe Level 1, 2, 3                                                  accidents and offsite results                                                        consequences
* Expectations
* Updated insights on (ballpark)                                                    margins to QHOs Peach Bottom
* Basis for regulatory analysis (backfitting, generic issue resolution)
NUREG-1150 (Surry)
Surry              Sequoyah 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                        41
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Example Uses of Risk Information Decision Support - Research (Methods/Models/Tools)
SPAR                                                                  IDHEAS-G
* Independent plant-
* Improved support for specific models                                                      qualitative analysis (generic data)
* Explicit ties with cognitive
* All-hazards (many)                                                  science (models, data)
* Support SDP, MD
* General framework for 8.3, ASP, GSI, SSC                                                  developing focused studies                                                              applications (e.g.,
* Adaptable for specific                                              IDHEAS-ECA) circumstances
* Benefits from NPP SAPHIRE                                                                  simulator studies
* Consistent with current
* General purpose HRA good practices model-building tool guidance (NUREG-1792)
* Multiple user From https://en.wikipedia.org/wiki/SAPHIRE        interfaces 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                                42
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Improved Realism: Finer Resolution More                                              More Details                                          Realism A common (and reasonable) expectationbut not a given:
* Need data/evidence for details
* Need to identify and treat sub-model dependencies
* Need to recognize potential impact of sub-model heterogeneity 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 43
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Improved Realism: Better Completeness PRA Examples:
* Decision-based Errors of Commission (EOCs) and Omission (EOOs)
        - Bounded rationality model: reasons for decisions and actions (and inaction) are affected by context, including
* scenario evolution
* past decisions/actions
        - Dynamic modeling provides framework for context
        - Insights into difference between precursors and accidents?
Accident                                      Possible Precursor(s)
TMI-2 (1979)                                  Davis-Besse (1977), Beznau (1974)
Chernobyl 4 (1986)                            Leningrad (1975)
* T/H reliability of passive systems 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 44
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Improved Decision Support: Additional Insights PRA Examples
* Human performance insights
        - Available time for action
        - Important contextual factors
        - Compounding impact of decisions and actions
* System insights
        -  Complex dependencies
        -  Success criteria
        -  Sequences                                                                              Long-duration scenarios Partial/intermittent failures
        -  Time-dependence (warning, aftershocks)
Game Over                        Recovery/mitigation actions
* What isnt important as well as what is 11th Annual Modeling, Experimentation and Validation (MeV) Summer School                              45
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Improved Decision Support: Better Use of Knowledge PRA Examples
* Phenomena
        - Direct use of knowledge encoded in model systems (models, data, guidance, reviews)
        - Not restricted to discrete-logic
* Operational experience Rich information source: influencing factors, mechanisms, dependencies, time scales, successes, 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 46
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Broader Acceptance: Integration of Multiple Disciplines
* Risk-informed decision making
        - An enterprise-wide activity
        - Need broad understanding, buy-in
* Postulate: explicit, mechanistic modeling reduces need for translation
        - Disciplines can use native frameworks and terms (e.g., forces/behaviors vs.
success/failure)
        - Improved comfort, trust 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 47
 
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Benefits of MeV Broader Acceptance: Consistency with Engineering Trends
* Increasing computational capabilities => enables more detailed models
* Improving scientific and engineering knowledge =>
desire to incorporate
* Changing problem solving approaches and expectations in technical community and even general public
        - routine use of simulation
        - explicit characterization of uncertainty 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 48}}

Revision as of 13:17, 17 January 2022

PRA and RIDM Inl Mev
ML21138A779
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Issue date: 07/27/2020
From: Nathan Siu
NRC/RES/DRA
To:
Siu, Nathan - 301 415 0744
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