ML21138A779
| ML21138A779 | |
| Person / Time | |
|---|---|
| Issue date: | 07/27/2020 |
| From: | Nathan Siu NRC/RES/DRA |
| To: | |
| Siu, Nathan - 301 415 0744 | |
| Shared Package | |
| ML21138A647 | List: |
| References | |
| Download: ML21138A779 (48) | |
Text
NRC Perspective on Nuclear Safety PRA and Risk-Informed Decision Making at the NRC: Some Trends and Challenges*
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 NRC USE OF RISK INFORMATION 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 4
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)
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Triplet Definition of Risk (Kaplan and Garrick, 1981)*
11th Annual Modeling, Experimentation and Validation (MeV) Summer School 5
i i
i Risk { i, i,
i }
Features
- Vector, not scalar
- Qualitative and quantitative
- Differences 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
- What can go wrong?
- What are the consequences?
- How likely is it?
Use of risk information
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 A PRA/RIDM Timeline 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 6
1940 1950 1970 1960 1980 1990 2010 2000 2020 Indian Point IPE/
IPEEE Atomic Energy Act No undue risk Safety Goal Policy PRA Policy Price-Anderson (non-zero risk)
RG 1.174 ASME/ANS PRA Standard Revised Reactor Oversight Level 3 PRA NUREG-1150 WASH-740 Farmer Curve WASH-1400 German Risk Study UKAEA SGHWR NRC created Fukushima Chernobyl TMI EU Stress Tests AEC created Windscale Hanford to WASH-1400 Early PRAs Expansion Modern Applications Use of risk information
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 NRC Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 7
Regulations and Guidance Licensing and Certification Oversight Operational Experience Decision Support Use of risk information PRA Policy Statement (1995)
- Increase use of PRA technology in all regulatory matters Consistent with PRA state-of-the-art Complement deterministic approach, support defense-in-depth philosophy
- Benefits:
(1) Considers broader set of potential challenges (2) Helps prioritize challenges (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.
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Recent Application (2019)
In any licensing review or other regulatory decision, the staff should apply risk-informed principles when strict, prescriptive application of deterministic criteria such as the single failure criterion is unnecessary to provide for reasonable assurance of adequate protection of public health and safety.
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.
Risk-Informed Decisionmaking (RIDM) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 8
Current regulations Defense-in-depth Safety margins Risk Monitoring Integrated Decision Making Adapted from RG 1.174 Use of risk information a philosophy whereby risk insights are considered together with other factors to establish requirements that better focus licensee and regulatory attention on design and operational issues commensurate with their importance to public health and safety. [Emphases added]
White Paper on Risk-Informed and Performance-Based Regulation, SECY-98-144, January 22, 1998.
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 In Addition to Immediate Decision Support 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 9
Adapted from NUREG-2150 Risk Information
- Results
- Insights
- Explanations
- Uncertainties
- Qualifications Use of risk information
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 SOME TRENDS AND CHALLENGES 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 10 Its tough to make predictions, especially about the future.
- Yogi Berra
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 11 Applying the Principles of Good Regulation as a Risk-Informed Regulator, October 15, 2019 (ADAMS ML19260E683)
Trends and challenges
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 0
10 20 30 40 50 FY-17 FY-18 FY-19 FY-20 Number Fiscal Year Risk-Informed LARS Received*
Miscellaneous Risk Insights TMRE Fire Seismic GSI-191 EPU 50.69 TSTF-XXX RI TS Comp Time RI-ISI ILRT
- As of June 8, 2020 Market Forces 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 12 "Risk-Informed Performance-Based Technology-Inclusive Guidance for Non-Light Water Reactors," NEI 18-04, Rev. 1, August 29, 2019.
Operating Rx - More use of PRA models New Rx - Early use of PRA in design Trends and challenges
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Cmon HAL, open the pod bay door Im worried about the mission, Dave.
New Technologies 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 13
- New designs
- New operational concepts
- Smart reactor systems
- Improved analysis tools Photo courtesy of NEA Halden Reactor Project Trends and challenges
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 New Professionals Changing Experiences, knowledge Information content and delivery preferences Comfort with analytics, risk, probability Mobility 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 14 Adapted from: https://www.nrc.gov/reading-rm/doc-collections/commission/slides/2019/20190618/staff-20190618.pdf Trends and challenges
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Trends and Impacts: A Two-Way Street Trends Increasing # RI-applications New licensing approaches New designs New operational concepts New technologies New analytical methods New professionals
11th Annual Modeling, Experimentation and Validation (MeV) Summer School 15 Decision Making Issue Identification Option Identification Analysis Deliberation Implementation Monitoring PRA Technology Methods Models Tools Data Trends and challenges
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 SOME RISK-ORIENTED THOUGHTS ON MeV 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 16 Many calculations bring success; few calculations bring failure. No calculations at all spell disaster!
- Sun-Tzu (The Art of War)
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 A PRA Perspective on MeV What: System of Systems Why: Decision Support 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 17 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)
Thoughts on MeV
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 Thoughts on MeV
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Some General Challenges*
- Trustworthiness
- breadth/completeness
- integration and balance
- uncertainty characterization**
- good enough
- Transparency
- Explainability
- complexity
- uncertainties**
11th Annual Modeling, Experimentation and Validation (MeV) Summer School 19 Thoughts on MeV 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
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 A Matter of Perspective Developer Method/model/tool Validity Best-Estimate [Plus Uncertainty]
Decision Maker Results (including user effect)
Acceptability (for intended use)
Community state-of-knowledge 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 20 Thoughts on MeV 2A 1C 1A 3A Action 1.0 1E-1 1E-2 1E-3 1E-4 1E-5 Human Error Probability Adapted from University of Wisconsin-Milwaukee (https://web.uwm.edu/hurricane-models/models/archive/)
Adapted from NUREG-2156 90W 85W 80W 75W 70W 65W 60W Hurricane Andrew 8/22/1992, 1200 UTC (about 2 days before FL landfall)
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Closing Remarks 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 21 Thats so cool 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 Final Stuff
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Knowledge Checks
- What is the triplet definition of risk?
- What are some of the NRC regulatory functions supported by risk information?
- What are some of the current trends affecting NRCs use of risk 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 Final Stuff Folks, clearly we have a TEP vulnerability Thermal Exhaust Port
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Essay Questions
- Is airplane flight less risky than 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?
11th Annual Modeling, Experimentation and Validation (MeV) Summer School 23 Final Stuff OTOH 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:
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 ADDITIONAL SLIDES 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 24
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 26
- As of early 2019, from NUREG-1350 V31 NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 How We Regulate 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 28 Functions Reasonable assurance of adequate protection Principles**
Independence Openness Efficiency Clarity Reliability
- When granting, suspending, revoking, or amending licenses or construction permits. (Atomic Energy Act of 1954, as amended
- see NUREG-0980, v1, n7, 2005)
- NRC Strategic Plan (NUREG-1614)
Standard*
NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 RIDM and NRCs Principles of Good Regulation 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 29 Highest Standards Best Information Public Coherent Logical Practical Competence Acceptable Readily Understood Candid Independence Openness Efficiency Clarity Reliability Risk Safety Margins Defense-In-Depth Current Regulations Performance Monitoring Integrated Decision Making Independence Openness Efficiency Clarity Reliability U.S. Nuclear Regulatory Commission, Principles of Good Regulation (ADAMS ML14135A076)
NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 The Role of Regulatory Research (1/2) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 30 NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 The Role of Regulatory Research (2/2)
Typical products (regulatory research)
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)
Problem-specific information (e.g., results, insights, uncertainties)
Side benefits Education/training of workforce Networking with technical community Regulatory Decision Support Specific Analyses
- Methods, Models, Tools, Databases, Standards,
- Guidance, Foundational Knowledge Decision R&D 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 Prioritization considerations (subject to change)
Mission Potential Risk Impact Business Line Safety Priorities Deterministic Evaluations Improving Uncertainty and/or State of Knowledge Generic Fleet Applicability Demand Level (Internal Driver)
Function (Internal Driver)
External Drivers Resources Leverage Anticipated Completion Mission, 66%
Demand, 17%
Resources, 17%
NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Different Communities, Different Challenges 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 32 Developers Analysts/
Reviewers Users Understanding Confidence o
Uncertainties o
Heterogeneity and aggregation Other Factors (e.g.,
DID, safety margins)
Stakeholders Time Resources Biases/heuristics Communication Data Bounding/screening Guidance Holes Integration Imagination New science/engineering Operational experience Intended users/applications Computational limits Rewards NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 An Evolving Budgetary Environment 0
5 10 15 20 25 30 35 40 45 50 0
100 200 300 400 500 600 700
% NRC Total Contracting Budget ($M)
Year NRC Research Budget (FY 1976 - FY 2019)
Actual ($M)
Inflation Adjusted ($M)
% NRC Total Budget data from NUREG-1350 (NRC Information Digest) 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 33 NRC Overview
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Regulation: Risk-informed fire protection (1/2)
Browns Ferry Nuclear Power Plant fire (3/22/75)
Candle ignited foam penetration seal, initiated cable tray fire; water suppression delayed; complicated shutdown Second-most challenging event in U.S. nuclear power plant operating history Spurred changes in requirements and analysis TVA File Photo 8.5m 8.5m 11.5m 11.5m 3m 3m Adapted from NUREG-0050 Adapted from NUREG-0050 8.5m 11.5m 3m Adapted from NUREG-0050 Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 34
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Regulation: Risk-informed fire protection (2/2)
Post-Browns Ferry deterministic fire protection (10 CFR Part 50, Appendix R) 3-hour fire barrier, OR 20 feet separation with detectors and auto suppression, OR 1-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.
Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 35
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 36
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Oversight - Reactor Oversight Program (ROP)
- Inspection planning
- Determining significance of findings
- Characterize performance deficiency
- Use review panel (if required)
- Obtain licensee perspective
- Finalize
- Performance indicators CDF < 1E-6 LERF < 1E-7 1E-6 < CDF < 1E-5 1E-7 < LERF < 1E-6 1E-5 < CDF < 1E-4 1E-6 < LERF < 1E-5 CDF > 1E-4 LERF > 1E-5 Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 37
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 OpE - Accident Sequence Precursor (ASP) Program (1/2)
Program recommended by WASH-1400 review group (1978)
Provides risk-informed view of nuclear plant operating experience
- Conditional core damage probability (events)
- Increase in core damage probability (conditions)
Supported by plant-specific Standardized Plant Analysis Risk (SPAR) models Licensee Event Reports 1969-2018 (No significant precursors since 2002) significant precursor precursor Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 38
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 OpE - Accident Sequence Precursor (ASP) Program (2/2)
Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 39
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Decision Support - Research (Frameworks/Methodologies)
NRC-sponsored Fire PRA R&D (universities)
Started after Browns Ferry fire (1975)
Developed fire PRA approach first used in industry Zion and Indian Point PRAs (early 80s), same basic approach today Started path leading to risk-informed fire protection (NFPA 805)
Technology Neutral Framework Explored use of risk metrics to identify licensing basis events Inspiration and part basis for current Licensing Modernization Program Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 40
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Decision Support - Research (Reference Points)
NUREG-1150 Continuing point of comparison for Level 1, 2, 3 results Expectations (ballpark)
Basis for regulatory analysis (backfitting, generic issue resolution)
NUREG-1150 (Surry)
SOARCA Detailed analysis of potential severe accidents and offsite consequences Updated insights on margins to QHOs Peach Bottom Surry Sequoyah Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 41
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Decision Support - Research (Methods/Models/Tools)
SPAR Independent plant-specific models (generic data)
All-hazards (many)
Support SDP, MD 8.3, ASP, GSI, SSC studies Adaptable for specific circumstances SAPHIRE General purpose model-building tool Multiple user interfaces IDHEAS-G Improved support for qualitative analysis Explicit ties with cognitive science (models, data)
General framework for developing focused applications (e.g.,
IDHEAS-ECA)
Benefits from NPP simulator studies Consistent with current HRA good practices guidance (NUREG-1792)
From https://en.wikipedia.org/wiki/SAPHIRE Example Uses of Risk Information 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 42
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 Improved Realism: Finer Resolution 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 Benefits of MeV More Details More Realism
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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?
T/H reliability of passive systems 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 44 Accident Possible Precursor(s)
TMI-2 (1979)
Davis-Besse (1977), Beznau (1974)
Chernobyl 4 (1986)
Leningrad (1975)
Benefits of MeV
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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
- Time-dependence (warning, aftershocks)
- What isnt important as well as what is 11th Annual Modeling, Experimentation and Validation (MeV) Summer School 45 Benefits of MeV Game Over Long-duration scenarios Partial/intermittent failures Recovery/mitigation actions
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 Benefits of MeV
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 Benefits of MeV
MODELING, EXPERIMENTATION, & VALIDATION - SUMMER 2020 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 Benefits of MeV