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| number = ML21138A779
| number = ML21138A779
| issue date = 07/27/2020
| issue date = 07/27/2020
| title = PRA and RIDM Inl Mev
| title = PRA and RIDM INL Mev
| author name = Siu N
| author name = Siu N
| author affiliation = NRC/RES/DRA
| author affiliation = NRC/RES/DRA

Latest revision as of 19:51, 17 April 2023

PRA and RIDM INL Mev
ML21138A779
Person / Time
Issue date: 07/27/2020
From: Nathan Siu
NRC/RES/DRA
To:
Siu, Nathan - 301 415 0744
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ML21138A647 List:
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Download: ML21138A779 (48)
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PRA and Risk-Informed Decision Making NRC at thePerspective NRC: Someon Nuclear Trends andSafetyChallenges*

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

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.

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]

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

- 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)

- 20 feet separation with detectors and auto suppression, OR hour fire barrier with detectors and auto suppression

- 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)

  • 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)
  • General framework for 8.3, ASP, GSI, SSC developing focused studies applications (e.g.,
  • Adaptable for specific IDHEAS-ECA) circumstances
  • Consistent with current
  • General purpose HRA good practices model-building tool guidance (NUREG-1792)

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

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