ML21326A184
| ML21326A184 | |
| Person / Time | |
|---|---|
| Issue date: | 11/09/2021 |
| From: | Christopher Boyd, Jim Steckel, Robert Tregoning NRC/RES/DSA |
| To: | |
| Dennis M | |
| Shared Package | |
| ML21326A182 | List: |
| References | |
| Download: ML21326A184 (15) | |
Text
NRCs Future-Focused Research Program Advisors: R. Tregoning, C. Boyd Project Manager: J. Steckel NRC Data Science and AI Workshop III -
Future Focused Initiatives 11/9/2021 Thats so cool Are we there yet?
2 FFR Program Overview
- Program Concept and Context
- Program Objectives
- Process Considerations
- Activities
- Artificial Intelligence and Data Science
- Future Directions
3 Future-Focused Research (FFR) Program Concept Support NRCs need for longer-term ( 3 years) R&D activities Broad scope: all good ideas considered*
Funding
- Dedicated
- Fully loaded at beginning of project
- Exploring opportunities to leverage with University R&D Grant Program Program management and administration
- Streamlined submission and review process
- Low-burden, low-resource implementation Start small, grow with success
- Initiated current program in FY-20 Mixed project portfolio
- Time horizons
- Project risk: emphasizing riskier, less-applied ideas for FY-22 and beyond
- Inspired by national lab Laboratory-Directed Research and Development (LDRD) programs Concept Scale
- Includes blue sky, risky projects
- All ideas (including those outside FFR scope) are communicated to NRC management Program Concept and Context
Decision Making Computational Methods Human/Org Factors Natural Hazards Blue Sky Simulation-based PRA*
Dynamic PRA*
Automatic model construction AI-based data mining AI-assisted RIDM**
Advanced techniques for risk communication NRCs research Needs Advanced metrics for RIDM**
Autonomous Reactors Org Factors in PRA*
Errors of Commission Correlated Hazards Simulation-Based Extreme Hazards Climate Change NRCs Blue Sky Now Blue Sky Degree of Blueness (DoB) =
f{technological readiness, clarity of application, user skepticism}
Program Concept and Context
- RIDM = Risk Informed Decision Making
5 NRCs Horizon: Opportunities and Challenges Its tough to make predictions, especially about the future.
- Yogi Berra
- Changing reactor technologies, concepts of operation
- Increasing knowledge base (and means to use)
- Increasing computational capabilities (hardware, software, modeling approaches, )
- Changing staff and other stakeholders
- Increasing and more challenging regulatory applications RES goal: help ensure that NRC is prepared U.S. Nuclear Regulatory Commission, The Dynamic Futures for NRC Mission Areas, 2019.
(ML19022A178) 0 Program Concept and Context
6 FFR Objectives
- Provide kickstart (basis, direction, and support) for extended projects (outside the FFR program) on likely important topics
- Promote more robust R&D program to sustain agency
- Energize staff
- Improve (and perhaps even radically change) foundational knowledge on key topics
- Develop useful products and appropriate staff cognizance of same
- Actionable insights (including dismissal of potential issues)
- Tools and data for analyses
- Current status, directions, and likely schedules for potentially important technologies, programs, etc.
- Create synergy with related programs (e.g., University R&D Grants)
Program Objectives
7 Research: providing a basis for decisions 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.
Program Objectives
8 FFR Process Idea Generation Idea Refinement and Selection Portfolio Monitoring and Reporting Follow-On Projects (User Needs)
FFR Program Process Considerations Gather ideas - could be individual or crowdsourced Open to ideas from across agency As needed, work with submitters to refine initial concept Advisors recommend and senior RES managers choose projects Communicate and monitor progress through program reviews and seminars May identify research for potential future development through user needs
9 Project Rating Considerations*
- Agency impact
- Improves NRCs future capabilities
- Improves foundational knowledge important to future decision making
- Addresses recognized gaps
- Resource leveraging
- Enables NRCs influencing of important external activities
- Potentially benefits multiple NRC programs
- Leverages available resources for research
- Staff enrichment
- Is attractive to individual researchers
- Is attractive to university research programs
- Notes:
- 1) Considerations used as guidance.
- 2) Selection committee also considers the overall portfolio of FFR activities a)
Risk b)
Resources Process Considerations
10 FFR Portfolio Appropriate balance among efforts 50% developing foundational knowledge 50% developing more specific technical tools or addressing regulatory framework gaps Current portfolio is balanced across risk horizon spectrum.
Trending toward bluer sky activities as FFR program has matured.
Activities Foundational Technical Regulatory Low Moderate Strong Gap Objectives Degree of Blueness 0
0.5 1
1.5 2
2.5 3
FY-20 FY-21 FY-22 Submitted Selected
11 AI and Data Science in FFR Related FFR Activities FY-20
- Digital Twins - Regulatory Viability FY-21
- RESbot - A web-based bot to aid RES Researchers FY-22
- Use Machine Learning to Prioritize Inspections
- Characterizing Cyber Security Using AI/ML
- Application of Natural Language Processing to NRC Regulatory Documents Explosion of AI-DS topics both submitted and selected in latest data call General bias in selecting AI-DS topics as FFR activities 0
10 20 30 40 50 60 FY-20 FY-21 FY-22
(% of Activities)
Submitted Selected AI and Data Science
12 Existing AI-DS FFR Activities Digital Twins - Regulatory Viability
- Objective: Understand the potential industry applications of reactor digital twins and the regulatory viability of use of digital twins
- Approach: Assess existing technical information, knowledge, tools, and codes and standards to determine state-of-the-art and current gaps; identify regulatory gaps and fundamental infrastructure elements
- Status:
- Held December 2020 and September 2021 workshops: published December proceedings (ML21083A132)
- Completed report: The State of Technology of Application of Digital Twins (ML21160A074)
- Transitioned out of FFR and is continuing as a follow-on research project RESbot - A web-based bot to aid RES Researchers
- Objective: Develop one or more web-based bots, to aid NRC researchers in mining, for example, experimental data, analyses, compilation of field experience, and risk assessments to support decision-making
- Approach: Create NRC use cases and develop RESbot implementation plan to address use cases; executing implementation plan would be a follow-on effort
- Status: Defined use cases on technical document querying, modeling and simulation, and report preparation; currently evaluating use cases using IBM Watson Discovery and Microsoft Azure platforms AI and Data Science
13 FY-22 AI-DS FFR Activities Use Machine Learning (ML) to Prioritize Inspections
- Objective: Explore use of commercially available ML applications to prioritize inspections and their associated periodicity during abnormal situations (i.e., pandemics)
- Approach: Define licensees as customers; define and build safety behavior using data similar to customer preferences; perform test case using several off-the-shelf ML tools Characterizing Cyber Security Using AI/ML
- Objective: Evaluate issues associated with future AI/ML applications used to characterize cyber security system performance and configurations, and detect abnormal system states associated with a cyber attack
- Approach: Identify viable AI/ML technologies; evaluate technologies relative to defined nuclear cyber use case; apply most promising approach to benchmark test case Application of Natural Language Processing (NLP) to NRC Regulatory Documents
- Objective: Assess use of existing NLP tools for NRC use to assist review of licensing actions
- Approach: Create licensing benchmark case and collect associated data; apply named entity recognition to data set and subsequently create term-frequency inverse document frequency model; evaluate Googles BERT model to retain semantic meaning for neural network training and implementation AI and Data Science
14 Thoughts for Future: AI/DS Nuclear is typically a later adopter of technological innovations
- Slower pace of innovation
- Opportunities to build off advancements and investments in other industries
- Which AI/DS advancements hold biggest promise and challenges for nuclear application?
Nuclear energy landscape is continually changing
- Future reactors will likely be smaller; may be more widely distributed
- Bulk of aging LWR fleet may require operation beyond 60 to 80 years to meet nations energy goals
- How can AI/DS be used to both optimize the new design, certification, and approval process?
- How can AI/DS optimize efficiencies of existing plants to retain safety and economic viability?
- How can NRC use AI/DS to evaluate this landscape to better position itself for future regulatory challenges?
Continuous pressure to decrease human operations to maximize efficiencies
- What are the actions/operations where decreasing human involvement is most beneficial?
- Are there actions/operations that should always retain human involvement/oversight and, if so, how can these be best identified?
Future Directions
15 Questions?