Risk-informed Methods and Applications in Nuclear and Energy Engineering

Modeling, Experimentation, and Validation

1st Edition - November 15, 2023
Editors: Curtis Smith, Diego Mandelli, Katya Le Blanc
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 1 1 5 2 - 8
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 8 1 8 - 5

Risk-informed Methods and Applications in Nuclear and Energy Engineering: Modelling, Experimentation, and Validation presents a comprehensive view of the latest technical approache… Read more

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Risk-informed Methods and Applications in Nuclear and Energy Engineering: Modelling, Experimentation, and Validation presents a comprehensive view of the latest technical approaches and experimental capabilities in nuclear energy engineering. Based on Idaho National Laboratory’s popular summer school series, this book compiles a collection of entries on the cutting-edge research and knowledge presented by proponents and developers of current and future nuclear systems, focusing on the connection between modelling and experimental approaches. Included in this book are key topics such as probabilistic concepts for risk analysis, the survey of legacy reliability and risk analysis tools, and newly developed tools supporting dynamic probabilistic risk-assessment.

This book is an insightful and inspiring compilation of work from top nuclear experts from INL. Industry professionals, researchers and academics working in nuclear engineering, safety, operations and training will gain a board picture of the current state-of-practice and be able to apply that to their own risk-assessment studies.

Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1 Introduction
Abstract
1.1 Probabilistic safety assessment scope
References
Part 1: Risk and reliability
Chapter 2 Improving nuclear power plant flooding hazard analysis through component performance experiments, fragility model development, and smoothed particle hydrodynamic simulation
Abstract
Dedication
2.1 Introduction
2.2 Component flooding experiments
2.3 Fragility modeling
2.4 Smoothed particle hydrodynamics
2.5 Fragility and SPH integration
2.6 Conclusions
References
Chapter 3 Severe accidents in light water reactors
Abstract
3.1 Introduction
3.2 Overview of severe accident phenomena
3.3 Severe accident research
3.4 Evolution of understanding of severe accident risk
3.5 Conclusions
References
Further reading
Chapter 4 Dynamic probabilistic risk assessment (PRA): Theory, tools, and applications for uncertainty quantification
Abstract
4.1 Introduction
4.2 Theoretical basis
4.3 Implementation software
4.4 Assessing impact of uncertainties
4.5 Challenges in data generation and analysis and some possible solutions
4.6 Conclusions
References
Chapter 5 Cyber risk considerations for nuclear digital I&C systems
Abstract
Acknowledgment
5.1 Introduction
5.2 Digital assets and I&C systems in nuclear reactors
5.3 Cyber risk management
5.4 Cyber-informed engineering (CIE)
5.5 Conclusions
References
Chapter 6 Perspective on attributes of modeling and simulation tools for effective reactor core analysis
Abstract
6.1 Introduction
6.2 Reactor core analysis tools
6.3 Conclusions
References
Chapter 7 Coupled multiphysics simulations in nuclear reactor design and safety
Abstract
7.1 Introduction
7.2 Multiphysics coupling solution techniques
7.3 A pedagogical numerical example
7.4 Draining transient in the molten salt fast reactor
7.5 Conclusions and outlook
References
Chapter 8 Data-driven prognostics and health management (PHM) for predictive maintenance of industrial components and systems
Abstract
8.1 Introduction
8.2 Prognostics and health management for industry
8.3 Identification of critical components for PHM
8.4 Data-driven approaches to PHM
8.5 Decision-making based on PHM
8.6 Applications
8.7 Conclusions
References
Chapter 9 The history of risk-informing reactor safety regulation
Abstract
9.1 Introduction
9.2 Civilian reactor safety and the Atomic Energy Act of 1954
9.3 The China syndrome: The Three Ds in crisis (1965–67)
9.4 Defense in depth revised in the 1960s
9.5 WASH-1400: The first PRA (1975)
9.6 From the Atomic Energy Commission to the Nuclear Regulatory Commission (1975)
9.7 TMI, risk, and operating reactors (1979)
9.8 Probabilistic regulations in the 1980s
9.9 Safety goals (1980–86)
9.10 Severe accident policy statement (1985)
9.11 Reactor oversight in the 1980s and 1990s
9.12 The maintenance rule (1991)
9.13 PRA policy statement
9.14 The NRC's near-death experience and the reactor oversight process (1998)
9.15 Safety culture and Davis-Besse’s hole in the head
9.16 Fukushima: Coping with beyond-design-basis events
9.17 Conclusions
References
Chapter 10 Dynamic PRA: An overview of methods and applications using RAVEN
Abstract
10.1 Introduction
10.2 Classical probabilistic risk analysis
10.3 Dynamic probabilistic risk analysis
10.4 Smart dynamic probabilistic risk analysis methods
10.5 Analysis of dynamic probabilistic risk analysis data
10.6 Risk-importance measures for dynamic probabilistic risk analysis
10.7 Comparison between classical and dynamic probabilistic risk analysis
10.8 Integration of classical probabilistic risk analysis models into dynamic probabilistic risk analysis
10.9 Conclusions
References
Part 2: Experiments and validation
Introduction
Chapter 11 Enhancing resilience of our Nation's critical infrastructure
Abstract
11.1 Introduction
11.2 Resilience terminology
11.3 Taking a comprehensive and collaborative approach
11.4 Ongoing research efforts
11.5 Conclusions
References
Chapter 12 Light Water Reactor Sustainability Program—Enabling the continued operation of existing US nuclear reactors
Abstract
12.1 Introduction
12.2 Sustaining the existing fleet
12.3 Conclusions
References
Chapter 13 Idaho National Laboratory (INL) microgrid testbeds
Abstract
13.1 Background
13.2 Experimental microgrid
Chapter 14 Modeling and simulation of advanced manufacturing techniques using MOOSE and MALAMUTE
Abstract
Acknowledgments
14.1 Introduction
14.2 Advanced sintering techniques
14.3 Laser-based additive manufacturing processes
14.4 Conclusions
References
Chapter 15 Critical infrastructure modeling: Resilience and the ability to adapt and maneuver to threats
Abstract
15.1 Introduction
15.2 Resilience and complexity
15.3 Resilience manifold
15.4 Special topic: Cyber resilience
15.5 Summary
References
Further reading
Part 3: Methods in modeling and simulation
Introduction
Chapter 16 Status and trends of kinetic Monte Carlo simulation in reactor physics
Abstract
Acknowledgments
16.1 Introduction
16.2 An overview of Monte Carlo methods for particle transport
16.3 Coping with time-dependent Monte Carlo simulations
16.4 Time-dependent CADIS: Toward zero-variance Monte Carlo games
16.5 Conclusions
References
Chapter 17 Inverse uncertainty quantification based on the modular Bayesian approach
Abstract
17.1 Introduction
17.2 Methodology
17.3 Application to TRACE
17.4 Conclusions
References
Chapter 18 Modeling and simulation for security system design and evaluation
Abstract
18.1 Introduction
18.2 Evaluation
18.3 Computerized tools
18.4 Scribe3D [10]
18.5 Nuclear safety risk
18.6 Safety-security (2S) interface
18.7 Conclusions
References
Chapter 19 Human system simulation laboratory for testing, evaluation, and validation of human performance
Abstract
19.1 Introduction
19.2 HSSL description
19.3 Display hardware and simulation models
19.4 Human performance measurement tools
19.5 Experts
19.6 Research in the HSSL
19.7 Conclusion
References
Index

Curtis Smith

Dr. Curtis Smith is the Director for the Idaho National Laboratory Nuclear Safety and Regulatory Research Division. His most recent appointment is in serving as the lead for the Risk Integration and Uncertainty Working Group for the NASA Interagency Nuclear Safety Review Panel (INSRP) on the Mars 2020 mission. Dr. Smith has been in the risk and reliability assessment field for more than 28 years. He has worked at INL as a risk analysis specialist and has served as a consultant for a diverse set of organizations including the Department of Energy (DOE), the Nuclear Regulatory Commission (NRC), the National Aeronautics and Space Administration (NASA), the International Atomic Energy Agency (IAEA), the Federal Aviation Administration (FAA), and other government and private companies. Dr. Smith has published over 200 papers, books, and reports on risk and reliability theory and application. He has taught over 100 technical and university courses on a variety of reliability and safety topics. He holds a Ph.D. in nuclear engineering from Massachusetts Institute of Technology. He is a member of the American Society of Mechanical Engineers, American Nuclear Society, and the Idaho Academy of Sciences.

Affiliations and expertise

Director, Idaho National Laboratory Nuclear Safety and Regulatory Research Division, Idaho Falls, ID, USA

Diego Mandelli

Dr. Diego Mandelli is an R&D Scientist in the “Reliability, Risk and Resilience Sciences” Department at the Idaho National Laboratory (INL). His areas of expertise include risk, reliability, and system health management. His research focuses on the development of probabilistic methods based on machine learning, data mining and optimization algorithms. He is currently employing these methods to perform state-of-the-art simulation-based safety assessment (also known as dynamic probabilistic risk assessment), system health management and stochastic resource optimization. His developed methods range from data pre-processing, system modeling, system analysis, data mining/visualization, and decision making. He holds a Ph.D. degree in Nuclear Engineering from The Ohio State University (2011). He is a member of the American Nuclear Society.

Affiliations and expertise

R&D Scientist, Idaho National Laboratory, USA

Katya Le Blanc

Katya Le Blanc is a senior human factors scientist who has been conducting research in the energy sector at INL for 11 years. Her research in nuclear power plant modernization has led transformational change in the way field operators conduct procedures and has improved operator interfaces for control of nuclear power plants. She has designed human-system interfaces for transmission system technologies and cyber security for electric grid operation. She leads research in several complex, multidisciplinary subjects including nuclear power plant modernization, and cyber security risk characterization in nuclear power and critical infrastructure. She is the deputy National Technical Director the Department of Energy Nuclear Energy's Cyber security program, and leads research on cyber security risk management for nuclear power. Katya has over 100 technical publications in the subject of human factors in the energy sector. She is a senior member of IEEE, and holds a PhD and Master’s degree in cognitive psychology from New Mexico State and a BS in Psychology from New Mexico Institute of Mining and Technology.

Affiliations and expertise

Idaho National Laboratory, Idaho, USA