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.
1. Chapter 1 : Introduction - p. Page ix 2. Chapter 2 : Improving nuclear power plant flooding hazard analysis through component performance experiments, fragility model development, and smoothed particle hydrodynamic simulation - p. Page 11 3. Chapter 3 : Severe accidents in light water reactors - p. Page 27 4. Chapter 4 : Dynamic probabilistic risk assessment (PRA): Theory, tools, and applications for uncertainty quantification - p. Page 41 5. Chapter 5 : Cyber risk considerations for nuclear digital I&C systems - p. Page 52 6. Chapter 6 : Perspective on attributes of modeling and simulation tools for effective reactor core analysis - p. Page 71 7. Chapter 7 : Coupled multiphysics simulations in nuclear reactor design and safety - p. Page 88 8. Chapter 8 : Data-driven prognostics and health management (PHM) for predictive maintenance of industrial components and systems - p. Page 109 9. Chapter 9 : The history of risk-informing reactor safety regulation☆ - p. Page 134 10. Chapter 10 : Dynamic PRA: An overview of methods and applications using RAVEN - p. Page 161 11. Introduction - p. Page 232 12. Chapter 11 : Enhancing resilience of our Nation's critical infrastructure - p. Page 240 13. Chapter 12 : Light Water Reactor Sustainability Program—Enabling the continued operation of existing US nuclear reactors - p. Page 246 14. Chapter 13 : Idaho National Laboratory (INL) microgrid testbeds - p. Page 257 15. Chapter 14 : Modeling and simulation of advanced manufacturing techniques using MOOSE and MALAMUTE - p. Page 262 16. Chapter 15 : Critical infrastructure modeling: Resilience and the ability to adapt and maneuver to threats - p. Page 284 17. Introduction - p. Page 302 18. Chapter 16 : Status and trends of kinetic Monte Carlo simulation in reactor physics - p. Page 302 19. Chapter 17 : Inverse uncertainty quantification based on the modular Bayesian approach - p. Page 317 20. Chapter 18 : Modeling and simulation for security system design and evaluation - p. Page 328 21. Chapter 19 : Human system simulation laboratory for testing, evaluation, and validation of human performance☆ - p. Page 349 22. Index - p. Page 360
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.
1. Chapter 1 : Introduction - p. Page ix 2. Chapter 2 : Improving nuclear power plant flooding hazard analysis through component performance experiments, fragility model development, and smoothed particle hydrodynamic simulation - p. Page 11 3. Chapter 3 : Severe accidents in light water reactors - p. Page 27 4. Chapter 4 : Dynamic probabilistic risk assessment (PRA): Theory, tools, and applications for uncertainty quantification - p. Page 41 5. Chapter 5 : Cyber risk considerations for nuclear digital I&C systems - p. Page 52 6. Chapter 6 : Perspective on attributes of modeling and simulation tools for effective reactor core analysis - p. Page 71 7. Chapter 7 : Coupled multiphysics simulations in nuclear reactor design and safety - p. Page 88 8. Chapter 8 : Data-driven prognostics and health management (PHM) for predictive maintenance of industrial components and systems - p. Page 109 9. Chapter 9 : The history of risk-informing reactor safety regulation☆ - p. Page 134 10. Chapter 10 : Dynamic PRA: An overview of methods and applications using RAVEN - p. Page 161 11. Introduction - p. Page 232 12. Chapter 11 : Enhancing resilience of our Nation's critical infrastructure - p. Page 240 13. Chapter 12 : Light Water Reactor Sustainability Program—Enabling the continued operation of existing US nuclear reactors - p. Page 246 14. Chapter 13 : Idaho National Laboratory (INL) microgrid testbeds - p. Page 257 15. Chapter 14 : Modeling and simulation of advanced manufacturing techniques using MOOSE and MALAMUTE - p. Page 262 16. Chapter 15 : Critical infrastructure modeling: Resilience and the ability to adapt and maneuver to threats - p. Page 284 17. Introduction - p. Page 302 18. Chapter 16 : Status and trends of kinetic Monte Carlo simulation in reactor physics - p. Page 302 19. Chapter 17 : Inverse uncertainty quantification based on the modular Bayesian approach - p. Page 317 20. Chapter 18 : Modeling and simulation for security system design and evaluation - p. Page 328 21. Chapter 19 : Human system simulation laboratory for testing, evaluation, and validation of human performance☆ - p. Page 349 22. Index - p. Page 360
