Risk-informed methods and applications in nuclear and energy engineering : modeling, experimentation, and validation /

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...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Other Authors:	Smith, Curtis, Mandelli, Diego, Le Blanc, Katya
Format:	eBook
Language:	English
Published:	London ; San Diego, CA : Academic Press, an imprint of Elsevier, [2024]
Subjects:	Nuclear engineering > Safety measures. Nuclear energy > Safety measures. Génie nucléaire > Sécurité > Mesures. Énergie nucléaire > Sécurité > Mesures. Nuclear energy > Safety measures Nuclear engineering > Safety measures Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Intro
Risk-Informed Methods and Applications in Nuclear and Energy Engineering: Modeling, Experimentation, and Validation
Copyright
Contents
Contributors
Chapter 1: Introduction
Contents
1.1. Probabilistic safety assessment scope
1.1.1. Summary of probabilistic safety assessment approach
Classical probabilistic safety assessment approaches
Event tree models
Fault tree models
Dynamic methods
References
Part 1: Risk and reliability
Chapter 2: Improving nuclear power plant flooding hazard analysis through component performance experiments, fragility mo ...
Contents
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
Dedication
References
Chapter 3: Severe accidents in light water reactors
Contents
3.1. Introduction
3.2. Overview of severe accident phenomena
3.2.1. Initiation of fuel damage
3.2.2. Stages of accident progression
3.2.3. Ex-vessel progression
3.2.4. Containment integrity
3.3. Severe accident research
3.3.1. Radionuclide release and transport
3.3.2. Development and validation of models for the analysis of key severe accident phenomena
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
Contents
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&amp
C systems
Contents
5.1. Introduction.
5.2. Digital assets and I&amp
C systems in nuclear reactors
5.3. Cyber risk management
5.3.1. Cyber risk analysis
5.3.2. Consequence
5.3.3. Threat
5.3.4. Vulnerability
5.3.5. Cyber risk evaluation
5.3.6. Cyber risk treatment
5.4. Cyber-informed engineering (CIE)
5.5. Conclusions
Acknowledgment
References
Chapter 6: Perspective on attributes of modeling and simulation tools for effective reactor core analysis
Contents
6.1. Introduction
6.2. Reactor core analysis tools
6.2.1. Context on scope of M&amp
S tools
6.2.2. Neutronics
6.2.3. Thermal-hydraulics
6.2.4. Fuel performance
6.2.5. Multiphysics
6.3. Conclusions
References
Chapter 7: Coupled multiphysics simulations in nuclear reactor design and safety
Contents
7.1. Introduction
7.2. Multiphysics coupling solution techniques
7.2.1. Notation
7.2.2. Operator-splitting
7.2.3. Newton and Newton-like techniques
7.3. A pedagogical numerical example
7.4. Draining transient in the molten salt fast reactor
7.4.1. Description of the MSFR
7.4.2. Description of the transient
7.4.3. Stages of the transient
7.4.4. Numerical model
7.4.5. Results
7.5. Conclusions and outlook
References
Chapter 8: Data-driven prognostics and health management (PHM) for predictive maintenance of industrial components and&amp
s
Contents
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
8.4.1. Model-based approaches
8.4.2. Data-driven approaches
8.5. Decision-making based on PHM
8.5.1. Decision-making for safety
8.5.2. Decision-making for business
8.5.3. Decision-making for O&amp
M
8.6. Applications
8.6.1. A data-driven approach: Ensemble of echo-state networks.
8.6.2. A data-driven approach: Deep neural network
8.7. Conclusions
References
Chapter 9: The history of risk-informing reactor safety regulation*
Contents
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-Besses 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
Contents
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
10.7.1. Classical probabilistic risk analysis BWR SBO data
10.7.2. Comparison approach
10.7.3. Classical probabilistic risk analysis event tree restructuring
10.7.4. Dynamic probabilistic risk analysis data processing
10.8. Integration of classical probabilistic risk analysis models into dynamic probabilistic risk analysis
10.9. Conclusions
References.
Part 2: Experiments and validation
Chapter 11: Enhancing resilience of our Nation's critical infrastructure
Contents
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
Contents
12.1. Introduction
12.1.1. Research to enable sustainability
12.2. Sustaining the existing fleet
12.2.1. Enhancing the economic competitiveness of the existing fleet
12.2.1.1. Research to reduce operating costs and improve efficiencies to enhance economic competitiveness
12.2.1.2. Research to enable diversification of revenue and expand to markets beyond electricity
12.2.2. Delivering the scientific basis for continued safe operation
12.2.2.1. Understanding and managing the aging and performance of key materials for long-term operation
12.2.2.2. Addressing aging and obsolescence of plant technologies
12.3. Conclusions
References
Chapter 13: Idaho National Laboratory (INL) microgrid testbeds
Contents
13.1. Background
13.2. Experimental microgrid
Chapter 14: Modeling and simulation of advanced manufacturing techniques using MOOSE and MALAMUTE
Contents
14.1. Introduction
14.2. Advanced sintering techniques
14.2.1. Microstructural evolution
14.2.2. Engineering-scale process model
14.2.3. Multiscale modeling approach
14.3. Laser-based additive manufacturing processes
14.3.1. Element activation capability
14.3.2. MultiApp modeling design
14.3.3. Level set method
14.3.4. Arbitrary Lagrangian-Eulerian capability
14.3.5. Microstructure evolution and multiscale approach
14.4. Conclusions
Acknowledgments
References.
Chapter 15: Critical infrastructure modeling: Resilience and the ability to adapt and maneuver to threats
Contents
15.1. Introduction
15.2. Resilience and complexity
15.2.1. Control system complexity
15.2.2. Cyber system complexity
15.2.3. Human system complexity
15.3. Resilience manifold
15.3.1. Manifold description
15.3.2. Resilience manifold example
15.4. Special topic: Cyber resilience
15.5. Summary
References
Further reading
Part 3: Methods in modeling and simulation
Chapter 16: Status and trends of kinetic Monte Carlo simulation in reactor physics
Contents
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
Acknowledgments
References
Chapter 17: Inverse uncertainty quantification based on the modular Bayesian approach
Contents
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
Contents
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*
Contents
19.1. Introduction
19.2. HSSL description
19.3. Display hardware and simulation models
19.4. Human performance measurement tools
19.4.1. Operator performance
19.4.2. Supplemental human performance measures
Operator SA
Operator workload
Eye tracking
19.5. Experts
19.6. Research in the HSSL
19.7. Conclusion
References
Index.