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Risk and Reliability Analysis

In: Risk and Reliability Analysis: Theory and Applications

Author

Listed:
  • Paolo Gardoni

    (University of Illinois at Urbana-Champaign)

Abstract

Natural and anthropogenic hazards pose significant risks to individuals and communities. Over the past few decades, risk and reliability analysis have gone from a specialty topic to a mainstream subject in engineering, becoming essential tools for informed decision making, hazard mitigation, and planning. This book presents the state-of-the-art in risk and reliability analysis with a unique collection of contributions from some of the foremost scholars in the field. Combining the most advanced analysis techniques with practical applications, this book is one of the most comprehensive and up-to-date references available on this subject, makes the state-of-the-art in risk and reliability analysis accessible to a large audience, and helps make risk and reliability analysis the rigorous foundation of engineering decision-making. The fundamental concepts needed to conduct risk and reliability analysis are covered in detail, providing readers with a sound understanding of the field and making the book a powerful tool for students, researchers and practitioners (engineering professionals and risk analysts) alike. The book is a tribute to Professor Armen Der Kiureghian, one of the fathers of modern risk and reliability analysis. During his career, Professor Der Kiureghian has made fundamental and revolutionary research contributions to this field. He has pioneered methods for safety and reliability assessment of complex structures and for stochastic seismic analysis of buildings, bridges and critical equipment. Many of his publications have become mandatory readings for the current and future generations of students, researchers and practitioners. The book is organized into six parts. Part I gives a general introduction of the book including a discussion of its goal and contributions, presents an overview of the field of risk and reliability analysis, and discusses the role of Armen Der Kiureghian in modern risk and reliability analysis. Part II focuses specifically on reliability analysis, and includes a description of efficient computational methods and their applications to some of the most complex real-life problems. Part III covers the subject of stochastic dynamics, presenting both methods and applications. Part IV discusses methods for sensitivity analysis and optimization in the context of risk and reliability analysis. Part V focuses on statistical analysis and the development of probabilistic models. Finally, Part VI covers life-cycle and resilience analysis as well as different financial tools for risk mitigation. While each part has a specific focus, many of the chapters build on and use the methods and techniques covered in some of the other parts of the book. Such links help understand the relation between the different subjects, which is needed for a thorough understanding of the topic of risk and reliability analysis.

Suggested Citation

  • Paolo Gardoni, 2017. "Risk and Reliability Analysis," Springer Series in Reliability Engineering, in: Paolo Gardoni (ed.), Risk and Reliability Analysis: Theory and Applications, pages 3-24, Springer.
  • Handle: RePEc:spr:ssrchp:978-3-319-52425-2_1
    DOI: 10.1007/978-3-319-52425-2_1
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Armin Tabandeh & Paolo Gardoni & Colleen Murphy, 2018. "A Reliability‐Based Capability Approach," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 410-424, February.
    3. Guidotti, Roberto & Gardoni, Paolo & Rosenheim, Nathanael, 2019. "Integration of physical infrastructure and social systems in communities’ reliability and resilience analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 476-492.
    4. Tabandeh, Armin & Sharma, Neetesh & Gardoni, Paolo, 2022. "Uncertainty propagation in risk and resilience analysis of hierarchical systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Sun, Bo & Gardoni, Paolo, 2019. "Directional search algorithm for hierarchical model development and selection," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 194-207.
    6. Ali Lenjani & Ilias Bilionis & Shirley J. Dyke & Chul Min Yeum & Ricardo Monteiro, 2020. "A resilience-based method for prioritizing post-event building inspections," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(2), pages 877-896, January.
    7. Chun, Junho, 2021. "Sensitivity analysis of system reliability using the complex-step derivative approximation," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    9. Chabridon, Vincent & Balesdent, Mathieu & Bourinet, Jean-Marc & Morio, Jérôme & Gayton, Nicolas, 2018. "Reliability-based sensitivity estimators of rare event probability in the presence of distribution parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 164-178.
    10. Byun, Ji-Eun & Zwirglmaier, Kilian & Straub, Daniel & Song, Junho, 2019. "Matrix-based Bayesian Network for efficient memory storage and flexible inference," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 533-545.
    11. Wang, Jinsheng & Xu, Guoji & Li, Yongle & Kareem, Ahsan, 2022. "AKSE: A novel adaptive Kriging method combining sampling region scheme and error-based stopping criterion for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    12. Yang, David Y. & Frangopol, Dan M., 2019. "Life-cycle management of deteriorating civil infrastructure considering resilience to lifetime hazards: A general approach based on renewal-reward processes," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 197-212.
    13. Tao, Longlong & Wu, Jie & Ge, Daochuan & Chen, Liwei & Sun, Ming, 2022. "Risk-informed based comprehensive path-planning method for radioactive materials road transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    14. Li, Pei-Pei & Zhang, Yi & Zhao, Yan-Gang & Zhao, Zhao & Cai, Enjian, 2023. "An information reuse-based method for reliability updating," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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