Overview
- Provides quantitative risk methodology documentation for PSA
- Includes current “hot” topics in PSA techniques
- Can be used as supplemental reading for PSA courses
Part of the book series: Topics in Safety, Risk, Reliability and Quality (TSRQ, volume 38)
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Table of contents (4 chapters)
Keywords
About this book
Probabilistic Safety Assessment (PSA) is a structured, comprehensive, and logical analysis method aimed at identifying and assessing risks in complex technological systems, such as the nuclear power plants. It is also known as probabilistic risk assessment – PRA. This book presents the theoretical basis to understand the numerous and complex aspects that are covered by PSA and it will help the reader to better understand and to effectively manage risks. The book provides PSA methods and techniques and it includes recommended procedures that are based on the experience of the authors and applicable to different levels and types of PSA that are used for nuclear power plants applications. It can be used as extra reading for PSA courses for practitioners and it provides quantitative risk methodology documentation for PSA.
Authors and Affiliations
Bibliographic Information
Book Title: Selected Topics in Probabilistic Safety Assessment
Book Subtitle: Methodology and Practice in Nuclear Power Plants
Authors: Dan Serbanescu, Anatoli Paul Ulmeanu
Series Title: Topics in Safety, Risk, Reliability and Quality
DOI: https://doi.org/10.1007/978-3-030-40548-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-40547-2Published: 20 February 2020
Softcover ISBN: 978-3-030-40550-2Published: 20 February 2021
eBook ISBN: 978-3-030-40548-9Published: 19 February 2020
Series ISSN: 1566-0443
Series E-ISSN: 2215-0285
Edition Number: 1
Number of Pages: XX, 159
Number of Illustrations: 127 b/w illustrations, 91 illustrations in colour
Topics: Quality Control, Reliability, Safety and Risk, Nuclear Energy, Probability Theory and Stochastic Processes, Mathematical Logic and Foundations