Risk Analysis in Engineering
Techniques, Tools, and Trends
1st Edition
Published on 27. April 2016
424 pages
978-1-040-06297-5 (ISBN)
Description
Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p
Reviews / Votes
"... this book contains the most used procedures and practices particularly in conducting probabilistic risk assessments of complex systems such nuclear power plants. One of the special feature of this gook is the inclusion of several worked out examples in the text and also a large number of exercises at the end of each chapters. This feature makes it very useful for the undergraduate, graduate students, who would like to study the subject of risk modeling, assessment and management as a part of their curricula. ... the reviewer would like to recommend this book to all those practicing engineers, students, teachers, and researchers, who would like to make in depth study of the probabilistic risk assessment and associated problems and are looking for their solutions. This is a most comprehensive treatment of the subject."- K. B. Misra, in International Journal of Performability Engineering, (IJPE), July 2006
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
ISBN-13
978-1-040-06297-5 (9781040062975)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
01/2006
1st Edition
CRC Press
€240.70
Shipment within 15-20 days
Content
Introduction and Definitions. Elements of Risk Assessment. Probabilistic Risk Assessment. Performance Assessment: Data and Modeling. Uncertainty Analysis. Identifying, Ranking, and Predicting Contributors to Risk. Risk Acceptance Criteria. Decision Making Techniques. Risk Communication.
