Probabilistic risk analysis: Foundations and methods (Q2716049)

Probabilistic risk analysis (PRA for short) is concerned with the quantification of risks, usually in the context of high technology installations. Typical examples come from the aerospace, nuclear or chemical industry and all involve events that (almost) never occur. This book on PRA has two major aims. One is to provide an introduction, both to the main tools used in PRA and to some recent developments in PRA modeling. The other is a thorough discussion of uncertainty to clarify both the scope and the limits of mathematical and especially probabilistic methods for its modeling and analysis. NEWLINENEWLINENEWLINEThe book consists of four parts subdivided into a total of 18 chapters. Part I gives an introduction to the subject of PRA with emphasis on its history, its scope and a list of resources and references. Part II contains theoretical issues and background material. This includes a detailed discussion of uncertainty and the basics about probability and statistical inference used later. Part III is about system analysis and quantification. It presents tools for modeling engineering systems and techniques to quantify the uncertainties appearing in them. The modeling aspects are mainly addressed in the three chapters on fault and event trees, fault tree analysis, and dependent failures. Quantification includes the four chapters on reliability data bases, expert opinion, human reliability, and software reliability. Part IV finally discusses uncertainty modeling and risk measurement. The focus here is on the importance as well as the modeling of dependent uncertainties, on optimal decisions under uncertainty and on the presentation and measurement of uncertainties and risks. The chapters in this part address decision theory; influence diagrams and belief nets, as techniques for representing high-dimensional distributions and decision problems; the increasingly important area of project risk management; probabilistic inversion techniques for uncertainty analysis; uncertainty analysis; and risk measurement and regulation, in particular with relation to mortality.