Mathematical tools for probabilistic risk analysis

Probabilistic risk analysis aims to quantify the risk caused by high technology installations.

Increasingly, such analyses are being applied to a wider class of systems in which problems such as lack of data, complexity of the systems, uncertainty about consequences, make a classical statistical analysis difficult or impossible.

The authors discuss the fundamental notion of uncertainty, its relationship with probability, and the limits to the quantification of uncertainty.

Drawing on extensive experience in the theory and applications of risk analysis, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk.

They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation.

The relationship of risk analysis with decision making is highlighted in chapters on influence diagrams and decision theory.

Finally, the difficulties of choosing metrics to quantify risk, and current regulatory frameworks are discussed.