A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

Probabilistic risk and hazard assessments are applied to a wide range of engineering systems, mainly for regulatory reasons needed for development consent, system certification and occupational health and safety issues. The purpose of this book is to raise awareness of the limitations, uncertainties and other issues inherent in probabilistic risk analysis procedures. Probabilistic Risk Assessment of Engineering Systems describes: the importance of probabilistic risk assessment in decision making, i.e. risk management; types of risk and probabilistic risk analysis procedures; data needed for the conduct of probabilistic risk analysis; and acceptable/tolerable risk and other risk acceptance criteria. In essence, the book provides a multi-disciplinary and integrated explanation of risk assessment procedures that will enable the non-specialist reader to gain valuable insights into the development of risk analysis procedures. Practising engineers and graduate engineering students across a range of disciplines will find this book immensely useful.

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described. A powerful feature of OpenBUGS is its automatic selection of an appropriate MCMC sampling scheme for a given problem. The authors provide analysis “building blocks” that can be modified, combined, or used as-is to solve a variety of challenging problems. The MCMC approach used is implemented via textual scripts similar to a macro-type programming language. Accompanying most scripts is a graphical Bayesian network illustrating the elements of the script and the overall inference problem being solved. Bayesian Inference for Probabilistic Risk Assessment also covers the important topics of MCMC convergence and Bayesian model checking. Bayesian Inference for Probabilistic Risk Assessment is aimed at scientists and engineers who perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.

Electrical Engineering Probabilistic Risk Assessment and Management for Engineers and Scientists Second Edition "State of the art in risk analysis...[this book] projects the technology into the next decade. Congratulations to the authors on a virtuoso performance." -Charles Donaghey, University of Houston "A very useful reference to the academic and government communities, and junior engineering staff within nuclear, chemical, transportation, aerospace, and other industries." -Yovan Lukic, Arizona Public Service Company As the demands of government agencies and insurance companies escalate, societal risk assessment and management become increasingly critical to the development and use of engineered systems in the full range of industrial installations. Packed with real-world examples and practical mathematical and statistical methods for large, complex systems, this definitive text and sourcebook gives you the guidance you need for thorough and conclusive study. You'll find new and updated coverage of all the key topics related to risk analysis: * Probabilistic nature of risk * Qualitative and quantitative risk assessments * System decomposition * Legal and regulatory risks * And much more! The authors also provide end-of-chapter problems and a course outline. Complete with a new, automated, fault tree synthesis method using semantic networks. Probabilistic Risk Assessment and Management for Engineers and Scientists, Second Edition will be of value to anyone working with engineered systems. Also of Interest from IEEE Press... Successful Patents and Patenting for Engineers and Scientists edited by Michael A. Lechter, Esq. 1995 Softcover 432 pp IEEE Order No. PP4478 ISBN 0-7803-1086-1 Metric Units and Conversion Charts A Metrication Handbook for Engineers, Technologists, and Scientists Second Edition Theodore Wildi 1995 Softcover 144 pp IEEE Order No. PP4044 ISBN 0-7803-1050-0 The Probability Tutoring Book An Intuitive Course for Engineers and Scientists (And Everyone Else!) Carol Ash 1993 Softcover 480 pp IEEE Order No. PP2881 ISBN 0-7803-1051-9

This book proposes a new approach to dynamic and online risk assessment of automated and autonomous marine systems, taking into account different environmental and operational conditions. The book presents lessons learnt from dynamic positioning incidents and accidents, and discusses the challenges of risk assessment of complex systems. The book begins by introducing dynamic and online risk assessment, before presenting automated and autonomous marine systems, as well as numerous dynamic positioning incidents. It then discusses human interactions with technology and explores how to quantify human error. Dynamic probabilistic risk assessment and online risk assessment are both considered fully, including case studies with the application of assisting operators in decision making in emergency situations. Finally, areas for future research are suggested. This practical volume offers tools and methodologies to help operators make better decisions and improve the safety of automated and autonomous marine systems. It provides a guideline for researchers and practitioners to perform dynamic probabilistic and online risk assessment, which also should be applicable to other complex systems outside the marine and maritime domain, such as nuclear power plants, chemical processes, autonomous transport systems, and space shuttles.

This book is a methodological approach to the goal-based safety design procedure that will soon be an international requirement. This is the first single volume book to describe how to satisfy safety goals by modern reliability engineering. Its focus is on the quantitative aspects of the international standards using a methodological approach. Case studies illustrate the methodologies presented.

A collection of papers presented at the PSAM 7 – ESREL ’04 conference in June 2004, reflecting a wide variety of disciplines, such as principles and theory of reliability and risk analysis, systems modelling and simulation, consequence assessment, human and organisational factors, structural reliability methods, software reliability and safety, insights and lessons from risk studies and management/decision making. This volume covers both well-established practices and open issues in these fields, identifying areas where maturity has been reached and those where more development is needed.