Decisions under Uncertainty Probabilistic Analysis for Engineering Decisions [Paperback]

Risk assessment theory and practice for graduate engineering students, practising engineers, designers and project managers, first published in 2005.Risk assessment is a critical part of every engineer's role, whether it is simply to determine the likelihood of failure of a new product within the warranty period, or the potential cost, human and financial, of the catastrophic failure of a bridge. This book helps the reader to understand the tradeoffs between time, costs and risk in an engineering setting, and includes a wide range of case studies and worked examples. Equally valuable for graduate students, practising engineers, designers and project managers.Risk assessment is a critical part of every engineer's role, whether it is simply to determine the likelihood of failure of a new product within the warranty period, or the potential cost, human and financial, of the catastrophic failure of a bridge. This book helps the reader to understand the tradeoffs between time, costs and risk in an engineering setting, and includes a wide range of case studies and worked examples. Equally valuable for graduate students, practising engineers, designers and project managers.To better understand the core concepts of probability and to see how they affect real-world decisions about design and system performance, engineers and scientists might want to ask themselves the following questions: What exactly is meant by probability? What is the precise definition of the 100-year load and how is it calculated? What is an extremal probability distribution? What is the Bayesian approach? How is utility defined? How do games fit into probability theory? What is entropy? How do I apply these ideas in risk analysis? Starting from the most basic assumptions, this book develops a coherent theory of probability and broadens it into applications in decision theory, design, and risk analysis. This book is written for engineers and scientists interested in probability and risk. It cl£ã