Probabilistic Physics of Failure Approach to Reliability: Modeling, Accelerated Testing, Prognosis and Reliability Assessment

Mohammad Modarres · Mehdi Amiri · Christopher Jackson

Jun 2017 · Kuthengiswe ngu-John Wiley & Sons

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The book presents highly technical approaches to the probabilistic physics of failure analysis and applications to accelerated life and degradation testing to reliability prediction and assessment. Beside reviewing a select set of important failure mechanisms, the book covers basic and advanced methods of performing accelerated life test and accelerated degradation tests and analyzing the test data. The book includes a large number of very useful examples to help readers understand complicated methods described. Finally, MATLAB, R and OpenBUGS computer scripts are provided and discussed to support complex computational probabilistic analyses introduced.

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Mohammad Modarres is Director, Center for Risk and Reliability and the Nicole Y. Kim Eminent Professor of Engineering, University of Maryland; M.S. (1977) and PhD (1980) in Nuclear Engineering from MIT, and M.S. in Mechanical Engineering also from MIT (1977). He has more than 400 papers in archival journals and proceedings of conferences, including several books and textbooks in various areas of nuclear safety, risk and reliability engineering. He is a University of Maryland Distinguished Scholar-Teacher and a fellow of the American Nuclear Society.

Mehdi Amiri is an adjunct professor in the Department of Mechanical Engineering, George Mason University; M.S. (2006) in Mechanical Engineering from University of Tehran, Iran and PhD (2011) in Mechanical Engineering from Louisiana State University (LSU). His main research interests include materials, failure prediction through simulation-based modeling of the microstructural defects, with current emphases on additively manufactured materials, and nondestructive evaluation and testing.

Christopher Jackson is the Acting Director of the Centre of Reliability and Resilience Engineering at the B. John Garrick Institute for the Risk Sciences, University of California, Los Angeles. He graduated with a PhD (2011) and MS (2007) in Reliability Engineering from the University of Maryland, a Masters of Military Studies (2012) from the Australian National University, and a Bachelor of Engineering (Mechanical 2001) from the University of New South Wales. His current research thrusts revolve around Bayesian analysis, big data analysis and complex system modelling.