Abstract

In 1975, the Atomic Energy Commission initiated the landmark Rasmussen study that led to the advent of Probabilistic Risk Assessment (PRA) in the nuclear industry. Over the years, PRA has grown into a well-established technical discipline with a wide range of applications in diverse industries for the design, operation, and regulatory oversight of complex technological systems. In both the research and the application of PRA, the nuclear industry continues to be the leader. Last year’s disaster at the Japanese Fukushima Daiichi Power Plant is an unfortunate reminder of the vital importance of comprehensive PRA in the nuclear industry. Classical PRA primarily uses statistical data and expert opinions to estimate the probabilities of basic events in Fault Trees (FTs) and Event Trees (ETs) in order to calculate system-wide risks. Recently, and due to a broader role envisioned for PRA in various risk-informed applications, there has been a gradual shift in interest towards modeling the underlying failure mechanisms of the elements of risk scenarios. As a result, PRA is expanding its horizons into such fields as reliability engineering, cognitive psychology, organizational behavior, and computer science. This talk will describe the two emerging causal extensions of PRA models suitable for constructing a hybrid PRA. The first extension results from a study on the incorporation of human, social and organizational failure mechanisms into PRA. The proposed modeling techniques and theories are applied for maintenance safety. The second extension relates to a research study on the integration of physical failure mechanisms into PRA and its application for nuclear power safety and for the advancement of the treatment of dependent failures (i.e. Common Cause Failures). These two lines of research provide some of the building blocks for developing a fully hybrid PRA capable of covering the dynamic interactions of diverse risk-contributing factors. The talk will offer paradigms of the state-of-the-art combination of deterministic and probabilistic modeling techniques for the incorporation of underlying failure phenomena into risk assessments of complex systems.

Bio

Dr. Zahra Mohaghegh is the founder and principal research scientist at Soteria Consultants, a startup risk management consulting enterprise which supports proactive decision making for technological systems by collaborating with a cross-disciplinary group of experts from regulatory agencies, academia, national labs, and industry. She received the George Apostolakis fellowship in 2012 which was awarded for her achievement in the field of Risk Assessment. Her contribution to modeling large-scale complex systems was also recognized by the Zonta International Amelia Earhart Award.      Dr. Mohaghegh earned her M.Sc. and Ph.D. in Reliability Engineering from the University of Maryland (UMD) and worked as a post-doctoral research associate at the Center for Risk and Reliability at UMD. She is interested in promoting research and education in risk and reliability analysis. Examples include her studies on failure phenomenology and causal modeling, the treatment of dependent failures, Probabilistic Physics-Of-Failures (PPOF), risk-informed decision making, Bayesian inference, and organizational causes of human error. Her research has been of interest to regulatory agencies such as the U.S. Federal Aviation Administration (FAA) and the U.S. Nuclear Regulatory Commission (NRC). Dr. Mohaghegh is the author of the book, Socio-Technical Risk Analysis, and over 20 journal and conference papers on risk analysis. She has instructed a number of courses in advanced methods of reliability and risk analysis, and taught the first risk management workshop, sponsored by the Nuclear Energy Institute (NEI), at the 2011 U.S. Women in Nuclear conference. She has been on technical committees for international conferences and as a technical reviewer for journals. She is a member of the American Nuclear Society, Society for Risk Analysis, Society of Women Engineers, and American Society of Mechanical Engineers. Dr. Mohaghegh holds a B.S. in Mechanical Engineering.