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Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations
journal contributionposted on 2023-05-18, 03:09 authored by Ferdous, R, Faisal KhanFaisal Khan, Sadiq, R, Amyotte, P, Veitch, B
Quantitative risk analysis (QRA) is a systematic approach for evaluating likelihood, consequences, and risk of adverse events. QRA based on event (ETA) and fault tree analyses (FTA) employs two basic assumptions. The first assumption is related to likelihood values of input events, and the second assumption is regarding interdependence among the events (for ETA) or basic events (for FTA). Traditionally, FTA and ETA both use crisp probabilities; however, to deal with uncertainties, the probability distributions of input event likelihoods are assumed. These probability distributions are often hard to come by and even if available, they are subject to incompleteness (partial ignorance) and imprecision. Furthermore, both FTA and ETA assume that events (or basic events) are independent. In practice, these two assumptions are often unrealistic. This article focuses on handling uncertainty in a QRA framework of a process system. Fuzzy set theory and evidence theory are used to describe the uncertainties in the input event likelihoods. A method based on a dependency coefficient is used to express interdependencies of events (or basic events) in ETA and FTA. To demonstrate the approach, two case studies are discussed. Â© 2010 Society for Risk Analysis.
Publication titleRisk Analysis
Department/SchoolAustralian Maritime College
PublisherWiley-Blackwell Publishing, Inc.
Place of publicationUnited States
Socio-economic ObjectivesEnvironmentally sustainable mineral resource activities not elsewhere classified