title: A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents.
abstract: Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation-based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source-to-source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.
authors.affiliation: Centre for Risk, Integrity and Safety Engineering (CRISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St John's, NL, Canada.|National Centre for Maritime Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, TAS, Australia.
authors.forename: Hongyang
authors.initials: H
authors.lastname: Yu
authors.affiliation: Centre for Risk, Integrity and Safety Engineering (CRISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St John's, NL, Canada.|National Centre for Maritime Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, TAS, Australia.
authors.forename: Faisal
authors.initials: F
authors.lastname: Khan
authors.affiliation: Centre for Risk, Integrity and Safety Engineering (CRISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St John's, NL, Canada.
authors.forename: Brian
authors.initials: B
authors.lastname: Veitch
keywords: Event tree; fault tree; hierarchical Bayesian modeling; major accidents; probabilistic risk analysis