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A flexible hierarchical Bayesian modeling technique for risk analysis of major accidents
journal contribution
posted on 2023-05-19, 17:52 authored by Hongjiang Yu, Faisal KhanFaisal Khan, Veitch, BSafety 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.
History
Publication title
Risk AnalysisVolume
37Issue
9Pagination
1668-1682ISSN
0272-4332Department/School
Australian Maritime CollegePublisher
Wiley-Blackwell Publishing LtdPlace of publication
USARights statement
Copyright 2017 Society for Risk AnalysisRepository Status
- Restricted