A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents. Issue 9 (28th February 2017)

• Record Type: Journal Article
• Authors: Yu, Hongyang; Khan, Faisal; Veitch, Brian
• Is Part Of: Risk analysis. Volume 37:Issue 9(2017)
• Page Start: 1668
• Page End: 1682
• Publication Date: 2017-02-28
• Subjects: Event tree -- fault tree -- hierarchical Bayesian modeling -- major accidents -- probabilistic risk analysis; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12736
• Languages: English
• ISSNs: 0272-4332

Abstract

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.