Citation

Yu H, Khan F, Veitch B. Risk Anal. 2017; 37(9): 1668-1682.

Affiliation

Centre for Risk, Integrity and Safety Engineering (CRISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St John's, NL, Canada.

Copyright

(Copyright © 2017, Society for Risk Analysis, Publisher John Wiley and Sons)

DOI

10.1111/risa.12736

PMID

28244169

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.

© 2017 Society for Risk Analysis.

Language: en

Keywords

Event tree; fault tree; hierarchical Bayesian modeling; major accidents; probabilistic risk analysis