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.

Item Type:	Refereed Article
Keywords:	event tree, fault tree, hierarchical Bayesian modeling, major accidents, probabilistic risk analysis
Research Division:	Engineering
Research Group:	Engineering practice and education
Research Field:	Risk engineering
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in engineering
UTAS Author:	Yu, H (Mr Hongjiang Yu)
UTAS Author:	Khan, F (Professor Faisal Khan)
ID Code:	125800
Year Published:	2017
Web of Science® Times Cited:	34
Deposited By:	NC Maritime Engineering and Hydrodynamics
Deposited On:	2018-05-07
Last Modified:	2018-08-22
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