A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents

作者：Yu Hongyang; Khan Faisal^*; Veitch Brian

来源：Risk Analysis, 2017, 37(9): 1668-1682.

DOI：10.1111/risa.12736

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

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.

• 出版日期2017-9