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

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  • Hongyang Yu
  • Faisal Khan
  • Brian Veitch

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.

Suggested Citation

  • Hongyang Yu & Faisal Khan & Brian Veitch, 2017. "A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1668-1682, September.
  • Handle: RePEc:wly:riskan:v:37:y:2017:i:9:p:1668-1682
    DOI: 10.1111/risa.12736
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    References listed on IDEAS

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    8. BahooToroody, Ahmad & De Carlo, Filippo & Paltrinieri, Nicola & Tucci, Mario & Van Gelder, P.H.A.J.M., 2020. "Bayesian regression based condition monitoring approach for effective reliability prediction of random processes in autonomous energy supply operation," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    9. Guizhen Zhang & Vinh V. Thai & Adrian Wing‐Keung Law & Kum Fai Yuen & Hui Shan Loh & Qingji Zhou, 2020. "Quantitative Risk Assessment of Seafarers’ Nonfatal Injuries Due to Occupational Accidents Based on Bayesian Network Modeling," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 8-23, January.
    10. Yu, Jin-Zhu & Whitman, Mackenzie & Kermanshah, Amirhassan & Baroud, Hiba, 2021. "A hierarchical Bayesian approach for assessing infrastructure networks serviceability under uncertainty: A case study of water distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

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