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Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model

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  • Changfeng Yuan
  • Hui Cui
  • Bin Tao
  • Siming Ma

Abstract

From the perspective of the safety of emergency process, in this paper, we put forward a new analysis method of cause factors based on fault tree analysis and modified Bayesian network in emergency process of fire accident for oil–gas storage and transportation. Nineteen cause factors are found based on the statistical analysis of actual accident cases. We adopt fault tree analysis method and Bayesian network model to analyze cause factors qualitatively and quantitatively. In order to more accurately determine the quantitative influencing degree of each cause factor, the conditional probabilities in Bayesian network are modified by using expert scoring method and modified Bayesian network model is established. Finally, the proposed method is applied to analyze cause factors in emergency process of two practical accident cases. Research results have an important scientific significance to reveal evolution mechanism of secondary accidents in emergency process and ensure system safety in whole life cycle.

Suggested Citation

  • Changfeng Yuan & Hui Cui & Bin Tao & Siming Ma, 2018. "Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model," Energy & Environment, , vol. 29(5), pages 802-821, August.
    • Handle: RePEc:sae:engenv:v:29:y:2018:i:5:p:802-821
    DOI: 10.1177/0958305X18760222
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    References listed on IDEAS

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    1. Hu-Chen Liu & Jian-Xin You & Shouming Chen & Yi-Zeng Chen, 2016. "An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty," IISE Transactions, Taylor & Francis Journals, vol. 48(11), pages 1027-1042, November.
    2. Hu-Chen Liu & Yi-Zeng Chen & Jian-Xin You & Hui Li, 2016. "Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 805-816, August.
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    1. Sorrentino, Marco & Bruno, Marco & Trifirò, Alena & Rizzo, Gianfranco, 2019. "An innovative energy efficiency metric for data analytics and diagnostics in telecommunication applications," Applied Energy, Elsevier, vol. 242(C), pages 1539-1548.

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