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Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents

Author

Listed:
  • Yunmeng Lu

    (Beijing Institute of Technology, School of Management and Economics, Beijing 100081, China)

  • Tiantian Wang

    (Beijing Institute of Technology, School of Management and Economics, Beijing 100081, China)

  • Tiezhong Liu

    (Beijing Institute of Technology, School of Management and Economics, Beijing 100081, China)

Abstract

The chemical industry has made great contributions to the national economy, but frequent chemical plant explosion accidents (CPEAs) have also caused heavy property losses and casualties, as the CPEA is the result of interaction of many related risk factors, leading to uncertainty in the evolution of the accident. To systematically excavate and analyze the underlying causes of accidents, this paper first integrates emergency elements in the frame of orbit intersection theory and proposes 14 nodes to represent the evolution path of the accident. Then, combined with historical data and expert experience, a Bayesian network (BN) model of CPEAs was established. Through scenario analysis and sensitivity analysis, the interaction between factors and the impact of the factors on accident consequences was evaluated. It is found that the direct factors have the most obvious influence on the accident consequences, and the unsafe conditions contribute more than the unsafe behaviors. Furthermore, considering the factor chain, the management factors, especially safety education and training, are the key link of the accident that affects unsafe behaviors and unsafe conditions. Moreover, effective government emergency response has played a more prominent role in controlling environmental pollution. In addition, the complex network relationship between elements is presented in a sensitivity index matrix, and we extracted three important risk transmission paths from it. The research provides support for enterprises to formulate comprehensive safety production management strategies and control key factors in the risk transmission path to reduce CPEA risks.

Suggested Citation

  • Yunmeng Lu & Tiantian Wang & Tiezhong Liu, 2020. "Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents," IJERPH, MDPI, vol. 17(15), pages 1-20, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5364-:d:389825
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    References listed on IDEAS

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    1. Lina Han & Qing Ma & Feng Zhang & Yichen Zhang & Jiquan Zhang & Yongbin Bao & Jing Zhao, 2019. "Risk Assessment of An Earthquake-Collapse-Landslide Disaster Chain by Bayesian Network and Newmark Models," IJERPH, MDPI, vol. 16(18), pages 1-17, September.
    2. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    3. Tiezhong Liu & Hubo Zhang & Xiaowei Li & Haiyan Li, 2017. "Effects of organization factors on flood-related Natechs in urban areas of China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(1), pages 355-365, August.
    4. Li, Mei & Liu, Zixian & Li, Xiaopeng & Liu, Yiliu, 2019. "Dynamic risk assessment in healthcare based on Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 327-334.
    5. Rongchen Zhu & Xiaofeng Hu & Xin Li & Han Ye & Nan Jia, 2020. "Modeling and Risk Analysis of Chemical Terrorist Attacks: A Bayesian Network Method," IJERPH, MDPI, vol. 17(6), pages 1-23, March.
    6. Khakzad, Nima, 2015. "Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 263-272.
    7. 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.
    8. Jun Zhang & Haifeng Bian & Huanhuan Zhao & Xuexue Wang & Linlin Zhang & Yiping Bai, 2020. "Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines," IJERPH, MDPI, vol. 17(6), pages 1-17, March.
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    Cited by:

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    2. Liu, Jinbiao & Tan, Lingling & Ma, Yaping, 2024. "An integrated risk assessment method for urban areas due to chemical leakage accidents," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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