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A new accident causation model based on information flow and its application in Tianjin Port fire and explosion accident

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  • Wu, Chao
  • Huang, Lang

Abstract

Accident causation models can provide a framework of reference to help understand and explain how an accident occurs. The role of information flow (IF) in accident causation is profound. In this study, an accident causation model was developed and then validated to address the relevant accident-causing mechanisms based on IF. Three steps were followed to develop the new model. Firstly, the roles of IF in system safety were confirmed. Secondly, the principles of accident-causing mechanisms were addressed from the perspective of IF. Thirdly, the system safety factors were classified at the micro-, meso- and macro- levels. At each level, these factors were further divided into six information-centric aspects. The structure of the new model, known as the IF-based Accident-causing Model (IFAM), was constructed based on the hypothesis that any breakdown of IF at each level or between two adjacent levels of a system is the potential causation of accidents. To demonstrate the viability of IFAM, the Tianjin Port fire and explosion accident, which shocked the world and aroused widespread media attention, was selected as the case in this study. Results showed that this model can provide a new idea and method for accident analysis, as well as a new perspective for system safety investigation.

Suggested Citation

  • Wu, Chao & Huang, Lang, 2019. "A new accident causation model based on information flow and its application in Tianjin Port fire and explosion accident," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 73-85.
  • Handle: RePEc:eee:reensy:v:182:y:2019:i:c:p:73-85
    DOI: 10.1016/j.ress.2018.10.009
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    References listed on IDEAS

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    2. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    3. Tan, Samson & Moinuddin, Khalid, 2019. "Systematic review of human and organizational risks for probabilistic risk analysis in high-rise buildings," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 233-250.
    4. Huimin Guo & Shugang Li & Lianhua Cheng, 2022. "Research on the Causes of Gas Explosion Accidents Based on Safety Information Transmission," IJERPH, MDPI, vol. 19(16), pages 1-13, August.
    5. Guirong Zhang & Wei Feng & Yu Lei, 2022. "Human Factor Analysis (HFA) Based on a Complex Network and Its Application in Gas Explosion Accidents," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    6. Chen, Yuanjiang & Feng, Wei & Jiang, Zhiqiang & Duan, Lingling & Cheng, Shuangyi, 2021. "An accident causation model based on safety information cognition and its application," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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