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Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines

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  • Jinjia Zhang
  • Kaili Xu
  • Greg You
  • Beibei Wang
  • Lei Zhao

Abstract

The coal mine production industry is a complex sociotechnical system with interactive relationships among several risk factors. Currently, causation analysis of gas explosion accidents is mainly focused on the aspects of human error and equipment fault, while neglecting the interactive relationships among risk factors. A new method is proposed through risk coupling. First, the meaning of risk coupling of a gas explosion is defined, and types of risk coupling are classified. Next, the coupled relationship and coupled effects among risk factors are explored through combining the interpretative structural modeling (ISM) and the NK model. Twenty‐eight representative risk factors and 16 coupled types of risk factors are obtained through analysis of 332 gas explosion accidents in coal mines in China. Through the application of the combined ISM–NK model, an eight‐level hierarchical model of risk coupling of a gas explosion accident is established, and the coupled degrees of different types of risk coupling are assessed. The hierarchical model reveals that two of the 28 risk factors, such as state policies, laws, and regulations, are the root risk factors for gas explosions; nine of the 28 risk factors, such as flame from blasting, electric spark, and local gas accumulation, are direct causes of gas explosions; whereas 17 of the risk factors, such as three‐violation actions, ventilation system, and safety management, are indirect ones. A quantitative analysis of the NK model shows that the probability of gas explosion increases with the increasing number of risk factors. Compared with subjective risk factors, objective risk factors have a higher probability of causing gas explosion because of risk coupling.

Suggested Citation

  • Jinjia Zhang & Kaili Xu & Greg You & Beibei Wang & Lei Zhao, 2019. "Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1634-1646, July.
    • Handle: RePEc:wly:riskan:v:39:y:2019:i:7:p:1634-1646
    DOI: 10.1111/risa.13311
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    Cited by:

    1. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Cailin Wang & Enliang Guo & Yongqiang Cao & Haishan Zhang & Ye Zhang, 2023. "Statistical characteristics of production safety accidents and its strategy implications for administrators in Inner Mongolia," 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. 117(1), pages 745-762, May.
    3. Yang, Yu & Chen, Dongjing, 2022. "Issues of corporate social responsibility in the mining industry: The case of China," Resources Policy, Elsevier, vol. 76(C).
    4. Shuicheng Tian & Junrui Mao & Hongxia Li, 2022. "Disaster-Causing Mechanism of Hidden Disaster-Causing Factors of Major and Extraordinarily Serious Gas Explosion Accidents in Coal Mine Goafs," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    5. Wanqing Wang & Shuran Lyu & Yudong Zhang & Shuqi Ma, 2019. "A Risk Assessment Model of Coalbed Methane Development Based on the Matter-Element Extension Method," Energies, MDPI, vol. 12(20), pages 1-30, October.
    6. 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.
    7. Peng Wan & Junwu Wang & Ye Liu & Qizhi Lu & Chunbao Yuan, 2022. "On Risk Probability of Prefabricated Building Hoisting Construction Based on Multiple Correlations," Sustainability, MDPI, vol. 14(8), pages 1-18, April.
    8. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

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