Prevention and control strategy of coal mine water inrush accident based on case-driven and Bow-tie-Bayesian model

Xin Tong, Xuezhao Zheng, Yongfei Jin, Beibei Dong, Qingyun Liu and Yuan Li

Energy, 2025, vol. 320, issue C

Abstract: Preventing and controlling coal mine water inrush accidents is a prerequisite for ensuring safe mining and a stable energy supply. In order to solve the problems of accident chain uncertainty reasoning and a priori information ambiguity in the risk analysis, the macroscopic causative mechanism was explored based on 154 cases, a causative system was constructed by using the Bow-tie model and the topological network, and a fuzzy Bayesian risk assessment model was developed. Through causal reasoning, diagnostic reasoning, and sensitivity analysis, the accident probability was determined, and causal mechanism was revealed. The case study showed that the accident probability in a mine working face is 0.84 %; the probabilities of accident induced by the four combined paths are more than 900 % higher than that of the normal situation, and paths are the main object of accident prevention. The accident development dynamic rules under the safety barriers was revealed. Finally, the model validation was carried out with the Zhaojin coal mine water inrush accident as a sample, and the result showed that the accident probability is 9 %, and the critical causal paths were basically consistent with the accident investigation. The method can provide technical support for decision-makers to effectively prevent accidents.

Keywords: Accident prevention strategy; Risk assessment; Bow-tie model; Fuzzy Bayesian; Topological network; Model application (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:320:y:2025:i:c:s0360544225009545

DOI: 10.1016/j.energy.2025.135312

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