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Risk assessment of coal and gas outburst in driving face based on finite interval cloud model

Author

Listed:
  • Guorui Zhang

    (China University of Mining and Technology
    China University of Mining and Technology)

  • Enyuan Wang

    (China University of Mining and Technology
    China University of Mining and Technology)

  • Zhonghui Li

    (China University of Mining and Technology
    China University of Mining and Technology)

  • Ben Qin

    (China University of Mining and Technology
    China University of Mining and Technology)

Abstract

Coal and gas outburst is one of the main disasters that seriously threaten workers’ safety during coal production. Timely identification and evaluation of the potential outburst before tunneling helps to implement the targeted control measures. Nevertheless, the influencing factors of outburst are so complex that there is no suitable index system and evaluation method available yet. In this paper, a more reasonable and complete index system (three categories of factors and 16 indicators) for outburst risk is established, in which, the risk level is divided into three levels. Then, the triangular fuzzy numbers are adopted to quantify the indicators and the logarithmic fuzzy preference programming method to calculate the weight. The cloud distribution under finite interval processing is generated based on cloud numerical characters of each indicator. In addition, the risk level is determined according to the calculation results of multi-index comprehensive membership degree. Finally, the entire evaluation system is applied to two excavated coal roadways for experiments, which show that the finite interval cloud model delivers a more objective and reasonable risk assessment. Five potential outburst threat areas of 58 excavation cycles evaluated show different degrees of outburst dynamic appearance, indicating a good relationship between the evaluation results and the actual risk. This method effectively considers the fuzziness and randomness between indexes, and it is able to classify outburst risk effectively, providing insights for the scientific and accurate assessment of such risks in front of the driving face.

Suggested Citation

  • Guorui Zhang & Enyuan Wang & Zhonghui Li & Ben Qin, 2022. "Risk assessment of coal and gas outburst in driving face based on finite interval cloud model," 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. 110(3), pages 1969-1995, February.
    • Handle: RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05021-z
    DOI: 10.1007/s11069-021-05021-z
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    References listed on IDEAS

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    1. Cheng Zhai & Xianwei Xiang & Jizhao Xu & Shiliang Wu, 2016. "The characteristics and main influencing factors affecting coal and gas outbursts in Chinese Pingdingshan mining region," 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. 82(1), pages 507-530, May.
    2. Saaty, Thomas L., 2003. "Decision-making with the AHP: Why is the principal eigenvector necessary," European Journal of Operational Research, Elsevier, vol. 145(1), pages 85-91, February.
    3. Guo-Ying Wei & Fang-Chao Kang & Bin-Bin Qin & Tian-Rang Jia & Jiang-Wei Yan & Zhen-Dong Feng, 2020. "A novel method for evaluating proneness of gas outburst based on gas-geological complexity," 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. 104(2), pages 1841-1858, November.
    4. Chang, Da-Yong, 1996. "Applications of the extent analysis method on fuzzy AHP," European Journal of Operational Research, Elsevier, vol. 95(3), pages 649-655, December.
    5. Kahraman, Cengiz & Cebeci, Ufuk & Ruan, Da, 2004. "Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey," International Journal of Production Economics, Elsevier, vol. 87(2), pages 171-184, January.
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