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Modeling and analysis of mining subsidence disaster chains based on stochastic Petri nets

Author

Listed:
  • Yuejuan Chen

    (Taiyuan University of Technology
    Inner Mongolia University of Technology)

  • Jin Zhang

    (Taiyuan University of Technology)

  • Anchao Zhou

    (Taiyuan University of Technology)

  • Bo Yin

    (Taiyuan University of Technology
    Inner Mongolia University of Technology)

Abstract

Coal mining that results in goaf causes ground surface subsidence. It will in turn cause a disruptive threat to the surface construction, water, and slope body, which constitutes a transitive relationship. In the process of a disaster chain, the interactions between disasters have serious negative consequences. To solve these problems, we clearly established model elements of the disaster chain and analyzed their control flow relationships. On that basis, the stochastic Petri nets, as a powerful mathematical modeling tool that can be used to describe discrete and distributed systems, were adopted to model the process of mine ground surface subsidence disaster chains using the DISChain_Net model. The cause and process of the destruction as well as the disaster consequences were discussed. Then, the crucial nodes in the process of the disaster chain delivery were identified, which enabled the decision makers to make a reasonable judgment and implement mitigation measures. The study will thus provide new research ideas for studying the mine ground surface subsidence disasters through modeling, analysis, and assessment.

Suggested Citation

  • Yuejuan Chen & Jin Zhang & Anchao Zhou & Bo Yin, 2018. "Modeling and analysis of mining subsidence disaster chains based on stochastic Petri nets," 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. 92(1), pages 19-41, May.
  • Handle: RePEc:spr:nathaz:v:92:y:2018:i:1:d:10.1007_s11069-018-3190-6
    DOI: 10.1007/s11069-018-3190-6
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    References listed on IDEAS

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    1. Lifen Xu & Xiangwei Meng & Xuegong Xu, 2014. "Natural hazard chain research in China: A review," 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. 70(2), pages 1631-1659, January.
    2. Ximin Cui & Yongge Gao & Debao Yuan, 2014. "Sudden surface collapse disasters caused by shallow partial mining in Datong coalfield, 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. 74(2), pages 911-929, November.
    3. Tom Parsons & Chen Ji & Eric Kirby, 2008. "Stress changes from the 2008 Wenchuan earthquake and increased hazard in the Sichuan basin," Nature, Nature, vol. 454(7203), pages 509-510, July.
    4. K. Peters & L. Buzna & D. Helbing, 2008. "Modelling of cascading effects and efficient response to disaster spreading in complex networks," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 4(1/2), pages 46-62.
    5. Jianxiu Wang & Xueying Gu & Tianrong Huang, 2013. "Using Bayesian networks in analyzing powerful earthquake disaster chains," 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. 68(2), pages 509-527, September.
    6. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
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    Cited by:

    1. Li Li & Tingliang Li & Huisheng Meng & Yinghe Xie & Jie Zhang & Jianping Hong, 2021. "Effects of Seven-Year Fertilization Reclamation on Bacterial Community in a Coal Mining Subsidence Area in Shanxi, China," IJERPH, MDPI, vol. 18(23), pages 1-16, November.
    2. Yanyan Liu & Keping Li & Dongyang Yan & Shuang Gu, 2023. "The prediction of disaster risk paths based on IECNN 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. 117(1), pages 163-188, May.
    3. Kang Ma & Yuxiu Zhang & Mengying Ruan & Jing Guo & Tuanyao Chai, 2019. "Land Subsidence in a Coal Mining Area Reduced Soil Fertility and Led to Soil Degradation in Arid and Semi-Arid Regions," IJERPH, MDPI, vol. 16(20), pages 1-14, October.

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