Journal of Failure Analysis and Prevention

, Volume 13, Issue 5, pp 538–544 | Cite as

Analyses of Cascading Failure in Mine Ventilation System and Its Effects in a Serious Mine Gas Explosion Disaster

  • F. Zhou
  • L. Wei
  • K. Chen
  • J. Cheng
Case History---Peer-Reviewed


In 2009, a serious gas explosion happened in Tunlan coal mine at Shanxi province, P.R. China, which claimed the lives of 78 miners. 114 miners got injured, and nearly 4 million dollars of economic loss was reported. According to the investigation report, the mine gas explosion was originally from a buildup of gas catching a flame in the underground. The happening of such accumulation was actually caused by functional failures of the mine ventilation system so that the concentration of gas reached the lower flammable limit. Technically speaking, the mine ventilation system is an integrity system. Any unit’s failure can lead to other units losing their normal functions until the whole system breaks down. In other words, a cascading failure may happen. Based on the Tunlan mine disaster, this article introduces the concepts of cascading failure in the subject of mine ventilation engineering, which include the development process of failure, the mechanism, and the corresponding failure criteria, etc. The software “VentGIS simulator” is used as a tool to investigate the failure that occurred and its effects in the mine ventilation system. The coupled relationships between the failure mechanism and the gas explosion and its propagation are quantitatively studied in-depth. The research efforts show that (1) unreasonably installed the ventilation regulators directly caused the buildup of mine gas, which means an initial failure in a local ventilation system had appeared. Thus, one requirement of the gas explosion was provided; (2) failures of the early-warning system and mitigation measures led to the propagation of gas explosion shock in the underground mine network. Hence, impacts by the explosion are greatly enhanced. The research results presented in this article can be used as theoretical guidelines for improving the safety of a mine ventilation system or assisting to design a new one in the future.


Mine gas explosion accident Mine ventilation system Cascading failure Disaster prevention ability 



The financial supports from the National Science Foundation of China (Grant No. 51134023), the Outstanding Youth Fund by Jiangsu Province (BK2012003), and the Qinglan project of Jiangsu Province, the Natural Science Foundation of Jiangsu Province of China for Youths (Grant No. SBK201341455), and the Fundamental Research Funds for the Central Universities (Grant No. 2013QNA01) are deeply appreciated.


  1. 1.
    S. Boccaletti, V. Latora, Y. Moreno, Complex networks: structure and dynamics. Phys. Rep. 424(4–5), 175–308 (2006)CrossRefGoogle Scholar
  2. 2.
    L. Wei, F. Zhou, H. Zhu, Topology theory of ventilation network and path algorithm. J. China Coal Soc. 33(8), 926–930 (2008)Google Scholar
  3. 3.
    R. Albert, H. Jeong, A. Barabási, Error and attack tolerance of complex networks. Nature 406(6794), 378–382 (2000)CrossRefGoogle Scholar
  4. 4.
    P. Holme, Edge overload breakdown in evolving networks. Phys. Rev. E 66(3), 36–119 (2002)CrossRefGoogle Scholar
  5. 5.
    P. Holme, B. Kim, Vertex overload breakdown in evolving net-works. Phys. Rev. E 65(6), 66–109 (2002)CrossRefGoogle Scholar
  6. 6.
    A.E. Motter, Y.C. Lai, Cascade-based attacks on complex networks. Phys. Rev. E 66(6), 65–102 (2002)Google Scholar
  7. 7.
    P. Holme, B.J. Kim, C.N. Yoon, Attack vulnerability of complex networks. Phys. Rev. E 65(5), 56–109 (2002)CrossRefGoogle Scholar
  8. 8.
    D.J. Watts, A simple model of global cascades on random networks. Proc. Natl. Acad. Sci. 99(9), 5766–5771 (2002)CrossRefGoogle Scholar
  9. 9.
    J. Jia, J. Ou, H. Zhao, Analysis on resistant capability to disaster of ventilation system. China Saf. Sci. J. 16(6), 25–29 (2006)Google Scholar
  10. 10.
    L. Cheng, Y. Yang, Y. Xiong, Study of mine ventilation system assessment based on artificial neural network. China Saf. Sci. J. 15(5), 89–91 (2005)Google Scholar
  11. 11.
    L. Cheng, Large scale software transitions: a case study of the first half of MFIRE. Mast University of Nevada, Reno, May 2000Google Scholar
  12. 12.
    J. Jia, J. Liu, Reliability theory of ventilation system during mine fire. China Saf. Sci. J. 16(02), 35–38 (2006)Google Scholar
  13. 13.
    R. Albert, A. Barabásil, Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)CrossRefGoogle Scholar
  14. 14.
    C. Huang, J. Fang, J.P. Jeffrey, K. Tsai, Topological robustness of the protein–protein interaction networks. Lecture Notes in Computer Science, vol. 4023 (Springer, Berlin, 2006), pp. 166–177Google Scholar
  15. 15.
    Sun, J. The causes and main lessons of “2·22” gas explosion disaster at Tunlan mine of Shanxi Coking Coal Group Co., Ltd. National Coal Mine Gas Curb Conference, Nanchang, 2009Google Scholar

Copyright information

© ASM International 2013

Authors and Affiliations

  1. 1.Faculty of Safety Engineering, Key Laboratory of Coal Mine Gas and Fire Prevention, Ministry of EducationChina University of Mining & TechnologyXuzhouPeople’s Republic of China

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