An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

Author:

Deng Yongliang12ORCID,Song Liangliang3ORCID,Zhou Zhipeng4,Liu Ping35

Affiliation:

1. State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology, Xuzhou 22116, China

2. School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China

3. School of Civil Engineering, Southeast University, Nanjing 210096, China

4. College of Economic and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

5. School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Abstract

Capturing the interrelations among risks is essential to thoroughly understand and promote coal mining safety. From this standpoint, 105 risks and 135 interrelations among risks had been identified from 126 typical accidents, which were also the foundation of constructing coal mine risk network (CMRN). Based on the complex network theory and Pajek, six parameters (i.e., network diameter, network density, average path length, degree, betweenness, and clustering coefficient) were employed to reveal the topological properties of CMRN. As indicated by the results, CMRN possesses scale-free network property because its cumulative degree distribution obeys power-law distribution. This means that CMRN is robust to random hazard and vulnerable to deliberate attack. CMRN is also a small-world network due to its relatively small average path length as well as high clustering coefficient, implying that accident propagation in CMRN is faster than regular network. Furthermore, the effect of risk control is explored. According to the result, it shows that roof collapse, fire, and gas concentration exceeding limit refer to three most valuable targets for risk control among all the risks. This study will help offer recommendations and proposals for making beforehand strategies that can restrain original risks and reduce accidents.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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