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

Liangliang Song,Ping Liu,Zhipeng Zhou,Yongliang Deng

doi:10.1155/2017/7628569

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.

Highlights

China is the largest producer and consumer of coal in the world, from which it has derived about 65% of its energy over the past sixty years [1]
Badri et al [22] studied risk management in mining projects based on analytic hierarchy process method, and the results show the importance of considering occupational health and safety (OHS) in the process of coal mining
coal mine risk network (CMRN) is a relatively small-world network according to its clustering coefficient and average path length, indicating that the risk propagation in CMRN is much faster than a random network

Summary

Introduction

China is the largest producer and consumer of coal in the world, from which it has derived about 65% of its energy over the past sixty years [1]. In China, more than 90% of fossil energy reserves are coal. The energy consumption structure of energy, which relies mainly on coal, cannot be changed within quite a long time. This standpoint can be validated by China’s National Energy Development Strategy Plan (2014–2020) and 13th Five-Year Plan (2016–2020).

Methods

Results

Discussion

Conclusion