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

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.

Mining Employees Safety and the Application of Information Technology in Coal Mining: Review

“…Subsidence of the ground, underground railway accidents, and methane poisoning also cause fatalities (15). The operational risks were roof collapse, fire, and gas concentration exceeding the limit (16). With the spontaneous combustion of coal and the presence of methane in the structure of the lode, underground coal mining has the highest rate of fatal accidents and injury in the mining industry (17).…”

Using Network Theory to Explore the Risk Characteristics of Bridge-Tunnel Hybrid Construction

“…Instead of analyzing individual accidents, Zhou et al [9] used network theory to explore the complexity of a subway construction accident network. Deng et al [8] selected coal-mining accidents as data to analyze an accident chain and integrated the accident chains into a global network. From the perspective of complex network theory, Zhou et al [29] discussed the time series characteristics of hidden accidents in subway construction and the underlying mechanisms.…”

“…In the BCRN and TCRN, the node's size increased with increasing out-degree of the risk factor, and in the WRN, it increased with increasing betweenness. As in the classification of coal mining risk factors by Deng et al [8], the risk factors in the present work are roughly divided into five categories: Worker, Machine, Technology, Management, and Environment, as indicated by different colors in the risk network. ''Worker'' refers to the risk attributed to worker errors.…”

“…Secondly, some studies have used questionnaires [7] to combine data from historical accidents with expert subjective judgments without taking into account the effects of workers' operations or the natural environment. Thirdly, although most of the current literature [8], [9] only focuses on a single type of engineering, crucial traffic engineering often involves the combination of bridges and tunnels.…”

Exploring the Properties of Cost Overrun Risk Propagation Network (Corpn) for Promoting Cost Management

“…100 Zhou et al (2014) 102 available cases about subway construction accident were used to establish a subway construction accident network. 102 Deng, Song, Zhou, and Liu (2017) 126 typical coal mining accidents were collected to construct a coal mine risk network. 126…”