Previously conducted studies have established that as a disaster-bearing body, a coal mine is vulnerable to flood disasters and their consequent impacts. The purpose of this study is to put forward a quantitative evaluation method of the risk of coal mine flood disaster. Based on the scientific theory of disaster risk, a risk assessment model and index system for coal mine flood disaster was constructed, and a risk assessment method was proposed based on the projection pursuit and fuzzy cluster analysis. The results show that the risk of coal mine flood disaster was mainly determined by the hazard of disaster-causing factors, the stability of the disaster-prone environment, and the vulnerability of disaster-bearing bodies. Further research shows that the maximum daily rainfall had the greatest impact the risk of coal mine flood disaster. Therefore, the early warning mechanism should be established between the coal mine and the meteorological department to improve the fortification level. A risk assessment method of coal mine flood disaster was proposed in this study, which is of great significance for energy sustainability.
A multisignal nanosecond synchronous acquisition system to measure acoustic emission (AE) and electromagnetic radiation (EMR) generated during the process of loading and failure of coal and rock samples is established. The correlation between the energy of the AE and EMR signals and the loading stress of outburst coal-rock samples was studied, and the characteristics of the AE and EMR signals during the process of loading and fracturing the outburst coal and rock samples were analyzed. The results show that (1) before the failure of the outburst coal and rock samples, the fluctuation of the AE and EMR signals is the largest, with the same rising and falling trend, and the intensity is not strictly positively correlated, with the phenomenon of low EMR when the AE intensity is high; (2) the EMR and AE deviation degree and frequency exhibit a good response to coal and rock fracturing. The correlation between EMR and stress drop is stronger than that of AE, and the AE signal is richer than the EMR signal. The results show that it is feasible to develop combined AE and EMR early warning technology to improve the early forecasting accuracy of coal and gas outbursts.
As a disaster-bearing body, the coal mine is vulnerable to the impact threat of rainstorm disasters, which easily induce flooding accidents. In view of this, this study is designed to propose the vulnerability assessment method of rainstorm-induced coal mine flooding disasters. On account of the scientific theory of disaster risk, the evaluation model and index system of coal mine flooding disaster induced by rainstorm covering exposure, fortification level, and resilience are constructed, while the vulnerability assessment method based on Tri-AHP method is proposed. Study results demonstrate that population exerts the greatest impact on exposure, wellhead elevation matters the most for fortification level, and the emergency plan has a dominant influence on resilience. Therefore, for coal mines, it is suggested to strengthen the special rainstorm emergency plan drill, improve the fortification level, and solidify the emergency duty during the rainy season. In this study, the rainstorm disaster vulnerability assessment method of coal mine is innovatively put forward, which is conducive to sustainable energy and environmental development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.