New Evaluation Methods for Coal Loss Due to Underground Coal Fires

ABSTRACT

The evaluation of coal loss caused by underground coal fire is the principal basis for the decision-making of underground coal fire extinguishing and utilization. However, the existing coal fire risk assessment method is complex, time-consuming, laborious and inaccurate, and it is difficult to meet the requirements of coal mine underground fire control and utilization. Thus, this paper systematically investigates the relationship between coal loss and the underground combustion space area of coal fires, and the synergetic relationship between combustion space area of coal fires and surface subsidence：1. The coal loss caused by underground coal fire is related to the combustion space area of coal fires. When the different types of coal spontaneous combustion form the same size fuel-burning area, the coal loss is different. The loss of coal can be calculated by the size of the combustion space area of coal fires. 2. The random medium theory, surface subsidence rule of main section and the geometric method were used to determine they synergistic relationship between the combustion space area of coal fires and the surface subsidence. Different methods have their own advantages and disadvantages and applicable scope. Then, the monitoring method of surface subsidence caused by underground coal fire was analyzed, new methods to determine the position of underground combustion space area and to evaluate coal loss caused by coal fire were proposed. The results have important theoretical and practical significance for the determination of underground hidden coal fire location and the management and utilization of underground coal fires.

KEYWORDS:

• Underground coal fire
• coal loss
• surface subsidence
• combustion space area of coal fires

Acknowledgments

We would like to acknowledge the support of the Jiangsu dual creative teams project awarded in 2017.

Additional information

Funding

This work was funded by the National Natural Science Foundation of China (Grant No. 51804301), National Natural Science Foundation of China (Grant No. 51674249), Natural Science Foundation of Jiangsu Province (BK20180661), China Postdoctoral Science Foundation Funded Project (Grant No. 2017M621873), the National Natural Science Foundation of China (Grant No. 41641036) and Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX19_2193).