Prediction of Gas Emissions in the Working Face Based on the Desorption Effects of Granular Coal: A Case Study
Prediction of Gas Emissions in the Working Face Based on the Desorption Effects of Granular Coal: A Case Study
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基于粒煤解吸效应的工作面瓦斯涌出量预测——以实例分析
DOI：
10.3390/su141811353
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发表时间：
2022-09
期刊：
影响因子：
3.9
通讯作者：
Chao Liu
中科院分区：
文献类型：
--
作者：
Cheng Cheng;Xiao-Yu Cheng;Han Gao;Wen-Ping Yue;Chao Liu
The aim of the study in this paper is to establish a prediction model of gas emission in the working face. The gas desorption variation characteristics of coal with different particle sizes were assessed using physical tests and based on the coal body of No. 2 coal seam in Wangjialing Coal Mine, Shanxi, China, to reveal the influence law of coal particle size on coal gas desorption. The gas desorption characteristics in the working face, the law of gas emission of coal cutting, coal caving, coal wall, and remnant coal in the goaf of the production process were then analyzed after establishing a gas emission prediction model based on the particle size of the coal. The accuracy of the gas emission prediction model was finally validated through actual measurement of the coal particle size distribution and gas emission in the test working face. The results of the current study show that the coal particle size is negatively correlated with the gas desorption capacity within a certain range. The initial desorption intensity of the coal gas decreased with an increase in the coal particle size. However, the initial gas desorption intensity and attenuation coefficient of gas emission were constant after a certain level of increase in the coal particle size. It was found that the average error between the gas emission prediction model and the actual gas emission data in the mining process was 5.29% based on the desorption characteristics of granular coal. Therefore, the established gas emission prediction model can characterize the law of gas emission in the actual production process more effectively. Furthermore, it provides reliable support for the prediction and control of gas emissions from the goaf under the condition of fully mechanized mining with top coal caving.
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