Cheng Cheng

Cheng Cheng


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 September 2022 in Sustainability
Verified
Journal Article
Open access
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CCCheng Cheng
Cheng Cheng
XCXiaoyu Cheng
Xiaoyu Cheng
HGHan Gao
Han Gao
WYWenping Yue
Wenping Yue
CLchao liu
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.