Abstract
Coal particle size is an important factor affecting the gas emission law. Taking Wangjialing coal mine as the research object, the particle size distribution of coal mining and caving is analyzed via field tests in order to develop the gas emission theoretical model from granular coal. We also perform the numerical simulation of the coal body and longwall face gas emission characteristics under different particles. Finally, the gas emission rules of coal cutting, caving, longwall face, and goaf in Wangjialing coal mine are analyzed, and the dynamic prediction model, which accounts for the time influence of the coal cutting and coal caving speed based on the particle size distribution characteristics, is derived. Results demonstrate the wide distribution of the coal particle size at Wangjialing coal mine, with a higher proportion of small- and large-sized particles. The smaller the coal particle size, the faster the gas emission and the smaller the desorption ratio of coal at ≥ 20 mm within 30 min. The comprehensive emission intensity of coal mining and caving can be described by an exponential function. The initial emission intensity of coal mining is observed to exceed that of coal caving, while the attenuation laws of the two are essentially equal, and the majority of the gas emission is completed within 5 min. The error between the results of the multisource dynamic prediction model and the field measurement is small, which is of practical application significance.
Highlights
Coal particle size is an important factor affecting the gas emission law
Results demonstrate the wide distribution of the coal particle size at Wangjialing coal mine, with a higher proportion of small- and large-sized particles. e smaller the coal particle size, the faster the gas emission and the smaller the desorption ratio of coal at ≥ 20 mm within 30 min. e comprehensive emission intensity of coal mining and caving can be described by an exponential function. e initial emission intensity of coal mining is observed to exceed that of coal caving, while the attenuation laws of the two are essentially equal, and the majority of the gas emission is completed within 5 min. e error between the results of the multisource dynamic prediction model and the field measurement is small, which is of practical application significance
E equipment used in the particle size distribution tests include a mine explosion-proof camera, camera overhead frame, explosion-proof fill light, and ruler. e testing process is described in the following. e camera was fixed with the overhead frame, placing the ruler flat above the falling coal (Figure 1), using the overhead frame to keep the camera line of sight perpendicular to the coal body and to minimize the imaging deformation during the shooting process. e coal mining and coal caving in the Wangjialing 12322 face were photographed separately. e collected images were analyzed in the laboratory
Summary
Coal particle size is an important factor affecting the gas emission law. Taking Wangjialing coal mine as the research object, the particle size distribution of coal mining and caving is analyzed via field tests in order to develop the gas emission theoretical model from granular coal. The gas emission rules of coal cutting, caving, longwall face, and goaf in Wangjialing coal mine are analyzed, and the dynamic prediction model, which accounts for the time influence of the coal cutting and coal caving speed based on the particle size distribution characteristics, is derived. Ey determined the correction method and regression coefficient of gas emission with temperature, as well as the quantitative variation law of the gas diffusion coefficient with increasing coal particle temperatures across different ranks Liu et al [32] examined the quantitative relationship between gas diffusion flux and temperature of coal particles under different ranks. ey determined the correction method and regression coefficient of gas emission with temperature, as well as the quantitative variation law of the gas diffusion coefficient with increasing coal particle temperatures across different ranks
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