CHN Energy Shendong Coal Group Co. , Ltd.
School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing

研究煤中瓦斯解吸-扩散规律,对于充分认识煤中瓦斯运移机理、科学利用瓦斯资源、精准防治瓦斯灾害具有重要意义。采用数值模拟研究方法,对单孔模型、双孔模型及动扩散系数模型在煤粒瓦斯解吸-扩散过程中的适用性进行了对比和分析,研究了双孔模型与动扩散系数模型的瓦斯压力分布规律及模型各参数对煤样变质程度、粒径、吸附平衡压力的敏感性。结果表明,相较于单孔模型,双孔模型与动扩散系数模型可以更加精准描述全阶段瓦斯解吸-扩散规律。双孔模型与动扩散系数模型以不同方式描述了瓦斯解吸-扩散过程,相较于双孔模型,动扩散系数模型中煤粒径向瓦斯压力梯度较大。煤样变质程度、粒径、吸附平衡压力等对模型各参数有较大影响,其本质均为煤中孔隙结构差异。研究结果可为合理选择瓦斯解吸-扩散模型及其参数提供借鉴。

Study on the law of gas desorption-diffusion in coal is of great significance for fully understanding the mechanism of gas migration in coal, gas resources scientific utilization, and gas disasters precise control and prevention. Based on the numerical simulation method, the applicability of the unipore model, the bidisperse model and the dynamic diffusion coefficient model in the gas desorption-diffusion of coal particles was compared and analyzed. The gas pressure distribution law of the bidisperse model and the dynamic diffusion coefficient model and the sensitivity of the model parameters to the metamorphic degree, particle size and adsorption equilibrium pressure of the coal sample were studied. The results show that compared with the unipore model, the bidisperse model and the dynamic diffusion coefficient model will more accurately describe the gas desorption-diffusion law in the whole stage. The bidisperse model and the dynamic diffusion coefficient model describe the gas desorption-diffusion process in different ways. Compared with the bidisperse model, the dynamic diffusion coefficient model has a larger radial gas pressure gradient. The degree of coal sample metamorphism, particle size, and adsorption equilibrium pressure have a significant impact on the various parameters of the model, and its essence is the difference in pore structure of coal. The research results can provide a guidance for the rational selection of gas desorption-diffusion model and parameters.

国家自然科学基金项目(52130409,52121003)

张迪,丰程涛,李鹏,等.煤粒瓦斯解吸-扩散数值模型适用性及参数敏感性研究[J].煤炭工程,2024,56(10):281-288.