Hao Xu

Conventional standard oxygen-consumption-rate models can retain an apparent dependence on reactor height and gas flow rate when outlet oxygen concentrations become low. To examine this issue, programmed-temperature oxidation experiments were conducted using gas-fat coal from the Zhuxianzhuang Coal Mine. Two packed coal-bed configurations were used: a full bed (coal-bed height, 20 cm; packed-coal volume, 250 cm³) and a half bed (coal-bed height, 10 cm; packed-coal volume, 125 cm³); both were operated at inlet flow rates of 80, 100, and 120 mL min⁻¹. Outlet O₂, CO, and CO₂ samples were collected near the end of each isothermal hold and analysed by gas chromatography. An empirical effective oxygen-concentration correction parameter was introduced to revise the conventional standard oxygen-consumption-rate model, and corresponding standard CO and CO₂ generation-rate and calculated heat-release-intensity models were derived. The outlet oxygen concentration exhibited four apparent stages with increasing temperature: slow decrease, rapid decrease, renewed slow decrease, and stabilization. Above approximately 195 °C, the outlet oxygen concentration approached a nonzero plateau. On the basis of this plateau and the consistency of results obtained under the tested conditions, a value of 1.21 vol.% was selected as an empirical correction parameter for the present system. The conventional model produced increasingly separated oxygen-consumption-rate curves at high temperatures and yielded R² = 0.930. After introducing the correction parameter, the curves obtained under the tested conditions showed improved convergence and R² increased to 0.993. The revised standard CO and CO₂ generation rates and calculated heat-release intensities likewise showed reduced dependence on reactor height and flow rate within the present dataset and increased exponentially with temperature. These empirical correlations describe the tested coal under the specified reactor and heating conditions. Independent validation is required before extending them to other coals or operating conditions.

With the gradual depletion of shallow coal resources and the continuous increase in mining intensity in coal-producing regions, coal mining is progressively deepening

Understanding gas transport mechanisms within the coal matrix is crucial for optimizing coalbed methane extraction and preventing gas-related accidents. However, current academic research often ignores the release characteristics and transport behaviors of gas stored within rocks. This study first determined the adsorption constants of coal and rock particles for different gases and conducted isothermal desorption experiments for both carbon dioxide and methane under constant-volume conditions. Based on the free gas density gradient diffusion theory, a mathematical model for gas transport was developed and solved numerically using the finite difference method. Furthermore, a novel method integrating dimensionless analysis criteria with an empirical desorption formula was proposed to determine the micropore diffusion coefficient. The results demonstrate that (1) for both rock and coal particles, and for both carbon dioxide and methane desorption, the simulation curves based on the density gradient diffusion model show fundamental consistency with the experimental data, verifying the model's correctness; (2) within the same coal/rock particle, the micropore diffusion coefficient of carbon dioxide is greater than that of methane. For anthracite under 2 MPa, the methane diffusion coefficient is 6.3 × 10−8 cm2/s, while the carbon dioxide diffusion coefficient is 4.9 × 10−7 cm2/s. For the same gas, the micropore diffusion coefficient is greater in coal particles than in rock particles; (3) although the total gas content stored in the rock matrix is less compared to coal particles, it is not negligible. Subsequent research should pay greater attention to the storage and transport behaviors of gas within rocks.

Accurate structural characterization of nanopores in coal by cryo-FIB-SEM

Moisture in coal plays a critical role in influencing gas desorption. This work numerically establishes a mathematical model for the gas desorption in spherical coal particles with different moisture contents based on the free gas density gradient (FGDG) concept. Importantly, the gas desorption pressure drop starting time (DPDST) was defined, and its response mechanism to moisture content was explored. Finally, the theoretical differences between the classical Fick's and FGDG models in describing the gas desorption/diffusion of water-containing coal were discussed in particular. The results show that the final stabilized dimensionless gas pressure in coal becomes closer and closer to the external initial dimensionless pressure as the coal moisture content increases. The DPDST is inversely proportional to the moisture content of the coal sample, possibly because more gas adsorption sites are occupied by water molecules at high moisture contents. Three different well-used empirical formulas for gas desorption were used for fitting, with one of the nth power of time t empirical formulas yielding the best fit. Based on the fitting results, the gas desorption amount limit is inversely proportional, and the gas desorption rate is proportional to the moisture content of the coal sample. On the basis of the diffusion coefficient inversion results, the prediction accuracy of the FGDG model is higher than that of the Fick's model. Theoretically, the diffusion coefficients of both models are inversely proportional to the coal moisture content, possibly because water molecules may occupy the adsorption sites of gas molecules and hinder the diffusion channel.

Understanding the characteristics of coal spontaneous combustion (CSC) in goaf under different porosities is crucial for comprehending the mechanism of CSC and its prevention and control. In this paper, a multi-field coupled model of CSC in the goaf, considering porosity variation, is developed to investigate the effect of porosity on the CSC characteristics in the goaf. The results indicate that, as the goaf depth increases, both porosity and permeability decrease. When the highest goaf porosity is 25%, the average airflow velocity is between 0.00134 and 0.00139 m/s. In contrast, the average airflow velocity in the goaf with a porosity of 40% is approximately six times greater than that of the goaf with a porosity of 25%. As the goaf porosity increases, the overall oxygen concentration, temperature, and oxidized zone area also rise. Moreover, the oxidation zone area can be quantified and visualized, thereby enabling more effective prediction of the CSC risk in the goaf. The findings of the study have a positive significance in guiding the prevention and control of coal fires.

An in-depth understanding of gas diffusion characteristics in coal is of great value to coalbed methane (CBM) production planning and coal mine safety management. However, the mechanism and model of gas diffusion is still unclear, and some methods for determining diffusion coefficients are not accurate enough. Accordingly, a free gas density gradient (FGDG)–driven coal particle gas desorption and diffusion model was established in this work, and numerical solutions were performed via finite difference method (FDM) and dimensionless method. The variation rules of dimensionless gas pressure, gas content, desorption capacity, and desorption rate were obtained. Finally, the application of the dimensionless method in diffusion modeling and diffusion coefficient inversion was discussed. The results show that the dimensionless method can simplify mathematical equation processing and analyze the common phenomena of desorption and diffusion under different parameters. The gas desorption diffusion in coal particles is from the surface to the inside, and there is obvious desorption hysteresis effect. The larger the dimensionless radius or dimensionless time, the smaller the dimensionless gas pressure, gas content, and dimensionless desorption rate. The dimensionless cumulative gas desorption amount increased rapidly first and then tended to flat with dimensionless time. The simulated curve can be easily converted into the variation curves of several different measured parameters, and the diffusion coefficient can be calculated accurately. The prediction curve of the FGDG diffusion model is in good agreement with the experimentally measured data, which verifies its reasonableness. The research content aims to provide some ideas for modeling gas desorption and diffusion behavior.