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To improve the accuracy of early warning on coal spontaneous combustion (CSC), this paper, on the basis of the principle of preferential selection of index gases in CSC process, carries out fitting analysis of the variation curve of index gas data with coal temperature by combining logistic fitting model, then establishes a CSC graded warning system based on positive pressure beam tube monitoring, and determines CO, O2, φ(CO)/φ(O2), C2H4, C2H6, φ(C2H4)/φ(C2H6) as the index gases for predicting and forecasting CSC, and accurately divides the CSC process into seven levels of early warning: safe, gray, blue, yellow, orange, red, and black. Applying the CSC positive pressure beam tube monitoring system to Dongtan coal mine and analyzing the error by manual sampling and sampling by positive pressure beam tube system, we find that the error is less than 0.1%. Monitoring of several working faces, we get that the CO and CH4 concentrations of 14,320 working face are higher than the normal level at the beginning of mining, and the 100 × CO/ΔO2 value is higher than the gray warning threshold of 0.1, and the warning level is gray warning. After taking timely preventive measures against coal oxidation and warming, the CO and CH4 concentrations return to the normal level and the warning level drops to the safe level. This paper improves the monitoring, identifying and early warning capabilities of underground CSC in its early stage. [ABSTRACT FROM AUTHOR]

Coal spontaneous combustion is a common problem faced by many coal mines. Spontaneous combustion in goaf releases a large amount of harmful gases, polluting the environment while causing a large amount of wasted resources, and even endangering the lives of workers. Due to the collapse of the interior of the mining area, it is impossible to measure the internal gas composition directly. In order to more accurately predict the spontaneous combustion state inside the mining airspace, this paper obtains the CO generation law and the main source of the working face through the combination of laboratory experiments and on-site monitoring. The CO concentration prediction model of the return corner is established with CO as the index gas. Finally, the safe concentration and warning concentration of the working face are calculated according to the example, which provides theoretical basis for the prediction of spontaneous combustion of coal. [ABSTRACT FROM AUTHOR]

The productivity of coal mines is seriously threatened by the combined disasters of gas and coal spontaneous combustion, which have become a common disaster mode. It is unclear how the gas and coal spontaneously combusted in the roof cutting along gob working face. The goal of this study is to identify the distinctive features of combined disasters in gob from two different types of roof cutting along working faces. In these two different types of roof cutting along gob working faces, the paper constructs the permeability model of the gob. The findings demonstrate that the data from the field experiment and the simulation results agree, which validates the simulation's reliability. In contrast to single sided roof cutting along gob working faces, double sided roof cutting along gob working faces clearly has a thinner oxidation zone. Moreover, the oxidation zone of the double side roof cutting along gob working faces is closer to the working face, which is located in the shallow area of the gob 50 m behind the working face. The gas explosion area and the coal spontaneous combustion area are divided by the double side roof cutting along gob working face, which reduces the risk of compound disasters. Important theoretical direction for the prevention and control of gob disasters in the roof cutting along gob working face is provided by the simulation results. [ABSTRACT FROM AUTHOR]

Spontaneous combustion of coal leading to mine fire is a major problem in most of the coal mining countries in the world. It causes major loss to the Indian economy. The liability of coal to spontaneous combustion varies from place to place and mainly depends on the coal intrinsic properties and other geo-mining factors. Hence, the prediction of spontaneous combustion susceptibility of coal is of utmost importance for preventing the risk of fire in coal mines and utility sectors. Machine learning tools are pivotal in system improvements in relation to the statistical analysis of experimental results. Wet oxidation potential (WOP) of coal determined in the laboratory is one of the most relied indices used for assessing the spontaneous combustion susceptibility of coal. In this study, multiple linear regression (MLR) and five different machine learning (ML) techniques, such as Support Vector Regression (SVR), Artificial Neural Network (ANN), Random Forest (RF), Gradient Boosting (GB) and Extreme Gradient Boost (XGB) algorithms, were used to predict the spontaneous combustion susceptibility (WOP) of coal seams based on the coal intrinsic properties. The results derived from the models were compared with the experimental data. The results indicated excellent prediction accuracy and ease of interpretation of tree-based ensemble algorithms, like Random Forest, Gradient Boosting and Extreme Gradient Boosting. The MLR exhibited the least while XGB demonstrated the highest predictive performance. The developed XGB achieved R2 of 0.9879, RMSE of 4.364 and VAF of 84.28%. In addition, the results of sensitivity analysis showed that the volatile matter is most sensitive to the changes in WOP of coal samples considered in the study. Thus, during spontaneous combustion modelling and simulation, volatile matter can be used as the most influential parameter for assessing the fire risk of the coal samples considered in the study. Further, the partial dependence analysis was done to interpret the complex relationships between the WOP and intrinsic properties of coal. [ABSTRACT FROM AUTHOR]

With the increasing complication of production and geology conditions, and the increase of mining intensity and depth in coal mine, the coal structure presents varying degrees of deformation. In order to study the influence of uniaxial tension–compression effect on mechanical properties of coal matrix and CH4/CO2 adsorption characteristics, a macromolecular model reflecting the realistic bituminous coal structure was established. Results demonstrate that the influence of tension strain on the microporous structural parameters is greater than that of compression strain, and the tension strain weakens the mechanical properties but enhances the adsorbates adsorption amount. For the pure gases adsorption, there is a negative linear correlation between the total energy and adsorption amount. Additionally, the strain ranging from −0.20 to 0.20, the distribution of punctated adsorbates density develops to that of banded adsorbates density, and the mean adsorption density and saturated adsorption amount increase linearly. For the binary components adsorption (1:1), the CH4 adsorption strength increases while the CO2 adsorption strength slightly decreases. The minimum of total energy decreases in a quadratic polynomial relationship with the strain, and the proportion of van der Waals energy is 75.8–85.5%. Nevertheless, the competitive adsorption and strain have little effect on the potential energy range of the adsorbates. Furthermore, the diffusibility of CO2 molecular layers is relatively good, and the strain enhances the stability of CH4 molecular layers for the saturated binary adsorption. The findings provide essential guidance for the improvement of carbon capture and storage and CO2-enhanced coalbed methane technologies in the deformation area of coal seam. [ABSTRACT FROM AUTHOR]

Deposits remained after coal combustion are a well-known occurrence in the world; unfortunately, only a small percentage of such deposits are adequately regulated and, consequently, pose a serious threat to the local environment. Attenuation of negative consequences presupposes knowledge of a number of features, both of the deposit and the local environment as well the interaction with local biota. In this study, unregulated waste generated from decades of coal mining and combustion of superhigh-organic-sulfur Raša coal, enriched in Se-U–Mo-V and located in a vulnerable karst region, was investigated. To assess the impact of landfill on the environment, in addition to its general geochemical and mineralogical features, the human health risk was assessed and the leaching of elements from the landfill, local soil, and the coal itself was investigated. For the latter, three extraction procedures, ASTM, EP, and TCLP (pH 4.93 and 2.9), were employed, mimicking different environmental conditions, including the sporadic occurrence of acid rains in the region. The soil around the landfill displayed enrichment in the majority of elements compared to expected values, with exception of Se, Mo, U, V, Sr, and Cu found at the highest levels in landfill samples. Mobility of elements was found to be controlled by both pH and mineralogy (carbonates and sulfates), whereby the overall highest relative mobility was observed in landfill samples for elements prevalently bound to sulfate phases. Calculated Hazard Quotient describes this landfill as a risk to the environment and human health through different pathways. [ABSTRACT FROM AUTHOR]

There is a high potential for coal spontaneous combustion (CSC) above the roof beams of supports during the mining-stopped period. Early detection of temperature abnormal zones and corresponding measures are necessary to prevent CSC. In this work, a top-coal temperature measurement method was proposed, combining the coal surface temperature detection and the drilling temperature observation. Furthermore, an apparatus was developed that dramatically increases the rate of dry ice sublimation, resulting in the rapid release of cryogenic carbon dioxide gas. The device utilizes water from firefighting pipes in underground coal mines as a heat source for dry ice sublimation without electrical energy and has been applied and validated taking Silaogou Coal Mine in China as a field test site. Specifically, we found that during the stoppage period, the coal above the supports near the air inlet tunnel is more likely to appear hot spots; the carbon dioxide gas generated by the dry ice phase change device can quickly reduce the hot spots temperature, and the coal temperature does not rebound after the gas injection is stopped. Based on the above analysis, this work can effectively prevent the early top-coal spontaneous combustion during the stop mining period. [ABSTRACT FROM AUTHOR]