Thermal insulation gunite (TIG) in roadways is an effective method for regional thermal hazard control in mines. The development of mine TIG materials is the foundation of thermal insulation technique. However, some conventional and advanced insulation materials are inapplicable to deep mines which are rather humid with high in situ stress and high geo‐temperature. In this study, a kind of fly ash‐inorganic mineral TIG material was developed and applied to the modelling of a high geo‐temperature roadway. Moreover, the thermal insulation effect of the TIG layer was analyzed, and the temperature field characteristics of the TIG surrounding rock were discussed. Results reveal that (1) the TIG layer has a significant impact on the heat release of the wall and stability of the surrounding rock temperature field; (2) the initial temperature disturbance times, temperature disturbance ranges, and temperature drop rates differ with whether a TIG layer exists or not; (3) after the TIG roadway starts to be ventilated, the thermal flux densities tend to be consistent, which indicates the end of temperature disturbance; besides, the dimensionless temperature shares an exponential relation with the dimensionless radius; and (4) the characteristics of temperature drops vary with the radial positions of the surrounding rock. The research results provide a certain reference for thermal hazard control, temperature prediction, and ventilation network adjustment.

Accurate prediction of the coal spontaneous combustion hazard grades is of great significance to ensure the safe production of coal mines. However, traditional coal temperature prediction models have low accuracy and do not predict the coal spontaneous combustion hazard grades. In order to accurately predict coal spontaneous combustion hazard grades, a prediction model of coal spontaneous combustion based on principal component analysis (PCA), case-based reasoning (CBR), fuzzy clustering (FM), and the snake optimization (SO) algorithm was proposed in this manuscript. Firstly, based on the change rule of the concentration of signature gases in the process of coal warming, a new method of classifying the risk of spontaneous combustion of coal was established. Secondly, MeanRadius-SMOTE was adopted to balance the data structure. The weights of the prediction indicators were calculated through PCA to enhance the prediction precision of the CBR model. Then, by employing FM in the case base, the computational cost of CBR was reduced and its computational efficiency was improved. The SO algorithm was used to determine the hyperparameters in the PCA-FM-CBR model. In addition, multiple comparative experiments were conducted to verify the superiority of the model proposed in this manuscript. The results indicated that SO-PCA-FM-CBR possesses good prediction performance and also improves computational efficiency. Finally, the authors of this manuscript adopted the Random Balance Designs—Fourier Amplitude Sensitivity Test (RBD-FAST) to explain the output of the model and analyzed the global importance of input variables. The results demonstrated that CO is the most important variable affecting the coal spontaneous combustion hazard grades.

In the enhanced geothermal system (EGS), the injected fluid will induce shear sliding of rock fractures (i.e., hydroshearing), which consequently, would increase the fracture aperture and improve the heat transfer efficiency of the geothermal reservoir. In this study, theoretical analysis, experimental research and numerical simulation were performed to uncover the permeability and heat transfer enhancement mechanism of the Hot-Dry-Rock (HDR) mass under the impact of shearing. By conducting the direct shear test with the fractured rock samples, the evolution process of fracture aperture during the shearing tests was observed, during which process, cubic law was adopted to depict the rock fracture permeability. To investigate the seepage characteristics and temperature distribution of the fractured HDR under the influence of shearing, a simulation study of shear-seepage-heat transfer in a fractured rock mass has been conducted to validate the observed shear-induced fracture dilation during the direct shear test. The results demonstrate that (1) the hydroshearing increases the dilation of granite fracture and enhances the permeability of the HDR rock mass, while the temperature around the HDR fracture will reduce. (2) Fracture roughness is of vital importance to enhance the permeability during the shearing tests. To be more specific, a rougher fracture always implies a higher permeability and a greater heat extraction efficiency. (3) The shear induced heat extracting efficiency is dominated by the increased fluid flux in the earlier period of the EGS reservoir, and this efficiency is controlled by the outlet water temperature since the fluid flux becomes stable after the shearing test. Therefore, balancing the hydroshearing enhanced heat extraction efficiency and EGS reservoir lifespan would be significant to the sustainable development and utilization of geothermal energy

Characteristic parameters of shield supporting in fully mechanized mining, especially time-weighted average pressure (TWAP), are crucial for the analysis and prediction of roof weightings in longwall panels. Despite the leap-forward development of underground data collection and transmission, mining and regional correlation analysis of massive shield data remains challenging. In this study, a hybrid machine learning model integrating the long short-term memory (LSTM) networks and the Bayesian optimization (BO) algorithm was developed to predict TWAP based on the setting pressure (SP), revised setting pressure (RSP), final pressure (FP), number of yielding (NY), TWAP in the last supporting cycle (TWAP (last)), and loading rate in each period. Statistical measures including the mean square error and mean absolute error were used to validate and compare the prediction performances of the BP model, the LSTM model, and the BO-LSTM model. Furthermore, sensitivity studies were carried out to evaluate the importance of input parameters. The results show that the BO-LSTM model is robust in predicting TWAP. FP and TWAP (last) are the most important input parameters in TWAP prediction, followed by RSP and NY. Moreover, the total importance scores of loading rates reach 0.229, indicating the necessity of including these parameters into the dataset. The proposed BO-LSTM model is capable of predicting TWAP which serves for shield-roof status intelligent perception.

The novel class F fly ash‐based geopolymer, largely made of fly ash from the coal solid waste, was used as a kind of grouting material in the coal and electricity‐integrated mine from which the solid waste comes, for the purpose of in situ utilization of fly ash. The ratio experiment of material, designed through the orthogonal method, was used to study material properties such as fluidity and strength which are important to the application of mine grouting, and the optimal material proportioning scheme for Green Fly Ash‐based grouting material is determined. It has been found out that there was serious rib spalling, roof deformation, obvious floor heave, crack development, and some water seepage in the permanent refuge chamber of the mine. Therefore, to solve these problems, a specific scheme of grouting reinforcement for the surrounding rocks of the permanent refuge chamber and roadway in this mine was designed. Through an analysis of the reinforcement effect of the cementation of surrounding rock after the grouting process, it can be concluded that the green fly ash‐based polymer as grouting material can well penetrate into the cracks of the broken surrounding rock and get fully cemented with the surrounding rock and that it can reduce the deformation of the surrounding rock effectively, increase the integrity, and improve the carrying capacity of the surrounding rock. Besides, the grouting reinforcement effect of surrounding rock was verified through numerical simulation, and the grouting process design of green fly ash‐based polymer mine was discussed. This study can provide a green and economical approach to the in situ utilization of fly ash which is a kind of coal solid waste.