This paper presents an experimental investigation of anisotropic strength and deformation behavior of coal measure shale. The effect of two factors (i.e., anisotropy and water content) on shale strength and deformation behavior was studied. A series of uniaxial and triaxial compression tests were conducted on both room dried and water saturated samples for different lamination angles. The test results indicate that (1) the compressive strength, cohesion, internal friction angle, tangent Young’s modulus, and axial strain corresponding to the peak and residual strengths of room dried specimens exhibit anisotropic behavior that strongly depends on the orientation angle(β); (2) in comparison to the room dried samples, the compressive strength and Young’s modulus as well as the anisotropy are all reduced for water saturated specimens; and (3) the failure mechanism of the samples can be summarized into two categories: sliding along lamination and shearing of rock material, with the type occurring in a particular situation depending strongly on the lamination orientation angles with respect to the major principal stress. According to the findings, it is strongly recommended that the effect of anisotropy and water content on the strength and deformation behavior of the rock must be considered in ground control designs.

Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were used to generate datasets for training and validating models. Statistical measures including the coefficient of determination (R2) and Root Mean Square Error (RMSE) were selected to validate and compare the predictive performances of the single RF model and the hybrid RF– GA model. Furthermore, sensitivity studies were conducted to evaluate the importance of input parameters. The results show that, the proposed RF–GA model is robust in predicting the permeability; UCS is directly correlated to permeability, while all other inputs are inversely related to permeability; the effective stress exerts the greatest impact on permeability based on importance score, followed by the temperature (or gas pressure) and UCS. The partial dependence plots, indicative of marginal utility of each feature in permeability prediction, are in line with experimental results. Thus, the proposed hybrid model (RF–GA) is capable of predicting permeability and thus beneficial to precise CBM recovery.

Environmental problems caused by large amounts of CO₂ generated by coal–electricity integration bases have raised concerns. To solve these problems, this study develops a CO₂ foam concrete (CFC) material with both heat insulation and carbon fixation characteristics to realize CO₂ in situ storage and utilization. In this study, a Portland-cement-based CO₂ foam concrete (PC-CFC) with good thermal insulation performance and carbon fixation ability is prepared using carbonation pretreatment cement and a physical foaming method. The effects of CO₂ on the compressive strength, thermal insulation, and carbon fixation properties of PC-CFC are studied. The internal relationship between the compressive strength, thermal insulation, and carbon fixation performance of PC-CFC is analyzed, and the feasibility of PC-CFC as a filling material to realize the in situ mineralization and storage of CO₂ in the coal–electricity integration base is discussed. The experimental results show that the compressive strength of PC-CFC is significantly improved by CO₂ curing. However, CO₂ in the PC-CFC pores may weaken the strength of the pore structure, and the compressive strength decreases by 3.62% for each 1% increase in PC-CFC porosity. Using CO₂ as a foaming gas and the physical foaming method to prepare CFC can achieve improved thermal insulation performance. The thermal conductivity of PC-CFC is 0.0512–0.0905 W/(m·K). In addition, the compressive strength of PC-CFC increases by 19.08% when the thermal conductivity of PC-CFC increases by 1%. On the premise of meeting the thermal insulation requirements, PC-CFC can achieve improved compressive strength. The carbon sequestration rate of the PC-CFC skeleton is 6.1–8.57%, and the carbon storage capacity of PC-CFC pores is 1.36–2.60 kg/ton, which has obvious carbon sequestration potential; however, the preparation process and parameters of PC-CFC still require further improvement. The research results show that PC-CFC has great potential for engineering applications and is of great significance for realizing carbon reduction at the coal–electricity integration base.