Qiang Xu

The functional performance and structural integrity of natural rock materials under fluctuating environmental stressors are pivotal for their advanced applications. As a non-ionizing and radiation-free technology, terahertz (THz) spectroscopy offers a safe and promising alternative for non-destructive testing (NDT), uniquely capable of being deployed in open and unshielded environments. However, limited penetration depth, exacerbated by both the dense geological matrix and the extreme sensitivity of THz waves to moisture states, has long hindered its widespread application in rock characterization. This study establishes a quantitative Terahertz Time-Domain Spectroscopy (THz-TDS) framework to characterize four lithologies under drying–wetting cycles. Exponential signal attenuation across thicknesses was quantified based on the Beer–Lambert law, with attenuation coefficients ranging from 0.15 to 0.74 per millimeter. Planar transmission imaging successfully visualizes lithologic and moisture-dependent heterogeneity: limestone exhibits a dense, homogeneous structure with stable amplitude distribution; sandstone and purple sandstone show parallel statistical trends, reflecting uniform pore networks; and granite demonstrates the most pronounced imaging contrast under varying moisture states, driven by complex grain-boundary scattering. The findings reveal that THz transmission is dictated by the synergistic effects of mineral compositions and pore structures: scattering at grain boundaries and fractures leads to significant energy dissipation, whereas clay-rich lithologies exhibit the highest sensitivity to moisture variations due to water adsorption and interfacial polarization effects. As an exploration of THz technology in the non-destructive evaluation of rock materials, these findings establish an analytical framework for the quantitative assessment of microstructure evolution.

To reveal the deformation and failure mechanisms as well as the fracture evolution patterns of water-bearing coal–rock composites under complex stress conditions, this study established a true triaxial stress model for the key load-bearing structure of mined coal pillar dams and developed a true triaxial loading apparatus capable of implementing localized unloading paths. True triaxial loading–unloading tests were conducted on coal–rock composites under different water content conditions, and the internal fracture structures were quantitatively characterized using CT scanning combined with fractal analysis. The results indicate that: (1) under a constant axial stress-unloading confining stress path, failure primarily occurs in the coal component, and the extent of failure significantly increases with the water content of the roof rock. For instance, the total fracture volume in the coal body increased by approximately 66% from the dry to the saturated state, while the lateral strain at peak stress decreased by about 65% over the same range, indicating a transition towards more brittle behavior. (2) CT scanning and three-dimensional reconstruction results reveal that the fracture system exhibits pronounced multi-scale polarization, with significant differences in volume, surface area, and morphological parameters between the main fractures and micropores, reflecting strong heterogeneity and anisotropy; (3) fractal dimension analysis of two-dimensional slices indicates that the fracture structures exhibit fractal characteristics in all directions, with the spatial distribution of fractal dimensions closely related to the loading direction. Overall, the XY-direction fractures exhibit the highest complexity, whereas the XZ and YZ directions show pronounced directional anisotropy. As water content increases, the amplitude of fractal dimension fluctuations rises, reflecting an enhancement in the geometric complexity of the fracture system.

Focusing on underground reservoir coal pillar dams subjected to long-term water immersion, this study employed a self-developed non-destructive water saturation apparatus to prepare monolithic and composite coal–rock specimens with varying moisture conditions. Through uniaxial compression tests combined with acoustic emission (AE) monitoring technology, the mechanical failure characteristics and energy dissipation behavior of these specimens were systematically investigated. The results indicated that both the UCS and elastic modulus (E) of the single-rock specimens decreased with increasing water content. Conversely, the mechanical properties of the composite specimens were significantly influenced by the properties and water saturation state of the rock components within the composite. When the rocks within the composite specimens share identical moisture conditions, higher rock strength correlates with greater specimen strength and strain. Under identical lithological conditions, the peak stress (σ_c), peak strain (ε_c), and elastic modulus (E) of the composite specimens decreased with increasing rock moisture content, which exhibited reductions of 45%, 21.8%, and 13.5% in σ_c, ε_c, and E, respectively, under saturated conditions. Acoustic emission (AE) monitoring data revealed that AE events in coal–rock composite specimens under uniaxial loading exhibited distinct spatial distribution patterns. Furthermore, as the rock moisture content increased, the ultimate failure mode of the composite specimen progressively shifted from shear failure within the coal matrix toward tensile failure of the composite as a whole. An analysis of the energy characteristics of coal–rock composite specimens under uniaxial compression revealed that rock properties and moisture content significantly influence energy absorption and conversion during loading. With increasing rock moisture content, the total energy, elastic strain energy, and dissipated energy at the peak load exhibited decreasing trends, reflecting the weakening effect of water on energy dissipation in coal–rock composites. This study systematically investigated the instability mechanisms of coal–rock composites from three perspectives—mechanical properties, failure modes, and energy dissipation—thereby providing valuable insights for evaluating the long-term stability of underground reservoir coal pillar dams subjected to prolonged water immersion.

Coal pillars are important safety structures for maintaining the stability of underground coal mine roadways. To address both coal resource loss from wide pillars and the need for safer, more sustainable underground building structures, this study proposes a framework for controlling the surrounding rock based on the narrow pillar. By establishing a load-bearing mechanical model for narrow coal pillars and a mechanical model for roof instability, the design principles of key parameters were clarified, including the optimal width, the required support strength for the pillar–roof system, and the height and angle of roof pre-splitting. In addition, zoning control measures and corresponding technical procedures for adjacent mining roadways were proposed. This technology was applied in Tashan Mine and, during the extraction of panel 8311, the surrounding rock stability of roadway 2312 was well maintained, with the maximum deformation of the solid coal rib measured at 135 mm, while that of the narrow pillar reached 386 mm. The proposed design method can effectively improve coal recovery in underground mining and provide theoretical and technical guidance for coal pillar stability control and wide pillar optimization under complex mining conditions.

Fractured rock masses are susceptible to stress-induced disturbances, which can lead to severe geological disasters. In recent years, the shear deformation and failure characteristics of fractured rock under cyclic shear loading have become a frontier issue in rock mechanics and engineering. A thorough understanding of the failure mechanism of fractured rock masses is of great significance for the scientific evaluation of their long-term stability in engineering applications. In this study, experiments were conducted on marble specimens with artificial fractures under constant normal stress using the RDS-200 rock mechanics shear test system. The results reveal the following three key findings: First, the residual shear displacement increases linearly with cycling numbers, and the fractures demonstrate memory functions under pre-peak tiered cyclic shear loading, with shear displacement exhibiting hysteresis effects. Second, significant differences were observed between tiered cyclic shear (TCS) and direct shear test (DST) outcomes in terms of peak shear stress and failure patterns. The peak shear strength under TCS was 17.76–24.04% lower than under DST, with the strength-weakening effect increasing with normal stress. The fracture surfaces showed more severe damage and debris accumulation under TCS compared to DST, with the contour area ratio decline rate correlating with both normal stress and initial surface conditions. Third, energy evolution analysis indicates that as cyclic shear stress increases, the elastic energy release rate exceeds the dissipation rate, and the elastic energy index progressively rises through the loading cycles. The findings of this research contribute to a better understanding of the shear instability of rock fractures under pre-peak tiered cyclic shear loading with constant normal stress.

It is vital to stabilize pillar dams in underground reservoirs in coal mine goafs to protect groundwater resources and quarry safety, practice green mining, and protect the ecological environment. Considering the actual occurrence of coal pillar dams in underground reservoirs, acoustic emission (AE) mechanical tests were performed on dry, naturally absorbed, and soaked coal samples. According to the mechanical analysis, Quantitative analysis revealed that dry samples exhibited the highest mechanical parameters (peak strength: 12.3 ± 0.8 MPa; elastic modulus: 1.45 ± 0.12 GPa), followed by natural absorption (peak strength: 9.7 ± 0.6 MPa; elastic modulus: 1.02 ± 0.09 GPa), and soaked absorption showed the lowest values (peak strength: 7.2 ± 0.5 MPa; elastic modulus: 0.78 ± 0.07 GPa). The rate of mechanical deterioration increased by ~25% per 1% increase in moisture content. It was identified that the internal crack development presented a macrofracture surface initiating at the sample center and expanding radially outward, and gradually expanding to the edges by adopting AE seismic source localization and the K-means clustering algorithm. Soaked absorption was easier to produce shear cracks than natural absorption, and a higher water content increased the likelihood. The b-value of the AE damage evaluation index based on crack development was negatively correlated with the rock damage state, and the S-value was positively correlated, and both effectively characterized it. The research results can offer reference and guidance for the support design, monitoring, and warning of coal pillar dams in underground reservoirs. (The samples were tested under two moisture conditions: (1) ‘Soaked absorption’—samples fully saturated by immersion in water for 24 h, and (2) ‘Natural absorption’—samples equilibrated at 50% relative humidity and 25 °C for 7 days).

The accurate evaluation of rock mass quality and competent roadway-support decision-making requires the rapid and accurate acquisition of the distribution of structural planes in rocks. To address this need, a program was developed that uses deep learning to automatically recognize the structural plane in-borehole images. First, borehole images from 30 mines in China were collected during field tests, and the structural planes in the images were categorized into five types. Second, a deep Coral architecture based on a convolutional neural network (CNN) was established to automatically extract features from the borehole images and classify the structural planes therein. The experimental results indicate that the CNN model classifies the structural planes in the borehole images with an overall accuracy of 86%. Validation tests in field applications demonstrated recognition accuracies ranging from 0.76 to 1.0 compared to manual markings, meeting engineering requirements. Finally, based on the proposed method, an intelligent system to recognize surrounding rock fracture was developed. Engineering application cases are presented and discussed to demonstrate the method and confirm the accuracy of this approach. Compared with traditional classification methods, the proposed method rapidly recognizes and classifies structural planes in borehole images at low cost, with precision, and in a non-destructive and automated manner.

The sandstone roof rock in the Huaibei mining area contains abundant water at depths of 2–3 m. Water–rock interactions in the rock-surrounding roadway can cause significant deformation, seriously threatening the safety of mine operations. Investigating the deformation and failure mechanisms of water-rich sandstone is therefore of critical importance. In this study, X-ray diffraction and scanning electron microscopy were used to analyze the composition and microstructure of water-rich sandstone. Based on the stress state during the roadway excavation, a true triaxial loading scheme with four different stress paths was designed to study the effects of different moisture contents and loading methods on the mechanical properties of the sandstone. The results show that the deviatoric stress decreased for all stress paths. Acoustic emission (AE) characteristics during the deformation and failure processes were also studied, which indicated that the AE b-value decreased, increased, and then decreased again corresponding to the primary compaction, elastic deformation, and plastic deformation evolutionary processes in the internal microstructure of the rock. The variation in the b-value reflected the development and expansion of internal fractures. These findings provide useful insights for controlling the stability of the surrounding rock in water-rich roadways in coal mines.

In multi-coal seam mining, when the lower coal seam mining face passes over the goaf, residual coal pillars, and other geological anomaly areas of the overlying coal seam, abnormal mine pressure appears, and the hydraulic support monitoring system is inaccurate in identifying the pressure, which brings great hidden dangers to the safe production of the mining face. It is very necessary to carry out the prediction and early warning of the mine pressure of this kind of mining face. In order to improve the reliability of the prediction model, this paper takes the 31317 mining faces of the Chahasu coal mine as the engineering background, studies the mechanism of the disaster caused by the abnormal mine pressure of the residual coal pillar, uses the clustering analysis algorithm to divide the abnormal mine pressure area of the mining face, reconstructs the abnormal mine pressure type and number based on the prediction results of CEEMDAN–Transformer deep learning, and proposes the disaster criterion of the abnormal mine pressure. The research results show that, when the 31317 mining face enters the goaf of the overlying 31203 and 31201 coal seams, the residual coal pillars are accompanied by the instability of the interlayer rotation, and the dynamic and static loads are superimposed to form the additional stress of the residual coal pillars and transfer downward, causing the abnormal mine pressure of the mining face to appear; based on the hydraulic support resistance data of the mining face within the range of 3921.4–5050.4 m advance, the clustering analysis results show that there are six abnormal mine pressures during this period, and the types are cutting eye, residual coal pillar, square breaking, previous working face goaf square breaking, double square breaking, and geological damage zone. The clustering analysis is used to reconstruct the abnormal mine pressure area based on the prediction results of the mine pressure time series (MPTS) after interpolation completion, decomposition, and noise reduction preprocessing, and the MAE values are all lower than 2000 kN, predicting that there will be one abnormal pressure between the 80#–129# hydraulic supports in the process of advancing to 5050.4–5219.5 m, corresponding to the 18th square breaking area of the working face. Through the verification in the actual production, the prediction result is accurate; when the predicted value of the hydraulic support working resistance is greater than 19,000 KN, measures should be taken to speed up the advancing speed of the mining face, quickly pass through the abnormal mine pressure area, and prevent the disaster caused by the abnormal mine pressure. The prediction clustering analysis reconstruction abnormal pressure analysis method based on mining working face mine pressure data proposed in this paper provides a new direction and guidance for the abnormal mine pressure prediction analysis of mining working face and has good foresight, good intelligent prediction, and a good analysis method for the intelligent empowerment of mine safety production.

Coal mining has caused groundwater pollution and loss. Using a mined area as a water storage space for storing and purifying mine water is a low-cost environmentally friendly mining method. In this study, static and dynamic adsorption experiments on the ions in mine water were carried out using the roof rocks from the Lingxin coal mine. The sample analysis results show that the main chemical composition of the roof is mainly SiO₂ and Al₂O₃. The water chemistry type of the mine water is SO4-HCO3-Cl-Na type, with an average mineralization of about 4000 mg/L. The experimental results show that gangue can stabilize the pH value of mine water with different pH values between 7.5 and 8.5. In the acidic and alkaline environment, the degree of void space increases the adsorption capacity of the gangue, in which the adsorption rate of gangue is between 3% and 5%. The calcium ion reduction rate reaches 75% in static leaching and 70% in dynamic leaching conditions. Medium-grained coarse sandstone has a stronger adsorption capacity than muddy siltstone. The results from this study can support further research on using gangue for water purification purposes in mines, simultaneously reducing the harmful accumulation of gangue and promoting the recycling of highly mineralized water.