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To investigate the effects of confining stress on the fracture behavior of rock masses under deep high-stress environments, this study employed stereolithography 3D printing technology to fabricate rock-like specimens featuring Cracked Chevron Notched Brazilian Disc (CCNBD) geometry. Static fracture tests under varying confining stress were conducted using a custom-designed confining stress loading system. The key findings are as follows: 1) Fracture toughness exhibited a linear increase with confining stress. When the confining stress reached 1.168 MPa, the fracture toughness increased to 2.86 times that of the unconfined specimen. 2) Crack propagation paths were influenced by confining stress. Under zero confinement, cracks propagated straight through the specimen. Increasing confining stress caused significant deflection in the crack propagation path. Concurrently, the fractal dimension of the fracture surface showed a positive correlation with increasing confining stress. 3) Confinement constrained lateral deformation and altered fracture characteristics. The presence of confining stress constrained lateral deformation under load. As confining stress increased, the resulting fracture surfaces became progressively rougher, and the corresponding energy release rate of the specimens demonstrated an increasing trend. These research outcomes hold significant theoretical and practical importance for enriching the understanding of fracture mechanisms in deep rock masses subjected to external loads.

To address challenges associated with the stability assessment and engineering control of buckling failure in steeply inclined rock slopes, this study takes the southern slope of the Longyu Open-Pit Mine as a case study and adopts an integrated approach combining theoretical modeling, field monitoring, and numerical simulation. First, under the assumptions of coordinated deformation and small strain, a differential equation governing the behavior of the surface rock layer is derived. This leads to the formulation of a safety factor defined as the ratio of the critical to the actual slope length. The analysis indicates that the slope remains stable when the thickness of the rock layer exceeds 10 m and the elastic modulus is greater than 32 GPa, thereby establishing a robust mechanical model for buckling failure. Second, based on field monitoring data of displacement and strain, orthogonal testing and factor sensitivity analyses are conducted. The results reveal the following ranking of influential factors: rock layer thickness (R= 0.38+39.8 %) is an exceptionally sensitive positive factor; cohesion (R= 0.25) is a highly sensitive positive factor; unit weight and groundwater level are significantly sensitive negative factors; whereas the influence of elastic modulus is negligible (R= 0.03). These insights provide a clear priority hierarchy for monitoring and stability control measures. Finally, by incorporating real-time rainfall intensity data, FLAC3D simulations demonstrate a strong negative correlation between rainfall intensity and slope stability. Heavy rainfall is identified as a critical threshold triggering stability failure. Under such conditions, the maximum slope displacement increases by 175 %, reaching 5.5 m, and the shear strain increment develops into an arc-shaped sliding surface. The slope interval between 1360-1390 m is identified as the core risk zone, while the interval from 1290-1310 m acts as a key shear outlet. This clarifies the evolutionary pathway and key focus areas for preventing rainfall-induced instability. The findings of this study offer a solid theoretical foundation and practical technical support for the monitoring, risk warning, and engineering management of similar steeply inclined slopes.

Aiming at the problem that the scraper conveyor in the steeply inclined working face is prone to sliding instability and causing safety accidents under the coupling load of the shearer, a safety mechanics analysis of sliding was carried out to provide quantitative theoretical support for the anti-sliding safety control of the equipment. By combining theoretical modeling, numerical simulation and experimental testing, a load transfer model of the shearer cutting and a sliding mechanics model of the n-segment series scraper conveyor were established. The force balance equation of a single middle trough and the critical criterion for the overall sliding of the system were derived. The EDEM and RecurDyn co-simulation was used to analyze the influence of key factors such as two coal and rock strengths of 1.2 MPa and 2.6 MPa and working face inclinations from 30° to 60° on the sliding characteristics of the scraper conveyor. A 1:5 scale dynamic load sliding test bench was built, and the dynamic load of the shearer was simulated by a shaker. The rationality of the theoretical model was verified through multi-condition tests. The results show that the shearer load acting section is the weak force section between the sections of the scraper conveyor. When there is no hydraulic support restraint, as the working face inclination increases from 30° to 60°, the force between the sections of the shearer acting section increases from 150 N to 350 N, with an increase of 133 %. At a 45° inclination, the sliding driving force of the shearer acting section has exceeded the maximum static friction force in the unrestrained state, and there is a risk of local sliding, but the overall system remains stable. After applying the hydraulic support restraint force, the force between the sections of the shearer acting section at a 60° inclination decreases by more than 48 %, and the maximum static friction force of the acting section can completely counteract the sliding driving force, eliminating the risk of local sliding and achieving the overall sliding stability of the scraper conveyor. The research reveals the sliding instability mechanism of the scraper conveyor under the coupling load of the shearer, clarifies the key parameters for sliding safety control, and provides important theoretical and experimental basis for the anti-sliding safety design and on-site control of the scraper conveyor in steeply inclined working faces.

Blast wave is one of the main damage parameters generated by ammunition explosions. Clarifying the distribution pattern of blast wave pressure field in ammunition explosions is of great significance for evaluating the damage power of ammunition and guiding ammunition design. This study is based on the ground-reflection pressure and free-field pressure mapping model, considering the influence of altitude and surface material acoustic impedance on the distribution law of blast wave pressure. A reconstruction model of explosion blast wave pressure field was constructed, and experimental tests were conducted in typical scenarios to verify the accuracy of the pressure field reconstruction model. The results show that the blast wave pressure field reconstruction model proposed in this study can well reflect the pressure distribution law, with a reconstruction accuracy of better than 93.9 %, which compensates for the shortcomings of insufficient pressure distribution data in the pressure field reconstruction process. It provides theoretical and data support for accurate evaluation of ammunition explosion damage power and has significant military application value.

Reliable operation of auxiliary equipment is critical for hydropower stations. However, data-driven diagnosis faces the “cold start” challenge due to fault sample scarcity in high-maintenance environments. We propose a few-shot diagnostic model, Siamese Cross-Attention Network (Scan-Net), combined with a transfer learning strategy. To extract discriminative features from limited data, we utilize Multi-Scale Synchrosqueezed Wavelet Transform (MSWT) for physically consistent time-frequency representations. Unlike simple concatenation, we design a dual-stream Siamese network with a bidirectional Cross-Attention mechanism that enables explicit inter-sensor feature interaction. We introduce a Deep Mutual Learning (DML) strategy with symmetric KL divergence constraints to align prediction distributions between dual branches, serving as self-supervised regularization to prevent overfitting. We establish a transfer pathway from public datasets to field equipment. Experiments show that Scan-Net achieves 96.50 % accuracy on the CWRU dataset under the 10-shot setting, and 94.43 % average accuracy in cross-load transfer. Pilot deployment at a large-scale hydropower station provides preliminary validation, with the system contributing to a reduction in routine inspection workload

Slope stability in seismically active areas is a crucial issue in geotechnical design, as failure can have severe consequences for infrastructure and public safety. This study explores modern methods for calculating slope stability under seismic loads, including the limit equilibrium method (LEM), the finite element method (FEM), and the difference element method (DEM). Numerical modeling was conducted using the PLAXIS, GeoStudio, and Slide software packages. A parametric slope stability analysis was performed, considering various values of seismic acceleration, slope angle, and pore pressure. The stability factor calculated using the Bishop method (LEM) was compared with the results from FEM and DEM to assess the accuracy and limitations of each technique. The study revealed that the stability factor (FS) decreases as the slope angle and seismic acceleration increase. When the acceleration reaches 0.3 g, the stability factor falls below the critical value (FS < 1.0), indicating an increased likelihood of slope failure. Although FEM and DEM methods provide more accurate modeling of deformations and failure mechanisms, LEM, which is based on static equilibrium, may overestimate slope stability. This research highlights the effectiveness of numerical modeling in predicting slope stability under seismic loading. Future investigations are recommended to develop hybrid models that combine LEM, FEM, and DEM, apply machine learning methods for predictive stability analysis, and consider long-term factors such as soil erosion and cyclic seismic loads. The findings can be utilized to improve slope design safety and enhance the resilience of infrastructure in seismically active regions.

This paper presents the development of a wearable system for human motion monitoring based on an inertial measurement unit (IMU). The proposed device enables real-time acquisition of angular velocity, linear acceleration, and orientation parameters of a body segment. An experimental prototype was implemented using an IMU sensor, Arduino Nano, and a data recording module. Laboratory tests focused on dorsiflexion and plantarflexion movements of the ankle joint. The results demonstrate that the system can accurately capture motion parameters and reflect changes in the Pitch angle corresponding to these movements. The proposed approach can be applied in motion analysis and rehabilitation monitoring. Future work includes integration of EMG and force sensors to extend the system functionality.

In this paper, the vortex flow structures formed behind a square cylinder and their spectral properties are numerically investigated based on the 2D URANS k-ω SST model (Re ≈ 4.7×104). The study compared locally densified and adaptive anisotropic (Hessian-based) meshes. The calculations were performed using the PISO algorithm and second-order accuracy (CFL ≤ 1, Δt≈T/200). The results were compared with experimental data on Strouhal number, drag and lift coefficients, and velocity profiles. The adaptive mesh more accurately represents the wake zone and sharp gradients of the flow, allows for reliable estimation of spectral parameters (frequency and amplitude), and reduces numerical diffusion. Some limitations of the 2D URANS model are also indicated.