This study presents a novel framework for evaluating slope stability in spatially variable soils by integrating a newly developed sequential limit analysis based on the Hellinger-Reissner functional, utilizing the node-based smoothed finite element method (NS-FEM), with a newly proposed deep learning (DL) approach termed multi-downsampling hybrid Linformer-convolutional neural networks (CNNs). The NS-FEM-based mixed formulation of limit analysis (MFLA) enhances computational accuracy and convergence by smoothing strain fields and mitigating numerical discontinuities commonly encountered in standard finite element methods (FEMs). This method generates reliable datasets for stochastic simulations of slope stability under both static and seismic loading conditions. To address the computational expense of specific simulations, we propose the multi-downsampling hybrid Linformer-CNN model, a sophisticated DL architecture that employs dual parallel pathways with distinct downsampling strategies - AveragePpooling1D for medium-scale feature extraction and MaxPooling1D for coarse-scale feature extraction. Each pathway integrates one-dimensional (1D) CNNs for local feature extraction and Linformer-based self-attention mechanisms to efficiently capture global dependencies. The parallel downsampling strategies balance computational efficiency with feature granularity, enabling the model to leverage both local and global data characteristics effectively. The extracted multi-scale features are concatenated and further processed through fully connected networks (FCNs) to accurately predict the factor of safety (FoS) of slopes. Comparative analyses demonstrate that the hybrid Linformer-CNN model outperforms traditional FCN and CNN architectures, achieving robust and precise predictions with a mean absolute percentage error (MAPE) below 10 %. Additionally, the proposed framework significantly reduces computational time, highlighting the potential of integrating NS-FEM-based MFLA with advanced DL architectures for rapid and reliable slope stability assessment in geotechnical engineering.

The time-dependent failure of surrounding rock in deep engineering is essentially controlled by the evolution of microcracks, with the pre-existing fracturing state induced by excavation playing a crucial role in the subsequent time-dependent fracturing process. From the perspective of microcrack development, it is a continuous, dynamic process. Therefore, taking the microcrack propagation process as the fundamental principle, this paper proposes a novel three-dimensional (3D) time-dependent model for hard rock that can depict the entire fracturing process within a unified theoretical framework. This developed model discards the traditional tri-modal partition method based on deformation, and instead adopts an analysis approach centred on time-dependent tensile and shear fracturing. The results show that the time-dependent deformation of hard rock is the macroscopic manifestation of the progressive evolution of microcracks over time. Under true triaxial stress, the growth tendency of cracks in hard rock is orientation-dependent throughout the entire loading process. This developed model provides a mechanical explanation for key time-dependent fracture characteristics observed in true triaxial creep tests, including the anisotropy of time-dependent deformation and the preferred orientation of macroscopic failure plane, and provides a novel framework for elucidating the time-dependent failure process of hard rock.

This study investigates the effectiveness of combined tip-and-side post-grouting on large-diameter bored piles in deep fine sand layers. Field tests were conducted on nine piles for the Shishou Yangtze River Highway Bridge project. A detailed comparison of pile performance pre- and post-grouting assessed the technique's influence on ultimate bearing capacity and side resistance. The distribution and effectiveness of the cement grout were analysed using core drilling and the standard penetration test (SPT). An equation correlating post-grouting side resistance with the pre-grouting SPT index (N_SPT) was established. Results demonstrate a substantial improvement in pile bearing capacity after grouting. Ultimate bearing capacity increased by 76 %-152 % after grouting. Longer piles on the main bridge exhibited more pronounced enhancement, achieving ultimate capacities 145 %-206 % higher than those of the shorter approach bridge piles. This is attributed to the greater total cement volume applied along their sides. Critically, combined grouting outperformed side-only grouting, enhancing both side and tip resistance. Core drilling confirmed the spread of cement grout around the piles, confirming the method's effectiveness. SPT results indicated significant increases in the soil N_SPT adjacent to the piles following grouting. These findings provide directly applicable data for designing the bridge pile foundations and offer essential guidance for comparable projects in deep fine sand layers.

Rock mass discontinuities arise from tectonic movements and other geological processes, reflecting the evolution of the Earth's crust. These discontinuities significantly influence the physical properties, deformation characteristics, and energy release mechanisms of the crust. Therefore, recognizing discontinuities is crucial for understanding the evolution of geological structures, analyzing the physical and mechanical properties of geological bodies, and investigating geological hazards. Traditionally, discontinuity recognition has relied on manual interpretation or automated algorithms based on pixel brightness. However, these methods often struggle to strike a balance between efficiency and robustness. To overcome these limitations, we leveraged deep learning techniques that integrate the strengths of both approaches, enabling the recognition of automated discontinuity with expert-level accuracy. To accomplish this objective, we developed and open-sourced the first large-scale deep learning database for rock mass discontinuities, featuring over 300,000 annotated discontinuities. The YOLOv8x-seg model was extensively trained on this database and evaluated across diverse and complex scenarios. The results demonstrated the model's capability to accurately recognize discontinuities even under challenging conditions. Furthermore, we expanded the test set to include rock masses from various global locations, as well as underground rock masses, soils, and artificial structures, where the model consistently achieved effective recognition. The model consistently delivered accurate results, highlighting its strong generalization capability. A comparative analysis revealed that its performance closely aligns with expert manual interpretations. Our open-source database enables researchers to train various deep learning models and achieve equally high-performance results.

The mixed rock-ice deposits in high-latitude areas usually come from the accumulation of rock-ice avalanches. Melting tests and temperature-controlled triaxial tests were conducted on rock-ice mixture samples with varying volumetric ice contents (0.25, 0.5, and 0.75), environment temperatures (0.5 ℃, 1 ℃, and 1.5 ℃), and temperature control durations (20 min, 40 min, and 60 min), aiming to investigate the thermodynamic behavior of rock-ice mixed deposits under an ablation environment. Our findings reveal that the melting behavior of rock-ice mixtures mainly occurs in the surface layer; then, ice meltwater transports along the surface seepage path to the bottom of the sample. Notably, the basal meltwater gathering zone leads to accelerated melting of the ice debris, and the cohesion and occlusion between the rock debris in this zone almost disappear, ultimately resulting in severe basal damage. Triaxial test results indicate that the basal damaged zone leads to an easy initial compression process of the rock-ice mixture samples and forms a basal strain effect. Statistics show that ice content, environment temperature, and temperature control duration all show a negative impact on the mixture's peak strength in thaw environments, which also exacerbates the basal strain effect, with a maximum basal strain of 8.61% and a corresponding mass loss ratio of 28.69%. Finally, the mechanisms of the secondary sliding of the mixed deposits and the failure mode of the rock-ice deposit dams induced by ice debris melting were discussed.

In this study, the influences of the thermoelastic effect and fluid viscosity-temperature effect (VTE) on hydraulic fracture growth in deep reservoirs were investigated. A computational model that integrates the thermoporoelastic effect and VTE was developed on the basis of the displacement discontinuity method (DDM). The temperature distribution within fractures is determined using a first-order upwind scheme. Using this simulator, this study systematically evaluated the impacts of the poroelastic stress, thermoelastic stress, and VTE of the fracturing fluid on fracture propagation. Furthermore, the dominant controlling factors were identified in both the viscosity- and toughness-dominated regimes. The results show that (1) the thermoelastic stress exhibits behavior opposite to that of poroelastic stress, reducing the injection pressure and increasing the fracture width. (2) Under viscosity-dominated conditions, the influence of the VTE is more remarkable, whereas the thermoelastic effect on fracture propagation is relatively weak. Under toughness-dominated conditions, the influence of the thermoelastic effect on fracture propagation remains relatively weak, and the VTE can essentially be disregarded. (3) When proppant transport is considered, for small proppant particles, the transport distance increases from 88 m to 100 m when the VTE is considered because the VTE increases the fracture length. For large proppant particles, owing to the decrease in viscosity with increasing temperature, the proppant transport distance is significantly reduced from 86 m to 70 m. These results indicate that reasonably selecting the proppant size and paying more attention to the VTE of the fracturing fluid in deep reservoir fracturing are crucial.

In hard rock tunnel excavation, controlling the blasting profile to prevent overbreak and underbreak is critical for safety and cost-effectiveness. Discontinuities such as joints and faults significantly affect the mechanical properties of the rock mass, and their distribution critically influences the blasting outcomes. This study explores the impact of joint distribution on the tunnel blasting profile through field measurements and numerical simulations. Real-time monitoring of the tunnel face was conducted using the digital twin method, capturing both rock discontinuities and blasting profiles. Field results revealed that overbreak tends to occur at joints outside contour boreholes, where the joints lead the blasting profile diverging from the borehole connection line. To quantify this effect, dynamic finite element simulations were conducted to assess the influence of borehole-joint distances (d = 25 cm, 50 cm, and 100 cm) and intersecting joint angles (α = 60°, 90°, and 120°) on blasting stress wave propagation and rock fracture development. The results demonstrated that joints within the hard rock mass guide and restrain the propagation of blasting stress wave, leading to the formation of a fracture zone induced by the reflected stress wave (the RSW fracture zone). The morphology of the RSW fracture zone closely matched the field blasting profile, validating the numerical simulation results. Furthermore, the borehole-joint distance and the intersecting joint angle were found to govern the extent and geometry of the RSW fracture zone. These findings provide valuable insights for optimizing blasting designs in jointed hard rock masses to control tunnel excavation profiles better.

The ISRM-suggested Brazilian disc (BD) test using split Hopkinson pressure bar (SHPB) for dynamic rock tensile strength requires central crack initiation and stress equilibrium. This study aims to re-evaluate the critical strain rate, ensuring a valid dynamic Brazilian disc test, and to analyse the reliable dynamic tensile behaviour of granite using high-speed digital image correlation (DIC). The comparison between the measured strain obtained through high-speed DIC analysis and the strain gauge allowed for determining the optimal subset parameters used to obtain the real-time deformation field and the stress-strain curve from DIC data. Crack initiation, crack velocity, and failure process are studied to reveal the rate dependence of granites. A unified dynamic increase factor (DIF) model is proposed for the tensile strength of rocks, and the reason for the sudden drop in DIF for high strain rates is discussed. The results reveal that the upper limit of the valid strain rate, which ensures the validity of the ISRM-suggested dynamic BD test, is co-determined by the conditions of stress equilibrium and crack initiation from the centre of the disc. At higher strain rates (75 s^-1), BD test results fail to capture the actual tensile behaviour of rocks, and the potential factors influencing the critical valid strain rate (CVSr), such as sample radius and boundary crack length, should also be considered.