This study investigates the influence of mean stress and Lode angle on the mechanical behavior of porous sandstone. Sandstone specimens were tested using a newly developed true-triaxial loading apparatus under five constant Lode angle conditions and seven different mean stresses, covering a transition from brittle to ductile regimes. Based on the experimental results, three types of stress-strain responses were identified, transitioning progressively from Type 1, through Type 2 to Type 3 as the mean stress increases. Type 1 response represents typical brittle behavior, characterized by prominent shear fractures. Type 2 response corresponds to the brittle-ductile transition behavior, exhibiting non-penetrating shear fractures. Type 3 response is associated with ductile behavior, characterized by no visible shear fractures. The deviatoric stress initially increases and then decreases with increasing mean stress, forming a cap surface in the meridian plane. A generalized failure criterion is subsequently developed, capable of accurately characterizing this strength response. Furthermore, the brittle-ductile transition behavior is found to be significantly dependent on the Lode angle. Finally, the brittle-ductile transition boundary is described, incorporating the dependence of Lode angle.

In the natural environment, the soil structure can be weakened by temperature fluctuations and climatic changes. Nevertheless, the dynamic behavior of expansive soils, especially those with high swelling and pronounced fissure properties, subjected to wetting-drying-freeze-thaw (WDFT) cycles has been rarely investigated. Undisturbed and remolded samples, made of Xinjiang's highly expansive soils, were evaluated in this study through comprehensive resonant column tests conducted at several confining pressures and WDFT cycles. A typical hyperbolic model demonstrated the decay law of shear modulus with strain. An estimated model of the maximum shear modulus, incorporating the two factors, was developed, and it was found to be in good agreement with the measurement results. The results reveal that strain, WDFT cycle, and confining pressure have qualitatively uniform effects on the shear modulus of natural soils containing fissures and recompacted samples. However, the maximum shear modulus of the undisturbed samples is lower by 0.83-13.24 MPa due to the presence of initial fissures, except for the confining pressure of 400 kPa. Also, their responses to confining pressure are more significant, with the shear modulus increased by up to 20 %-124 % relative to that at 25 kPa. Furthermore, the relative difference in the shear modulus (up to about 60 %) between the two samples tested under low confining pressure conditions deserves special attentions. The quantitative differences in shear modulus and cumulative damage effect of the tested samples are attributed to the initial fabric and microstructural evolution, as observed by Scanning Electron Microscope (SEM). This research enriches the theoretical framework for analyzing the ability of soils to resist shear deformation under small strain, which is instructive for disaster prevention and mitigation in expansive soil regions, considering the effects of climate change.

Traditional deterministic numerical simulation often has a poor prediction performance for landslide-induced wave run-up (LIWR) hazards, as it neglects the effects of uncertainty. The limitation for efficiently quantifying the uncertainties in primary parameters remains largely unsolved. In this study, we propose a probabilistic evaluation method, integrating the adaptive Kriging (AK) metamodel method and probability density evolution method (PDEM) based on generalized F-discrepancy. A Taylor expansion-based adaptive design strategy is applied to construct the global AK model over representative points generated by generalized F-discrepancy, thereby approximating the numerical physical response (i.e., maximum LIWR). Using these approximate responses, the PDEM is used to compute the exceedance probabilities that LIWR heights exceed elements at risk based on a construction of virtual time, and then a probabilistic criterion is introduced to classify hazard zones. The proposed method is demonstrated via two examples: Example Ⅰ, which possesses risk element (building), and Example Ⅱwith water-level variations. The results indicate that the proposed method has an acceptable performance (showing a 1.7 % difference in exceedance probability compared to Monte Carlo simulation with 50,000 samples) with low computation cost (requiring 284 deterministic analyses). For two specific scenarios in this study, the wave induced by the landslide exhibits a solitary-like leading wave. The proposed probabilistic method provides promising prospects for quantifying LIWR uncertainties, and is helpful for direct, efficient, and low-cost quantification assessment of cascading hazards.

Accurate extraction of rock mass discontinuity parameters is crucial for stability assessment and engineering safety. High-resolution remote sensing facilitates automated extraction, but its effectiveness relies heavily on precise normal estimation to ensure geometric reliability. Conventional methods struggle to preserve sharp features such as edges and corners, thereby reducing accuracy. To address this, we propose a normal estimation method based on local geometric adjustment that enhances feature extraction while maintaining sharp geometries. The approach consists of four steps: (1) classifying points, (2) applying normal and axial projections, (3) fitting segmentation lines via least squares, and (4) refining normals by optimizing local neighborhoods. The proposed method was evaluated on computer-aided design (CAD) models, real objects, and rock mass point clouds, and benchmarked against eight representative algorithms, including principal component analysis (PCA), 2-Jet PCA, Voronoi-based PCA, PCPNet, neural gradient function (NeuralGF), low rank representation (LRR), normal estimation via shifted neighborhood (NSN) and pair consistency voting (PCV). Experimental results demonstrate that our method achieves superior accuracy and efficiency, significantly improving structural plane extraction and ensuring better preservation of sharp geometric features.

Tunnel portal sections have historically been more susceptible to earthquakes than other components, exhibiting significant seismic damage. However, critical seismic behaviors of portal sections remain unrevealed owing to insufficient consideration of actual topography. Moreover, the extent of asymmetric seismic responses induced by topography remains unclear, which is essential for seismic design. To overcome these limitations, this study replicated the actual geological conditions of a tunnel portal section, including the portal slope, topography, slope and tunnel supports, and the often-overlooked portal wall using large-scale shaking table tests. The asymmetric seismic responses and their impact ranges identified in the experiments were validated through numerical simulations. The results revealed that the seismic damage to the slope is attributable to the presence of the tunnel, with slope acceleration near the tunnel portal increasing by 20 %-40 % compared to slopes without a tunnel. Additionally, the tunnel facilitates seismic wave propagation in specific directions, leading to further seismic damage across the portal section. Portal walls, being exposed structures, are susceptible to higher seismic strain and acceleration than tunnel linings and thus warrant increased attention. Importantly, the asymmetric seismic response was found to vary based on different sides and influence ranges. Within 15 m of the portal, the tunnel was dominated by the open-side asymmetric response of acceleration, strain, and displacement. From 15 to 35 m range, the seismic response of the mountainside was more pronounced, exhibiting increased seismic earth pressure and stress on the right sidewall. Seismic earth pressure and stress diminished within the 35-75 m range and steadily decreased beyond 75 m. This enhanced understanding of seismic behaviors facilitates the targeted establishment of future seismic fortifications based on these classified ranges.

Timely identification of accelerating precursors and performing reliable time-to-failure analysis are the key components in the management of slope failure risks. This study focuses on rock slope failures and proposes a framework for online identification of accelerating precursors and dynamic probabilistic prediction of failure time grounded in Bayesian inference. By integrating the Bayesian online change-point detection (BOCD) method with a typical dimensionless trend (TDT) model, the BOCD-TDT algorithm is first developed for online identification of acceleration events and their corresponding onset of acceleration (OA). Subsequently, a Bayesian approach is employed to estimate the parameters of the inverse velocity (INV) method, enabling the dynamic probabilistic prediction of slope failure time while quantifying observational and model uncertainties across different accelerating deformation stages. Building on this, the influence of starting point (SP) selection, trend update (TU), and multi-data fusion on prediction reliability is evaluated, and a novel decision criterion for impending slope failure is proposed. The feasibility of the proposed methods is then validated using 73 rock slope failure cases. Results show that using INV data, the BOCD-TDT algorithm can reliably identify acceleration events and the corresponding OA. In time-to-failure analysis, the reliability of dynamic failure predictions can be enhanced by incorporating both observational and model uncertainties corresponding to the deformation stages into the Bayesian prediction model, along with TU detection and multi-data fusion. The proposed failure probability criterion provides valuable guidance for the identification of impending failure and the establishment of ultimate alert thresholds.

This study investigates particle crushing mechanisms in granular soils during shearing through staged triaxial compression experiments performed at prescribed axial strains and varying confining stresses, integrating a high-performance acoustic emission (AE) measurement system. The study analyzed particle crushing-related parameters using grain size distribution (GSD)-based indices (relative breakage index B_r and its rate ΔB_r) and AE-based parameters (high-frequency AE hits and hit rates ). The results confirm the feasibility of high-frequency AEs (>100 kHz) in comprehensive quantification of particle crushing, with a strong linear relationship observed between and B_r. Significant particle crushing occurs within the initial 5 % of axial strain, which correlates with the yielding and peak-stress phases. This process yields fragments with a size range of 0.425-2 mm. Increased confining stresses result in a steady rise in B_r and , suggesting that large strains are required for stable particle grading. The evolution trends of different high-frequency AE ranges reveal a shift to complex crushing mechanisms, such as particle abrasion/grinding and corner breakage/particle splitting, highlighting the role of stress and strain levels in influencing particle damage behavior.

Excavation-induced retaining wall deflection (RWD) significantly influences the safety of surrounding built environment. To predict the three-dimensional RWD in heterogeneous strata, a new partial differential equation (PDE) is derived in this study, and two prediction models are proposed, i.e. the physics-informed neural network (PINN) model and the data-driven PINN model. As a physical constraint, the new PDE is crucial to the loss functions of these models. Then, the validity of the models is verified and analysed using a subway deep-foundation pit. The results show that the training times of both models are controlled within 900 s, which is a significant reduction compared to that of the conventional numerical model. In addition, the prediction accuracy of the data-driven PINN model is higher than that of the numerical model, while that of the PINN model is slightly lower than that of the numerical simulation. However, in contrast to the data-driven PINN model, the PINN model can identify irregular soil interfaces in heterogeneous strata to learn the deflection continuity conditions at irregular interfaces and realize RWD prediction in non-uniform distributed strata. In practical applications in foundation pit engineering, the selection of the PINN and data-driven PINN models can be conducted according to the in situ distribution conditions of the strata to enable the early prediction of potential RWD, thereby providing a reliable basis for the further optimisation of retaining structures design.

To realize the soil reinforced through the carbonation of ternary binder under ambient pressure and mild conditions, the present study introduces triethanolamine (TEA), which serves as an effective carbonation accelerator. Through the unconfined compressive strength (UCS) test, the soft soil solidified with ternary eco-binder consisting of ground granulated blast-furnace slag (GGBS), metakaolin (MK), and calcium carbide residue (CCR), subjected to carbonation, is investigated. The effect of TEA on the carbonation of soil is evaluated by the UCS and the CO₂ mineralization. This study clarifies the influence factors, including the initial water content, TEA dosage, binder constituent ratio, and content. The optimal binder constituent ratio for the strength growth and carbonation efficiency of carbonated soil is approximately 4:4:2 for GGBS, CCR, and MK, respectively. The incorporation of TEA at a low dosage (<0.15 %) enhances the strength of carbonated soil, whereas the high dosages impair the strength. The synergistic effect of TEA and carbonation further improves the strength and compressibility of soil. The soil with 1.5 % TEA carbonated for 7d exhibits a 44.8 % increase in strength compared to that without TEA, which is attributed to a 2.2-fold increase in carbonation efficiency. The addition of TEA accelerates the ion dissolution and CO₂ dispersion, promoting the carbonation reaction in soft soil. Calcite and aragonite precipitate during carbonation, contributing to the strength development of soil. The carbonates phase difference and the pore structure density with different TEA dosages are also demonstrated to be the strength influence factors.

Water-rich sand layers are frequently encountered as adverse geological conditions during underground construction. Polymer slurry grouting has been widely recognized as an effective technique for reducing permeability and enhancing the stability of such strata. In this study, a mathematical model is established to describe the diffusion behavior of polymer slurry in porous media under dynamic water conditions and is further validated through laboratory experiments. The theoretical formulation of the slurry permeation process is developed based on Darcy's law, the Hagen-Poiseuille flow principle, and the physicochemical characteristics of the slurry. The derivation primarily focuses on analyzing the dynamic response of the slurry under the influence of water flow, considering the effects of flow velocity, grouting pressure, and sand-layer porosity on diffusion behavior. To verify the proposed model, a visualized grouting simulation system was designed to observe the diffusion process of polymer slurry in water-rich sand layers. The results demonstrate that slurry diffusion is significantly affected by grouting pressure, porosity, and water flow velocity. The observed staged diffusion characteristics, dynamic evolution patterns, and directional effects are in good agreement with theoretical predictions. Furthermore, the average relative deviations between the theoretical and experimental results for diffusion pressure and diffusion distance are both less than 25 %, confirming the reliability of the proposed model. Additionally, this study identifies distinct differences in slurry diffusion between porous and void media. In porous media, slurry propagation encounters greater hydraulic resistance, leading to rapid pressure attenuation and a limited diffusion range. Conversely, diffusion in void media occurs more smoothly due to the continuous cavity structure, resulting in slower pressure decay and a substantially larger diffusion radius. These findings elucidate the mechanisms governing slurry diffusion under dynamic water conditions and provide a theoretical basis for optimizing grouting parameters and improving construction efficiency in water-bearing strata.