Ice avalanches are a primary trigger for glacier-related disaster chains in high-mountain regions. Understanding how boundary conditions influence the dynamics and deposition of ice avalanche debris flows is crucial for deciphering the evolution of such disaster chains. This study systematically investigates the motion and depositional behavior of ice avalanche debris flows under varying mass, elevation differences, slope gradients, and toe constraints, utilizing a chute-based experimental setup within a low-temperature laboratory. Key parameters, including flow velocity, basal force, and deposition morphology, are analyzed throughout the debris flow movement. Results indicate that elevation differences and mass govern the dynamic energy transfer within the flows. Specifically, elevation differences control depositional dispersion by regulating peak flow velocity, while mass influences travel duration, resulting in a positive correlation between run-out length and deposit thickness. Furthermore, topographic conditions significantly affect energy dissipation during deposition. An increased slope gradient in the run-out zone reduces basal resistance, thereby expanding the depositional area and enhancing particle scattering at the flow front. A wider slope toe promotes lateral spreading, increasing travel distance and shifting the mass center, which transforms deposit morphology from tongue-shaped to fan-shaped. Finally, theoretical analysis confirms that run-out distance is dictated by the efficiency of kinetic energy transfer among particles and their interaction with the substrate, exhibiting a positive correlation with both particle energy-transfer efficiency and fluctuations in basal stress.

This paper investigates the effect of anisotropic stress states on the small strain stiffness of red mudstone fill material (RMF). A comprehensive experimental program was conducted, including 18 triaxial-bender element tests, 4 isotropic consolidation tests, and 6 stress-controlled loading-unloading tests. The results indicate that the normalized strength is well characterized by the nonlinear strength envelope. Under isotropic stress conditions, the small strain stiffness increases with mean stress, which can be described by a power equation. During conventional triaxial shear, small strain stiffness increases at low axial strains. When the axial strain exceeds 2%, the damage point can be identified, at which point small strain stiffness decreases by more than 25% with further axial strain. A power model has been employed to characterize the small strain stiffness and shear stress at both the damage point and peak point. Unloading at stress states below the damage point results in an increase in small strain stiffness. Conversely, due to irreversible structural disturbance, unloading at stress states above the damage point leads to a progressive reduction in small strain stiffness. The difference in small strain stiffness at various unloading points can exceed 30%. Therefore, the coupled effects of stress history and stress path should be considered for accurate determination of small strain stiffness, as the conventional monotonic model is not applicable in such coupled scenarios.

Current research on tunnels crossing active faults primarily focuses on individual tunnel cases, while the group tunnel effect in tunnel groups has not been systematically addressed. The influence of high internal water pressure on deformation mechanisms is rarely considered. This study employs physical model tests and numerical analysis under high internal pressure to investigate the fault resistance of tunnel groups. The results demonstrate the following: (1) Corrugated expansion joints significantly enhance fault resistance, delaying and reducing peak longitudinal strain (with maximum tensile strain reduced by 69% and compressive strain by 48%) and converting shear failure into coordinated deformation. (2) Group effects intensify the fracturing of surrounding rock during dislocation, resulting in a complex “Y-shaped intersecting crack system.” (3) The sides of adjacent tunnels exhibit higher strain responses than the outer sides (with peak compressive strain at 87% and longitudinal tensile strain at 35%), indicating tunnel-rock-tunnel interaction. (4) Earth pressure between tunnels increases abnormally due to group effects, while the pressure on the outer sides remains largely unaffected. (5) The mechanical response of the lining (axial and shear force) strengthens with smaller tunnel spacing but diminishes and stabilizes as spacing increases. This study reveals the failure mechanisms of high-pressure hydraulic tunnel groups, providing insights for fault-resistant designs in seismic zones.

To identify the distribution differences between fractures and interlayer gravels within glutenite cores, accurately evaluate spatial heterogeneity, and enhance hydrocarbon recovery efficiency, this study employed elastic ultrasonic wave velocity—a parameter highly sensitive to variations in the internal rock structure—to measure wave velocities in 18 outcrop cores collected from the Shawan Sag in the Junggar Basin. A non-destructive evaluation method for heterogeneity was established based on stratified elastic wave velocity measurements. Fifteen samples were utilized as test cores for heterogeneity assessment using this method, while the remaining three served as validation cores, with their velocity distributions compared for verification. The results demonstrate that: (1) the proposed method effectively identifies heterogeneity characteristics, such as gravel distribution and pore-fracture networks in glutenite, enabling an accurate assessment of spatial heterogeneity; (2) the method offers several advantages over conventional heterogeneity evaluation techniques, including non-destructiveness, high sensitivity, rapid measurement, and cost-effectiveness; and (3) consistent heterogeneity evaluation results were obtained between the test and validation cores. Therefore, this method can serve as a valuable reference for heterogeneity assessment in glutenite reservoirs.

Conventional finite element methods for large-scale numerical simulations are often constrained by high computational demands and extended runtimes. To enhance efficiency, we developed a predictive model based on a backpropagation (BP) neural network. A three-dimensional finite element model of a buried pipeline with corrosion defects crossing a reverse fault was established using ABAQUS. We systematically analyzed the effects of four key parameters—corrosion depth-to-thickness ratio, diameter-to-thickness ratio, internal pressure, and burial depth—on the seismic response of the pipeline. In this parametric study, fault displacement and the four key parameters served as inputs to the BP neural network, with the pipeline’s axial peak compressive strain as the output. The model was trained and validated using training, validation, and test datasets. Results indicate that increasing the corrosion depth-to-thickness ratio, diameter-to-thickness ratio, internal pressure, or burial depth reduces the fault displacement necessary for the lower section of the pipeline to reach its strain limit. Failure modes differ between unpressurized and pressurized pipelines, exhibiting inward local buckling and outward bulging, respectively, at stress concentration zones. The four parameters are highly correlated with the compressive strain response, with correlations transitioning from linear to nonlinear as fault displacement increases. The trained BP neural network achieves maximum prediction errors of 13.60% on the validation set and 12.84% on the test set, both below 15%, demonstrating robust accuracy and generalization in predicting the seismic response of in-service buried pipelines across reverse faults.

Significant limitations and hysteresis are presented in dynamic prediction methods driven by on-site monitored displacement data for tunnel surrounding rock deformation. By comprehensively utilizing the physical information contained in tunnel construction project documents and the mathematical information from displacement time-series curves, a modelling method based on the dynamic Bayesian network (DBN) was developed using the concept of physical information machine learning (PIML) to achieve dynamic predictions of surrounding rock deformation. Through discretization processing and reconstruction of displacement time-series curves, a static sample database was established by combining physical information data with ultimate displacement data, while a dynamic sample database was created by integrating physical information data with displacement time-series curve data. Based on the characteristics of the static samples, the K2-score algorithm was improved to construct a static Bayesian network (BN) model for ultimate displacement prediction. Utilizing the static BN model and the characteristics of the dynamic samples, physical-data dual-drive modelling methods for the Markov DBN were derived by incorporating prior information, including the constraints of steady-state random processes and Markov process constraints. By integrating prior information for constraint-enhanced optimization, the optimized Markov DBN model was established. Five-fold cross-validation tests revealed that the prediction capability of the Markov DBN model decreased rapidly over time and that the network transition direction significantly affected this capability. In contrast, the prediction ability of the optimized Markov DBN model remained robust over time, was unaffected by the network transition direction, and significantly exceeded that of the Markov DBN model, as the optimized model enhanced constraint connections between target nodes and influencing factor nodes throughout the entire timeframe. Through engineering case analysis, it was concluded that before and during the early stages of tunnel construction, the optimized Markov DBN model could effectively predict displacement time-series curves, overcoming the limitations and hysteresis inherent in traditional methods. Furthermore, during construction, self-updating of the optimized Markov DBN model and dynamic predictions of surrounding rock deformation could be achieved by inputting the on-site monitored displacement data.

Geothermal energy, a renewable resource with immense potential, has garnered significant attention. In deep geothermal reservoirs, artificially stimulated fracture networks serve as critical pathways for heat extraction. Consequently, the permeability and spatial distribution of these fractures directly impact heat extraction efficiency. This study conducted shear-seepage experiments on a single rough granite fracture under varying confining pressures, shear displacements, and fracture roughnesses. A nonlinear relationship between permeability and the aforementioned three factors was established based on the experimental results. This relationship was then integrated into the THM coupled framework TOUGH2MP-FLAC^3D to assess the long-term performance of Enhanced Geothermal Systems (EGS) under varying fracture networks, fracture densities, and horizontal stress ratio conditions. The findings reveal that fracture permeability exhibits an exponential negative correlation with confining pressure, a logarithmic positive correlation with shear displacement, and a quadratic correlation with fracture roughness. Increased fracture density significantly enhances thermal performance; as fracture densities increase from 0.1 to 0.25, the thermal breakthrough time extends by up to 6.4 years, the EGS lifespan increases by up to 13 years, and total heat production rises by approximately 22.5%. Horizontal stress anisotropy negatively affects thermal performance, while higher fracture density effectively mitigates the reduction in heat extraction caused by stress anisotropy. This work provides a theoretical foundation for hydraulic fracturing during the stimulation of hot dry rock reservoirs.

How can the essential requirements of retention, hydraulic conductivity, and clogging for geotextile filters be simultaneously satisfied? Coordinating the assessment of their seepage stability performance is crucial. To achieve this, sixteen soil-geotextile column hydraulic gradient ratio tests were conducted using four typical geotextiles. The seepage stability was evaluated based on hydraulic conductivity, stable hydraulic gradient ratio, and the washout of soil fines observed during the tests. Additionally, both the grain size of the soil and the constriction size of the geotextile were treated as random variables. Utilizing soil-water interaction theory, a retention assessment approach was proposed based on the probability of ineffective retention. The performance limits of retention were determined using data from eighty-five experimentally assessed soil-geotextile columns. Furthermore, a hydraulic conductivity assessment approach was developed, considering the partial clogging of the geotextile due to the formation of a bridging structure. The results indicate that the proposed design criterion surpasses previously published criteria in effectively distinguishing between clogging or blinding in ineffective and effective systems. It was found that polypropylene long-filament geotextiles with a high mass per unit area are particularly well-suited for use as filters.

Coral sand deposits in the islands and reefs of the South China Sea are vulnerable to seismic liquefaction. Shear wave velocity provides a rapid and non-destructive method for assessing liquefaction potential; however, existing criteria, primarily developed for quartz sands, exhibit limited applicability to coral sands. This study aims to establish a specific relationship between shear wave velocity and cyclic resistance ratio for coral sand. A series of cyclic undrained triaxial tests and bender element tests were conducted using a GDS dynamic triaxial system on saturated coral sand from the South China Sea and comparable quartz sand. Systematic measurements of cyclic resistance and shear wave velocity were obtained for both materials, leading to the development of a quantitative model relating shear wave velocity to cyclic resistance for coral sand. The validity and engineering applicability of the proposed model were further validated through a case study of typical liquefaction sites, resulting in an empirical equation for the critical shear wave velocity of coral sand. The results indicate a strong correlation between shear wave velocity and cyclic resistance ratio in coral sand, with coral sand exhibiting significantly higher shear wave velocity than quartz sand at equivalent cyclic resistance ratio levels, thereby confirming their intrinsic mechanical differences. The proposed model effectively characterizes the liquefaction resistance of coral sand under varying seismic intensities and can accurately delineate liquefied layers in case analyses. This research provides a valuable reference for seismic safety assessments and foundation design in coral sand sites, such as islands and ports in the South China Sea.

Multiple drying-wetting, freeze-thaw, and drying-wetting-freeze-thaw cycle tests were conducted on intact expansive soil. This was followed by conventional shrinkage tests and controlled suction desorption tests on saturated samples under each cycle condition to investigate the differences in the effects of drying-wetting, freeze-thaw, and combined drying-wetting-freeze-thaw cycles on the soil-water characteristics and shrinkage behavior of expansive soil. The results indicate that the yield suction (s_y) and shrinkage limit suction (s_SL) divide the desorption process of saturated expansive soil into three zones: (1) when s<s_y, the soil is in the elastic zone, (2) when s_y≤s≤s_SL, the soil is in the elastoplastic zone and (3) when s>s_SL, the soil is in the shrinkage limit zone. Following drying-wetting (DW) cycles, the expansive soil exhibited the highest critical suction, water retention capacity, air entry value, yield suction, and shrinkage limit suction, with freeze-thaw (FT) cycles yielding intermediate values, while drying-wetting-freeze-thaw (DW-FT) cycles resulted in the lowest values. Under various cycling conditions, the e-S_r curves during desorption can be approximately divided into three segments: a gentle segment, a steep descending segment, and a vertical segment. The shrinkage deformation was essentially completed after the steep descending segment. The degree of saturation (or void ratio) decreased (or increased) with the number of cycles and eventually stabilized. Notably, the first cycle caused the most significant reduction (or increase), with the degree of saturation (or void ratio) stabilizing after three cycles. The dry shrinkage degree of saturated expansive soil was greatest after DW cycles, followed by DW-FT cycles, and smallest after FT cycles. A model for the Soil Shrinkage Characteristic Curve (SSCC) and Soil-Water Characteristic Curve (SWCC) of saturated expansive soil, incorporating the effects of DW, FT, and DW-FT cycles, was proposed, and the fitting results demonstrated good agreement with the experimental data.