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.

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.

Rock masses often exhibit significant size effects under uniaxial compression, yet the underlying mesoscopic controlling mechanisms and sensitivity to crack parameters remain poorly understood. In this study, we conducted uniaxial compression and acoustic emission (AE) monitoring experiments on granite specimens of various laboratory scales. By incorporating constraints from X-ray diffraction (XRD) mineral composition and AE-guided micro-crack data, we established a numerical model with a pre-existing micro-crack network using the PFC platform. The results indicate that the uniaxial compressive strength, failure mode, and crack propagation of the specimens demonstrate pronounced size dependence: peak strength decreases with increasing specimen size, and the failure mode transitions from splitting to shearing. In a homogeneous mineral matrix model (without pre-existing micro-cracks), the strength is nearly independent of specimen size, suggesting that pre-existing micro-cracks are the primary factor controlling the size effect. Furthermore, crack length has a significantly greater impact on strength degradation than crack number, with smaller specimens being more sensitive to variations in crack parameters. The established model effectively reproduces the experimental results regarding stress-strain behavior, AE event sequences, AF-RA crack classification, and failure patterns, thereby validating the reliability of the multi-scale numerical approach. These findings provide theoretical support for addressing the strength size effect and enhancing the safety design of engineering rock masses under complex geological conditions.

The mechanical interaction between glaciers and the underlying bedrock is a primary factor influencing ice avalanche disasters. However, research on the mechanical properties of the ice-rock interface remains limited. To further investigate the key mechanisms involved in the initiation of ice avalanches in high-altitude cold regions and to elucidate the main controlling factors and their underlying principles, this study designed and developed a small high-speed centrifuge device suitable for conducting debonding tests at the ice-rock interface. Systematic tests on the bonding strength of the ice-rock interface were carried out under various conditions. The main findings are as follows: (1) The centrifuge device demonstrates high testing efficiency and low data dispersion, facilitating strength tests of the ice-rock interface under multiple conditions, including tension, pure shear, and compressive shear. (2) The bonding strength of the ice-rock interface is closely related to temperature, rock surface roughness, and rock lithology. Lower temperatures lead to greater bonding strength, exhibiting an overall linear relationship. The bonding strength shows a nonlinear positive correlation with rock surface roughness; however, when roughness exceeds a certain threshold, the formation of interface cavities inhibits further increases in bonding strength. Rock lithology affects bonding strength with ice through factors such as porosity and mineral hydrophilicity. (3) A computational model for the bonding strength of the ice-rock interface was established, clarifying the quantitative relationships among bonding strength, temperature, roughness, and normal pressure. This study provides a novel experimental method for analyzing the mechanical properties of the ice-rock interface, and the results offer a quantitative basis for understanding the mechanisms of disaster and assessing the risks of ice avalanches in high-altitude cold regions.

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.

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.

To elucidate the precursory tilt deformation patterns of tension-fractured hazardous rock masses under gravitational loading, this study conceptualizes the collapse process as subcritical propagation under stress corrosion, utilizing a bending Mode-I fracture model. A time-dependent evolution equation for tilt deformation is derived, and the theoretical characteristics of tilting behavior are examined. Based on the principles of micro-electro-mechanical system (MEMS) gravity accelerometry, a method for monitoring the cumulative tilt angle along the primary tilting direction is established using spatial vector angles. A physical model test simulating the collapse of such rock masses under predominantly gravitational loading is designed and conducted, with the resulting tilt deformation behavior analyzed. Additionally, high-low temperature tests are performed to calibrate MEMS tilt sensor drift, and automated field monitoring is implemented to capture time-series variation patterns of tilt angles during collapse events. Comprehensive analysis indicates that precursory tilt deformation transitions from a constant-rate phase to an accelerating phase. However, due to subcritical crack propagation within a heterogeneous medium, localized step-like fluctuations occur during the constant-rate stage, while trend alterations manifest during acceleration. A power-law relationship is identified between the tilt rate and its acceleration prior to collapse. Based on this relationship, a collapse time prediction equation utilizing the inverse of the tilt rate is proposed, and the predictive efficacy of both linear and nonlinear formulations is evaluated. These findings support the application of tilt-sensing technology in monitoring and early warning systems for rock collapse.

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.

When constructing tunnels in rheological strata, the creep of the surrounding rock increases the load on the supporting structure over time. Additionally, environmental influences may cause creep phenomena in the supporting structure, resulting in a complex interaction mechanism between the tunnel's surrounding rock and support due to the coupling effects of both. This article proposes an analytical method for circular tunnels based on the theory of complex functions and Laplace transform. Unlike previous analytical solutions, the approach presented here incorporates the rheological properties of the surrounding rock, non-hydrostatic stress fields, and the creep characteristics of supporting structures. The Kelvin-Voigt model was employed to simulate the rheological properties of both the surrounding rock and the supporting structures. Displacement and stress solutions were derived from the displacement coordination equation and the stress boundary conditions of the surrounding rock and support structures. The accuracy of the analytical solution was verified through numerical simulations, followed by a parameter analysis. The main conclusions drawn from this study are as follows: (1) For simple mechanical models, the analytical method proposed in this paper is faster, simpler, and retains a degree of accuracy superior to that of numerical simulations; (2) When accounting for the creep characteristics of the supporting structure, the deformation of the surrounding rock is greater compared to existing analytical results, the contact pressure between the surrounding rock and the supporting structure is reduced, and the creep of the supporting structure diminishes its bearing capacity and deformation constraint. A higher creep rate in the supporting structure correlates with a faster rate of deformation in the surrounding rock, a lower creep modulus, and increased deformation of the surrounding rock; (3) In the context of non-hydrostatic stress fields, the coupling effects of creep between the tunnel and the supporting structure can exacerbate tunnel issues such as arch uplift or inward compression of tunnel sidewalls, thereby compromising the safety of the supporting structure. Considering these factors is crucial for the design and construction of tunnels in complex environments; (4) Engineering applications demonstrate that the analytical method proposed in this paper effectively predicts the trends in tunnel surrounding rock deformation and support structure stress, showcasing its potential for practical engineering applications.

Accurately predicting the dynamic evolution of permeability during CO₂ injection into shale reservoirs is crucial for carbon sequestration and enhanced shale gas recovery. However, traditional permeability models often fail to comprehensively describe the full-range evolution of permeability throughout the entire CO₂ injection process in shale—from the low-pressure gaseous state to the supercritical state. To address this limitation, this study develops a shale permeability evolution model based on a dual-elastic system comprising both the matrix and fractures, determined by component permeability weighting. By incorporating key factors such as mechanical degradation of the matrix, secondary adsorption, and strain hysteresis effects, we establish a governing equation for permeability evolution under multi-effect coupling. Utilizing an overlapping dual-elastic medium structure, we perform parallel cross-coupling numerical solutions, achieving an accurate representation of the nonlinear permeability evolution during full-pressure CO₂ injection. Furthermore, a decoupled analysis of influencing effects reveals that the degradation of mechanical parameters of the matrix material due to CO₂ defines the boundary thresholds for permeability fluctuation ranges. The asynchronous response between mechanical strain and adsorption strain significantly amplifies differences across evolutionary stages, leading to clearly distinguishable phase transitions. Additionally, the strain hysteresis effect prolongs the duration of evolution. Gas adsorption and mechanical responses jointly regulate the transition points between evolutionary stages, with the secondary adsorption-induced swelling strain particularly enhancing phase differentiation throughout the evolution process. This study also provides an in-depth analysis of the fundamental framework of fluid-solid coupled permeability modeling and explores the characteristics of different numerical simulation methods. The findings not only deepen the understanding of shale permeability evolution during CO₂ injection but also offer valuable insights for theoretical modeling and numerical simulation of permeability in geological fluid sequestration.