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.

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.

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.

In-situ permeability evaluation of rock masses at the engineering scale is crucial for deep energy extraction and subsurface energy material sequestration, including CO₂, hydrogen, and nuclear waste storage. Compared to laboratory-scale tests, this approach more accurately reflects the seepage behavior of rocks under their original in-situ conditions. This study proposes a theoretical method for calculating the in-situ gas permeability of rock masses at the engineering scale, systematically analyzing key parameters that influence permeability results. Special emphasis is placed on determining and conducting sensitivity analyses of the effective testing radius. Through simulated engineering-scale permeability tests under in-situ conditions and comparative analysis with core-scale results, it is observed that permeability values differ by no more than a factor of three. This discrepancy is primarily attributed to the confining pressure of 0.8 MPa applied during core-scale tests and the presence of interconnected pores and microcracks induced by local air bubbles during the casting process. Based on these findings, a series of pilot field tests were conducted in a deep underground laboratory and in both coal and sandstone roadways of a coal mine in Shandong Province, utilizing a self-developed portable in-situ gas permeability testing system. The results demonstrate that the proposed method and integrated system exhibit strong adaptability, stability, and repeatability across diverse engineering scenarios, thereby facilitating effective evaluation of rock mass permeability and grouting effectiveness. This research offers a novel technical pathway and theoretical foundation for the in-situ assessment of reservoir exploitability and the sealing performance of barrier systems in deep subsurface energy material sequestration projects.

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.

In response to the engineering challenges associated with limited construction scale and slow development speed in high-impurity salt mines oil storage, this study proposes a novel technical approach that utilizes sediment voids to expand oil storage capacity. Laboratory experiments and theoretical analyses were conducted on sediment particles from the Yunying salt mine in Hubei Province. A evaluation system encompassing sediment characterization and sediment void storage capacity was established. The mechanism of oil injection and production under the fluid-solid coupling of oil/brine and sediment was systematically studied. The sediment void clogging risk during oil injection and production was explored. The migration rule of oil and brine in sediment voids were elucidated. The results indicate that Yunying sediments possess a void ratio exceeding 40% with favourable connectivity in total, meeting the requirements for oil storage. Multiple oil injection and production cycles demonstrate low flow resistance and a linear mass-time correlation. Dominant flow channels are established only during the initial injection, stabilizing thereafter. The oil-brine interface exhibits fingering phenomena without abnormal pressure or rate fluctuations. Transient clogging events occur randomly, presenting an overall low risk. The oil injection pressure increases stepwise as the oil-brine interface descends. The hydrophilic properties of the sediments improve brine injection and oil production efficiency through capillary forces. These findings provide scientific support for the construction of high-impurity salt mines oil storage facilities.

On 15 August 1950, an M_s8.6 earthquake struck the Medog—Zayu region in the Eastern Himalayan syntaxis, with a maximum intensity of XII and an area with intensity≥VIII of about 2.19×10⁵ km². This mainshock-dominated event released seismic energy in a highly concentrated manner and triggered extensive landslides and related geological hazards. To systematically reveal the spatial distribution and the river-blocking patterns of coseismic landslides, we integrate multi-temporal historical imagery since 1961, archival records and field investigations to analyse the intensity distribution. For the high-intensity zone (X–XII) from Milin Wolong to downstream of Duden in the Namcha Barwa region, a coseismic landslide inventory is constructed for the first time, resulting in a dataset of 920 landslides. Quantitative analysis reveals that landslides predominantly occurred at 2 000–4 000 m elevation, on 20°–50° slopes, and within 4 km of active faults. The landslide distribution is strongly controlled by the main central thrust fault, the Motuo fault, and the Apalong fault. Based on statistical analysis and morphological characteristics, we delineate four types of earthquake-induced landslide-damming patterns: seated landslides, high-altitude remote hazards, whole gully-scale landslides and multi-landslide clusters, typified by the Gengbangla, Zelongnong Gully, the Jamaqiming Gully, and Zhaqu—Xirang landslide groups, respectively. The maximum duration of river blockage reached 15–16 hours. The unique geomorphic and tectonic environment of the Eastern Himalayan Syntaxis provides favorable conditions for the occurrence and evolution of high-altitude remote geological hazards. As the region is currently in a seismically active phase, it is critical to enhance research on the failure mechanisms and early warning of under extreme earthquake conditions, thereby improving disaster preparedness, resilience, and emergency response capabilities in the region.

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.

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.

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.