A modified parallel model for estimating the thermal conductivity of unsaturated sand was proposed in this study. The heat conduction in the solid phase of sand depends mainly on the form of contacts between solid particles, while water bridges at the particle contacts increase the contact areas and remarkably enlarge the transfer paths of heat conduction in sandy soils. However, the thermal conductivity of the solid particle itself (λ_s) cannot describe the influence of the form of contacts and water bridges on heat conduction through the solid phase. In this study, the equivalent thermal conductivity of the solid particle (λ_es) was presented which reflected the influence of the form of contacts and water bridges between particles under dry conditions or a low degree of saturation, respectively. The relationship between λ_es and degree of saturation was described by hyperbolic expression. The modified model was calibrated using measured values of the thermal conductivity from published datasets, including those for 41 types of sand from 15 studies. Numerical analyses of the temperature field of the energy pile were performed and validated against laboratory measurements. The results illustrated that the modified model was more applicable than the original model for predictions of sand thermal conductivity.

Currently, research on employing finite difference method and discrete element method (FDM-DEM) coupling to assess the stability of tunnel lining structures is limited. This study utilized the FDM-DEM coupling approach, with the F2 fault of the East Tianshan Tunnel as a case study, to develop a numerical model in conjunction with PFC3D 6.0 and FLAC3D 6.0 software. We conducted a comprehensive analysis of the displacement deformation and crack progression of the tunnel lining structure under varying dislocation momentum conditions, unveiling the underlying mechanisms. The findings indicated that as the dislocation increased, the extent of damage to the vault intensified, and the particle contact force within the tunnel lining shifted from compression to tension, significantly contributing to the crack formation. Fault dislocation influenced the gradual expansion of cracks from the vault to the spandrel and arch waist, with the crack width increasing alongside the rising dislocation momentum. In particular, under substantial dislocation momentum, the overall stability of the tunnel lining was markedly diminished. The safety factor at the tunnel section declined progressively as the dislocation momentum escalated, with values of 2.53, 2.49, 2.43, 2.39, and 2.32 corresponding to dislocation momenta of 0.01 m, 0.05 m, 0.1 m, 0.15 m, and 0.2 m, respectively. This research offers valuable insights and a reference framework for investigating the stability of tunnel lining structures in proximity to fault dislocations, pinpointing potential failure points, and bolstering the structural integrity of tunnels.

Based on the mutation theory, the paper studies the stability of loess slope, and discusses the loess slope in Yili region in Xinjiang. From the perspective of mechanics, the paper focuses on the influence of mutation phenomenon on the stability of loess slope, and deeply analyzes the mechanical mechanism in the mutation process. As an effective tool to study the phenomenon of discontinuous change, mutation theory has important applications in the stability analysis of loess slopes. By applying the mutation theory, the mutation characteristics of the loess slope in the Xinjiang Yili area were analyzed. In terms of mechanical mechanism, the stress distribution, deformation characteristics and the instability mode are discussed in detail. Through theoretical analysis and numerical simulation, it is found that when the slope stress reaches a certain critical value, mutation will occur, leading in a sharp decline of slope stability. Specific data show that in a typical loess slope in Yili area, when the stress reaches about 0.6 MPa, the slope changes, and the displacement instantly increases to more than twice the original, indicating that the slope has been in a state of instability. In the case study of loess slope in Yili, Xinjiang, the slope stability is comprehensively evaluated by combining field investigation to monitoring data and indoor test. By identifying and analyzing the mutation characteristics of the slope, it is found that there are widespread subsidence and disintegration problems in this area, which play a key role in the mutation process. The specific data show that the subsidence coefficient of the loess slope in Yili area is generally above 0.05, and the disintegration rate is more than 0.5% per hour. These factors jointly aggravate the mutation risk of the slope. Based on the above data analysis, the paper puts forward targeted disaster prevention and mitigation measures, including strengthening slope drainage, using appropriate reinforcement technology, etc. These measures aim to reduce the risk of mutation and improve the stability of the loess slope.

Heavy rainfall infiltration is a key disaster-inducing factor that triggers the softening of surrounding rock and deformation of support structures in tuff gully tunnels. Based on the gully section of the left line of the Dabao Tunnel of the Leigongshan–Rongjiang Expressway in Guizhou Province, this study systematically reveals the synergistic disaster-inducing mechanism of “topography-seepage-softening” in tuff gully tunnels under heavy rainfall infiltration through laboratory tests and FLAC3D 3D numerical simulations. The main innovative conclusions are as follows: (1) The “phased” attenuation law of tuff mechanical parameters was quantified, and the critical water content for significant strength deterioration was determined to be 2.5%, with a saturated softening coefficient of 0.59. These results provide key data for early warning and evaluation of similar projects. (2) A “convergence-disorder” distribution pattern of pore water pressure controlled by gully topography was revealed. It was found that the rock mass directly below the aqueduct exhibits a disordered zone with downward-extending pore water pressure due to fluid convergence, with the maximum pore water pressure reaching 0.55 MPa. This clarifies the essence that tunnel stability is controlled by the coupling of topography and seepage field. (3) The key sensitive areas for tunnel stability—namely the gully bottom, arch haunches, and the area below the aqueduct—were accurately identified. The significant increase in displacement of these areas after rock stratum softening was quantified (e.g., the displacement at the crown of the secondary lining increased from 3 mm to 4 mm, and the influence range expanded to the arch haunches). This study clarifies the deformation characteristics and instability mechanism of tuff gully tunnels under heavy rainfall from two aspects: the “internal mechanism of rock mass softening” and the “external condition of topographic seepage control.” It can provide a theoretical basis and key technical pathway for disaster prevention and control as well as stability design of similar tunnels.

The cumulative displacement of landslides in alpine regions is jointly affected by rainfall, temperature variation, freeze–thaw cycles, and other factors, and usually exhibits nonlinear, non-stationary, and multi-scale fluctuation characteristics. To improve the accuracy of landslide displacement prediction under complex environmental conditions, this study takes the Taker Tubek Village landslide in Gongliu County, Xinjiang, China, as the study object. Cumulative displacement data from GNSS02 and GNSS03, together with daily rainfall and daily mean temperature, were used to construct a SOO-VMD-CNN-TimeXer hybrid prediction model. First, SOO was employed to adaptively optimize the VMD parameters, and the cumulative displacement series were decomposed into multiple IMF components. Then, CNN was used to extract local fluctuation features, while TimeXer was applied to model long-term temporal dependencies and the effects of exogenous variables. Finally, the predicted results of all components were reconstructed to obtain the cumulative displacement prediction. The results show that the proposed model achieved high prediction accuracy at both GNSS02 and GNSS03. The MSE, MAE, MAPE, and R² values were 0.0158, 0.0960, 0.0112, and 0.9464 for GNSS02, and 0.0483, 0.1590, 0.0203, and 0.9946 for GNSS03, respectively, outperforming LSTM, Informer, iTransformer, Crossformer, and other models. The results indicate that the SOO-VMD-CNN-TimeXer model can effectively characterize the cumulative displacement evolution of landslides in alpine regions and provide technical support for landslide deformation trend forecasting and disaster early warning.