Artificial ground freezing technology is the most important construction method of complex water-bearing soft clay rock. The thermodynamic properties of soft clay rock are important evidence for the design and construction of space resources development, and the variable hydrothermal parameter can directly affect the uncertain thermodynamic properties of soft clay rock. In this work, an array of field experiments on the soft clay rock are carried out, and the anisotropic spatial variations of hydrothermal parameters of soft clay rock are obtained. The statistical variability characteristics of variable hydrothermal parameters are estimated. A stochastic coupling model of soft clay rock with heat conduction and porous flow is proposed, and the uncertain thermodynamic properties of soft clay rock are computed by the self-compiled program. Model validation with the experimental and numerical temperatures is also presented. According to the relationship between anisotropic spatial variations and statistical variability characteristics for the different random field correlation models, the effects of the autocorrelation function, coefficient of variation, and autocorrelation distance of variable hydrothermal parameters on the uncertain thermodynamic properties of soft clay rock are analyzed. The results show that the proposed stochastic analysis model for the thermal characteristics of soft clay rock, considering the spatial variability of frozen soil layers, is scientifically reasonable. The maximum standard deviation of average thickness is 2.33 m, and the maximum average temperature is 2.25 degrees C. For the autocorrelation function, the most significant impact comes from DBIN. For the coefficient of variation, the most significant impact comes from thermal conductivity. Different variations of hydrothermal parameters have different effects on the standard deviation of soft clay rock temperature. The biggest influence is the thermal conductivity, while the lowest influence is the specific heat capacity.

This study investigates the influence of many factors, specifically the strength parameters of geotechnical materials, on the run-out distance of flow-like landslides. Due to the limitations of field tests and laboratory experiments, strength parameters of soils usually exhibit significant spatial variability with different scales of fluctuation (SOF) in different directions, which is the anisotropy of SOF. Aiming at the influence mechanism of anisotropic SOF of the cohesion random field on the run-out distance of flow-like landslides, this study introduced the mid-point method based on the Cholesky decomposition to generate the anisotropic random field. The smoothed particle hydrodynamics (SPH) analysis method, combined with the Mohr-Coulomb failure criterion and the non-Newtonian fluid model, was used to simulate the sliding process and run-out distance of landslides. A stochastic analysis method for the flow-like landslide motion process was established within Monte Carlo simulation framework. Then, by simulating the Yangbaodi landslide and the horizontal strata model, the applicability of the SPH method and the random field discretization method was validated. Finally, a conceptual landslide case was constructed based on the topographic data of the Wangjiayan landslide that was triggered by the Wenchuan earthquake. The study discussed the movement process under the anisotropic SOF in the random field of cohesion and analyzed the probability distribution characteristics of run-out distances. The results show that an increase in the vertical fluctuation range results in a wider range of variation in run-out distance, and the sliding distances exhibit a discrete nature; on the premise that the cohesion parameter conforms to the lognormal distribution, the distribution of the run-out distance also conforms to the same lognormal distribution, which proves that the run-out distance distribution of flow-like landslides is closely related to the distribution characteristics of inputted parameters.