Fengqian Pan

The spatial variability of geotechnical parameters, such as soil shear wave velocity (V_s), exhibits significant nonlinearity and non-stationarity with respect to depth (h) due to the influence of overlying stress. Existing stochastic field models for describing the variability of geotechnical parameters are insufficient for simultaneously capturing both the nonlinearity and non-stationarity of these parameters. In this study, a power function V_s = V_s0[f(h)]ⁿ is proposed to describe the nonlinear trend in soil shear wave velocity (V_s) as a function of depth-related variable f(h). Considering the physical significance and correlation of the power function parameters V_s0 and n, the variability of these parameters is modeled using a random variable model and a stationary stochastic field model, respectively. This leads to the development of a non-stationary stochastic field model that describes the spatial variability of V_s. The proposed method is applied to simulate the random V_s-structure of a seabed site in China, and the obtained V_s results are used to assess the liquefaction probability of the seabed. The results indicate that ignoring the correlation between geotechnical parameters significantly increases the variability of the final simulation results. However, the proposed method accurately captures the nonlinear trend and non-stationary characteristics of soil V_s with depth, and the liquefaction probability predictions are consistent with those derived from in situ V_s measurements in the study area. This approach provides valuable guidance for simulating the spatial variability of depth-dependent geotechnical parameters, particularly those significantly influenced by overlying pressure.

Granite residual soil is widely distributed in Southeast Fujian. Large-scale engineering construction leads to the exposure of residual soil slopes to the natural environment. Affected by seasonal climate factors, the soil of slopes experiences a dry–wet cycle for a long time. The repeated changes in water content seriously affect the shear strength of soil, and then affect the stability of the slope. In order to explore the influence of the dry–wet cycle on the shear strength of granite residual soil in Fujian, an indoor dry–wet cycle simulation test was carried out for shallow granite residual soil on a slope in Fuzhou, and the relationship between water content, dry–wet cycle times, and the shear strength index, including the cohesion and internal friction angle of the granite residual soil, was discussed. The results show that when the number of dry–wet cycles is constant, the cohesion and internal friction angle of the granite residual soil decrease with an increase in water content. The relationship between the cohesion, internal friction angle, and water content can be described using a power function. Meanwhile, the fitting parameters of the power function are also a function of the number of wet and dry cycles. The prediction formulas of the cohesion and internal friction angle considering the number of dry–wet cycles and water content are established, and then the prediction formula of shear strength is obtained. The ratio of the predicted value of shear strength to the test value shall be within ±15%. An error transfer analysis based on the point estimation method shows that the overall uncertainty of the predicted value of shear strength caused by the combined uncertainty of the predicted value of cohesion and the internal friction angle and the single-variable uncertainty of the predicted value of shear strength caused only by the uncertainty of the predicted value of either the cohesion or internal friction angle increases first and then decreases with an increase in the number of dry–wet cycles. All increase with an increasing water content. The maximum standard deviation of the proposed shear strength prediction model of granite residual soil is less than 9%.