•  
  •  
 

Rock and Soil Mechanics

Abstract

The strength parameters of geotechnical bodies in strata formed under natural conditions often exhibit spatial variability. Predicting the run-out distance of potential large-scale landslides using limited strength data is challenging as it may not comprehensively reflect the range of changes in sliding distance. Therefore, it is necessary to conduct stochastic analyses of landslide sliding distance by combining statistical characteristics and distribution laws of strength parameters, providing a reference for the prevention and control of landslide disasters. This study presents a smoothed particle hydrodynamics (SPH) method for modeling the large-deformation sliding process of landslides, based on the Bingham model, equivalent viscosity, and Mohr-Coulomb failure criterion. The mid-point method is used to generate random field samples of the internal friction angle. Monte Carlo simulations were conducted for stochastic analysis of the sliding distance, thereby obtaining the distribution characteristics of the run-out distance for large-scale landslides. The Yangbaodi landslide was chosen as a study case to verify the feasibility of the SPH method. The accuracy of the discretization of the internal friction angle random field was verified by establishing and analyzing geological models with different random field parameters, and the simulation parameters were calibrated. On this basis, the range and distribution pattern of landslide sliding distance under different conditions were analyzed by varying the coefficient of variation of the internal friction angle, as well as the vertical and horizontal scales of fluctuation. The results show that an increase in the coefficient of variation leads to an increase in the range of the landslide distance, with the sliding distance showing stronger discreteness; an increase in the vertical fluctuation range increases the size of the strength parameter distribution clusters, which in turn increases the range of the landslide distance; both the horizontal and vertical fluctuation ranges, as well as the coefficient of variation, show a positive correlation with the standard deviation of the sliding distance, with the horizontal fluctuation range having the least impact.

Download

Share

COinS