Effects of spatial autocorrelation structure for friction angle on the runout distance in heterogeneous sand collapse

This paper proposes a stochastic method for analyzing the runout distance of sand collapse considering the spatial variability of shear strength, in which random field theory and generalized interpolation material point method are integrated into a Monte-Carlo simulation basis. The random field is generated by Cholesky matrix decomposition method and implemented into the material point level, hence heterogeneity and large deformations are simultaneously considered in the modeling process. A sand collapse case is simulated with both homogeneous and heterogeneous condition assumptions by the proposed method. The effect of five theoretical autocorrelation functions (ACFs) on the runout distance of the collapse is highlighted since the ACFs are commonly adopted to characterize the spatial variability of soil properties due to sparse site observation data. It is shown that the deterministic analysis may underestimate the runout distance, while the heterogeneous model provides realistic results. Moreover, five ACFs and different coefficients of variation of friction angle (COV phi) are compared to investigate their influences on the runout distance modeling. The results show that the uncertainty of runout distance increases with the increase in COV phi. Meanwhile, the variances of the runout distance also become larger with COV phi increasing. Based on the proportion of the runout distance which exceeds the deterministic value, the results indicate that the deterministic analysis notably underestimates the risk induced by large runout distances in real heterogeneous granular flows (e.g., landslide, debris-avalanches).

Automated summary

This paper proposes a stochastic method for analyzing the runout distance of sand collapse considering the spatial variability of shear strength. The method integrates random field theory and generalized interpolation material point method, and uses a Monte-Carlo simulation basis. The results show that deterministic analysis may underestimate the runout distance, while a heterogeneous model provides more realistic results. The uncertainty of the runout distance increases with the increase in the coefficient of variation of friction angle.