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Large deformation analysis of slope failure using material point method with cross-correlated random fields
Large deformation analysis of slope failure is important for hazard and risk assessment of infrastructure. Recent studies have revealed that spatial variability of soil properties can significantly affect the probability of slope failure. However, due to limitations of traditional numerical tools, t...
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Published in: | Journal of Zhejiang University. A. Science 2021-11, Vol.22 (11), p.856-869 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Large deformation analysis of slope failure is important for hazard and risk assessment of infrastructure. Recent studies have revealed that spatial variability of soil properties can significantly affect the probability of slope failure. However, due to limitations of traditional numerical tools, the influence of spatial variability of soil properties on the post-failure behavior of slopes has not been fully understood. Therefore, in this study, we aimed to investigate the effects of the cross-correlation between cohesion and the friction angle on the probability of slope failure and post-failure behavior (e.g. run-out distance, influence distance, and influence zone) using a random material point method (RMPM). The study showed that mesh size, strength reduction shape factor parameter, and residual strength all play critical roles in the calculated post-failure behavior of a slope. Based on stochastic Monte Carlo simulation, the effects of cross-correlation between cohesion and the friction angle on the probability of slope failure, and its run-out distance, influence distance, influence zone, and sliding volume were studied. The study also showed that material point method (MPM) has great advantages compared with the finite element method (FEM) in handling large deformations. |
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ISSN: | 1673-565X 1862-1775 |
DOI: | 10.1631/jzus.A2100196 |