Probabilistic Analysis of Large Slope Deformation Considering Soil Spatial Variability with Rotated Anisotropy

被引:2
作者
Liu L. [1 ,2 ,3 ]
Liang C. [1 ,2 ,3 ]
Xu M. [1 ,2 ,3 ]
Zhu W. [1 ,2 ,3 ]
Zhang S. [1 ,2 ,3 ]
Ding X. [4 ]
机构
[1] Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha
[2] Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Changsha
[3] School of Geosciences and Info‐Physics, Central South University, Changsha
[4] School of Civil Engineering, Hunan City University, Yiyang
来源
Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences | 2023年 / 48卷 / 05期
关键词
engineering geology; large slope deformation; material point method; multiple response surface; random field; rotated anisotropy; spatial variability;
D O I
10.3799/dqkx.2022.372
中图分类号
学科分类号
摘要
To explore the influence of spatial variability of soil parameters with rotated anisotropy on probabilistic large slope deformation characteristics, a multiple response surface-based random material point method is proposed in this study. First, random field theory is employed to simulate the spatial variability of soil parameters with rotated anisotropy. Then, the multiple response surface method is used to evaluate the factor of safety (FS) of each random field sample, based on which the FSs for all random field samples are sorted efficiently in an ascending order. Finally, the random material point method is used to sequentially simulate the large deformation features of a slope for the failed samples with the FS at less than 1. An undrained clay slope is taken as the illustrative example, where the undrained shear strength of the soil is simulated as a rotated anisotropic random field. The effect of the rotational angle β and the autocorrelation length θ2 in the minor principal direction of the rotated anisotropic random field on the large deformation features and failure modes of the slope are systematically studied. The results show that the proposed method can be efficiently conducted for probabilistic analysis of large slope deformation. Both β and θ2 have significant effects on large slope deformation features and failure modes. In terms of large deformation features, the mean and standard deviation of the influence distance, sliding distance, and sliding volume increase with the increase of θ2. There might be four failure modes when considering the rotated anisotropic spatial variability of the undrained strength of the slope, among which the deep sliding mechanism and progressive failure are the two main probabilistic failure modes. Therefore, the proposed method provides an effective way for the probabilistic large slope deformation analysis as well as a good theoretical reference for an accurate risk assessment of slope stability. © 2023 China University of Geosciences. All rights reserved.
引用
收藏
页码:1836 / 1852
页数:16
相关论文
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