Three-dimensional slope reliability and risk assessment using auxiliary random finite element method

被引:112
|
作者
Xiao, Te [1 ]
Li, Dian-Qing [1 ]
Cao, Zi-Jun [1 ]
Au, Siu-Kui [2 ]
Phoon, Kok-Kwang [3 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, 8 Donghu South Rd, Wuhan 430072, Peoples R China
[2] Univ Liverpool, Inst Risk & Uncertainty, Harrison Hughes Bldg,Brownlow Hill, Liverpool L69 3GH, Merseyside, England
[3] Natl Univ Singapore, Dept Civil & Environm Engn, Blk E1A,07-03,1 Engn Dr 2, Singapore 117576, Singapore
基金
中国国家自然科学基金;
关键词
Slope stability; Reliability analysis; Risk assessment; Spatial variability; Random finite element method; Response conditioning method; RESPONSE-SURFACE METHOD; STABILITY ANALYSIS; SPATIAL VARIABILITY; SHEAR-STRENGTH; FAILURE; HETEROGENEITY; SIMULATION; EFFICIENT; SELECTION; IMPACT;
D O I
10.1016/j.compgeo.2016.05.024
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper aims to propose an auxiliary random finite element method (ARFEM) for efficient three-dimensional (3-D) slope reliability analysis and risk assessment considering spatial variability of soil properties. The ARFEM mainly consists of two steps: (1) preliminary analysis using a relatively coarse finite-element model and Subset Simulation, and (2) target analysis using a detailed finite-element model and response conditioning method. The 3-D spatial variability of soil properties is explicitly modeled using the expansion optimal linear estimation approach. A 3-D soil slope example is presented to demonstrate the validity of ARFEM. Finally, a sensitivity study is carried out to explore the effect of horizontal spatial variability. The results indicate that the proposed ARFEM not only provides reasonably accurate estimates of slope failure probability and risk, but also significantly reduces the computational effort at small probability levels. 3-D slope probabilistic analysis (including both 3-D slope stability analysis and 3-D spatial variability modeling) can reflect slope failure mechanism more realistically in terms of the shape, location and length of slip surface. Horizontal spatial variability can significantly influence the failure mode, reliability and risk of 3-D slopes, especially for long slopes with relatively strong horizontal spatial variability. These effects can be properly incorporated into 3-D slope reliability analysis and risk assessment using ARFEM. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:146 / 158
页数:13
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