Probabilistic Analysis of a Three-Dimensional Slope Based on Limit Analysis

被引:0
|
作者
Yuan, Ran [1 ]
Jia, Zheng-peng [1 ]
Sun, Jin-biao [2 ]
Ou, Jia-long [2 ]
Wang, Wen-fa [3 ]
He, Yi [2 ]
Jiang, Jian-hong [4 ]
机构
[1] Southwest Jiaotong Univ, Sch Civil Engn, Chengdu 610031, Peoples R China
[2] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China
[3] Jianghe Engn Inspect & Testing Co Ltd, 6 Shuiko Rd, Zhengzhou 450003, Henan, Peoples R China
[4] Shandong Prov Commun Planning & Design Inst Grp Co, 576 Wuyingshan West Rd, Jinan 250101, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Slope reliability; Parameter variability; Upper bound method; Stochastic response surface; Back analysis of parameters; STABILITY ANALYSIS; RELIABILITY-ANALYSIS; SPATIAL VARIABILITY; SEISMIC SLOPES; BACK ANALYSIS; ALGORITHM; 1ST-ORDER;
D O I
10.1061/NHREFO.NHENG-2093
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In traditional stability analyses of three-dimensional slopes, soil has often been treated as a homogeneous material with single-parameter properties, overlooking the variability inherent in the strength parameters and unit weight of natural soil. This oversight can lead to an overestimation of slope stability and reliability. To address this issue, this manuscript introduces a novel approach. Initially, a horn-shaped double logarithmic spiral failure mechanism for three-dimensional slopes is constructed based on the kinematic approach within the framework of limit analysis theory. The critical height of the three-dimensional slope is calculated using the mean values of soil properties. Subsequently, the stochastic response surface method is employed to formulate a limit state equation for three-dimensional slopes, with three different algorithms utilized to analyze failure probability. Two cases are employed to validate the proposed method and to assess the efficiency and accuracy of the algorithms. Further, a back analysis of the probabilistic distribution of strength parameters for three-dimensional slopes is performed using the stochastic response surface limit state equation. The findings reveal that the relative width of the three-dimensional slope, the coefficient of variation (COV) of strength parameters, and unit weight significantly affect slope reliability. An increase in relative width leads to higher failure probability, while larger COV values for strength parameters and unit weight correspond to higher failure probability. Through back analysis, the results considering parameter variability align more closely with strength parameters obtained from in situ experiments.
引用
收藏
页数:11
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