Fast Estimation for Reliability Index of Soil Subgrade Slopes Based on Safety Factor

被引:0
|
作者
Wang Q. [1 ,2 ]
Luo Q. [1 ,2 ]
Zhang W. [1 ,3 ]
Jiang L. [1 ,2 ]
机构
[1] School of Civil Eng., Southwest Jiaotong Univ., Chengdu
[2] MOE Key Lab. of High-Speed Railway Eng., Chengdu
[3] School of Civil and Environmental Eng., Harbin Inst. of Technol., Shenzhen
来源
Gongcheng Kexue Yu Jishu/Advanced Engineering Sciences | 2023年 / 55卷 / 03期
关键词
coefficient of variation; estimation bias; reliability index; safety factor; subgrade slope;
D O I
10.15961/j.jsuese.202101145
中图分类号
学科分类号
摘要
Due to the complexity of reliability analysis of subgrade slopes, establishing a fast estimation method of reliability index β is of great help for the promotion of probability theory in engineering practice. Using the Fellenius limit equilibrium method and Monte Carlo simulation, the reliability analysis of simple soil slopes with typical slope gradients was carried out, and the change laws of β with slope height h and the coefficient of variation of strength parameters, i.e., δc and δφ, were investigated. Using dimensionless and multiple nonlinear regression techniques, a β estimation function based on safety factor Fs and mean strength parameters, i.e., c and φ, was developed. The relationships between regression coefficients and slope height as well as the coefficient of variation were analyzed, and subsequently, the impact of Fs, c, and φ on the estimation bias of β was explored. The results indicate that: 1) β displays a negative power-law increasing trend with increasing Fs. The limit value of β satisfies βud=aud(1−Fs−bud), in which aud and bud are mainly affected by the variation level of strength parameters, indicating negative exponential power and negative linear laws respectively; 2) By nondimensionalizing the internal friction angle and cohesion, the β estimation model consisting of power and logarithm functions can well consider the influence of slope height, strength variability, and safety factor on β. 3) The estimation bias Δβ is affected by the variation level of strength parameters more than slope height. When φ≤18.52+1.5 c–0.17 c2, the estimation bias of β is slightly large, i.e., Δβ≥0.5, and accordingly Fs ≤1.377 for this case. The proposed method can assist engineers to assess the reliability of soil subgrade slopes rapidly and accurately. © 2023 Editorial Department of Journal of Sichuan University. All rights reserved.
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页码:121 / 129
页数:8
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