Probabilistic analysis of soil-water characteristic curve with Bayesian approach and its application on slope stability under rainfall via a difference equations approach

被引：5

作者：

Luo, Xiaoyan ^{[1
,2
]}

Liu, Weiping ^{[1
]}

Fu, Mingfu ^{[1
]}

Huang, Jinsong ^{[3
]}

机构：

[1] Nanchang Univ, Sch Civil Engn & Architecture, Nanchang, Jiangxi, Peoples R China

[2] Jiangxi Sci & Technol Normal Univ, Sch Civil Engn & Architecture, Nanchang, Jiangxi, Peoples R China

[3] Univ Newcastle, CGSE, Callaghan, NSW, Australia

来源：

JOURNAL OF DIFFERENCE EQUATIONS AND APPLICATIONS | 2017年 / 23卷 / 1-2期

关键词：

Soil-water characteristic curve; uncertainty; Bayesian analysis; Markov Chain Monte Carlo; slope stability; probabilistic analysis; UNSATURATED SOILS; SELECTION;

D O I：

10.1080/10236198.2016.1226291

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The soil-water characteristic curve (SWCC) is an important tool in the interpretation of the properties of unsaturated soil, and is widely applied in Geotechnical and Geo-environmental engineering. The SWCC uses several fitting parameters to express the best fit equations, and the fitting parameters depend on the experimental data. The reliability and predictability of SWCC are always being questioned. In this paper, Fredlund and Xing model is used to fit the experimental data of loamy sand and sandy clay loam in the UNSODA database, the fitting parameters values are discussed. Bayesian framework and the Markov Chain Monte Carlo simulation method are applied to estimate the uncertainty of SWCC from the errors and variance of the fitting parameters, and SWCC of different levels of confidence is obtained. Applications of the confidence on slope stability analysis are presented by a simplified finite element program.

引用

页码：322 / 333

页数：12