Reliability analysis of multilayered soil slopes system considering
spatial variability of soil properties

JIANG Shui-hua; LI Dian-qing

doi:10.16285/j.rsm.2015.S1.110

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Reliability analysis of multilayered soil slopes system considering spatial variability of soil properties

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- Reliability analysis of multilayered soil slopes system considering spatial variability of soil properties
- Vol. 36, Issue S1, Pages: 629-633(2015)
- 作者机构：
  
  1. 南昌大学建筑工程学院,江西,南昌,330031
  2. 武汉大学水资源与水电工程科学国家重点实验室,湖北,武汉,430072
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2015.S1.110
  CLC： TU443
- Online First：14 June 2018，
  
  Published：2015
- 稿件说明：
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JIANG Shui-hua, LI Dian-qing. Reliability analysis of multilayered soil slopes system considering spatial variability of soil properties[J]. 2015, 36(S1): 629-633.
DOI：

JIANG Shui-hua, LI Dian-qing. Reliability analysis of multilayered soil slopes system considering spatial variability of soil properties[J]. 2015, 36(S1): 629-633. DOI： 10.16285/j.rsm.2015.S1.110.

摘要

多层土坡在岩土工程实际中十分常见，不仅土体参数存在一定的空间变异性，而且土体框架呈现明显的层状分布特征，然而目前对考虑土体参数空间变异性的多层土坡稳定可靠度研究的远远不够。提出了基于多重响应面边坡系统可靠度分析的蒙特卡洛模拟（MCS）方法，给出了计算流程图，系统地研究了考虑土体参数空间变异性的多层土坡系统可靠度问题。结果表明，提出方法能够有效地分析考虑参数空间变异性低失效概率水平的多层土坡系统可靠度问题，并且具有较高的参数敏感性分析计算效率。

Abstract

The multilayered soil slopes are very common in geotechnical practice. Not only there exists inherent spatial variation for soil properties

but also there shows obvious multilayered distribution characteristics within the natural soil profile. However

few attempts have been made to study the reliability of multilayered soil slope stability in spatially variable soils. This paper proposes a Monte-Carlo simulation (MCS) based slope system reliability analysis approach using multiple response surfaces. The flow chart for the proposed approach is presented. The reliability of a multilayered soil slope system considering spatial variability of soil properties is systematically investigated using the proposed approach. The results indicate that the proposed approach properly evaluates the slope system reliability at small probability levels (i.e.

s < 0.001) considering spatial variability of soil properties and achieves high computational efficiency in parametric sensitivity analysis.

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Related Author

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TAN Xiao-hui

LIU Shan-wei

ZHA Fu-sheng

WANG Qiao

JIANG Shui-hua

LI Dian-qing

ZHOU Chuang-bing

Related Institution

School of Resources and Environmental Engineering, Hefei University of Technology

Key Laboratory of Rock Mechanics in Hydraulic Structural Engineering, Ministry of Education, Wuhan University

Department of Civil and Environmental Engineering, the Hong Kong University of Science and Technology

Research Center of Geotechnical and Structural Engineering, Shandong University

Institute of Geotechnical and Underground Engineering, Huazhong University of Science and Technology

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