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Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using Subset Simulation

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Abstract

Random finite element method (RFEM) provides a rigorous tool to incorporate spatial variability of soil properties into reliability analysis and risk assessment of slope stability. However, it suffers from a common criticism of requiring extensive computational efforts and a lack of efficiency, particularly at small probability levels (e.g., slope failure probability P f  < 0.001). To address this problem, this study integrates RFEM with an advanced Monte Carlo Simulation (MCS) method called “Subset Simulation (SS)” to develop an efficient RFEM (i.e., SS-based RFEM) for reliability analysis and risk assessment of soil slopes. The proposed SS-based RFEM expresses the overall risk of slope failure as a weighed aggregation of slope failure risk at different probability levels and quantifies the relative contributions of slope failure risk at different probability levels to the overall risk of slope failure. Equations are derived for integrating SS with RFEM to evaluate the probability (P f ) and risk (R) of slope failure. These equations are illustrated using a soil slope example. It is shown that the P f and R are evaluated properly using the proposed approach. Compared with the original RFEM with direct MCS, the SS-based RFEM improves, significantly, the computational efficiency of evaluating P f and R. This enhances the applications of RFEM in the reliability analysis and risk assessment of slope stability. With the aid of improved computational efficiency, a sensitivity study is also performed to explore effects of vertical spatial variability of soil properties on R. It is found that the vertical spatial variability affects the slope failure risk significantly.

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Acknowledgments

This work was supported by the National Science Fund for Distinguished Young Scholars (Project No. 51225903), the National Basic Research Program of China (973 Program) (Project No. 2011CB013506), the National Natural Science Foundation of China (Project No. 51329901, 51409196), the Natural Science Foundation of Hubei Province of China (Project No. 2014CFA001), an open fund from State Key Laboratory Hydraulics and Mountain River Engineering, Sichuan University (Project No. SKHL1318), and the Fundamental Research Funds for the Central Universities (Project No. 2042014kf0001). The financial support is gratefully acknowledged.

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Authors and Affiliations

  1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Key Laboratory of Rock Mechanics in Hydraulic Structural Engineering (Ministry of Education), Wuhan University, 8 Donghu South Road, Wuhan, 430072, People’s Republic of China

    Dian-Qing Li, Te Xiao, Zi-Jun Cao & Chuang-Bing Zhou

  2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

    Li-Min Zhang

  3. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, People’s Republic of China

    Zi-Jun Cao

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  1. Dian-Qing Li
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  2. Te Xiao
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  3. Zi-Jun Cao
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  4. Chuang-Bing Zhou
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  5. Li-Min Zhang
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Correspondence to Zi-Jun Cao.

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Li, DQ., Xiao, T., Cao, ZJ. et al. Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using Subset Simulation. Landslides 13, 293–303 (2016). https://doi.org/10.1007/s10346-015-0569-2

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  • DOI: https://doi.org/10.1007/s10346-015-0569-2

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