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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/99768


    Title: Probabilistic back analysis of slope failure - A case study in Taiwan
    Authors: 黃俊鴻;Wang, Lei;Hwang, Jin Hung;Luo, Zhe;Juang, C. Hsein;Xiao, Junhua
    Contributors: 工學院土木工程學系
    Keywords: Anchors;Back analysis;Case study;Computer simulation;Dip slope;Failure;Geotechnics;Inverse;Markov Chain Monte Carlo;Maximum likelihood method;Probabilistic methods;Probability theory;Slope failure;Strength;Uncertainty
    Date: 2013-06-01
    Issue Date: 2026-04-21 13:35:03 (UTC+8)
    Publisher: Elsevier BV;Elsevier Ltd
    Abstract: 摘要: In this paper, the authors present a probabilistic back-analysis of a recent slope failure at a site on Freeway No. 3 in northern Taiwan. Post-event investigations of this failure found uncertain strength parameters and deteriorating anchor systems as the most likely causes for failure. Field measurement after the event indicated an average slip surface of inclination 15°. To account for the uncertainties in input parameters, the probabilistic back analysis approach was adopted. First, the Markov Chain Monte Carlo (MCMC) simulation was used to back-calculate the geotechnical strength parameters and the anchor force. These inverse analysis results, which agreed closely with the findings of the post-event investigations, were then used to validate the maximum likelihood (ML) method, a computationally more efficient back-analysis approach. The improved knowledge of the geotechnical strength parameters and the anchor force gained through the probabilistic inverse analysis better elucidated the slope failure mechanism, which provides a basis for a more rational selection of remedial measures.
    出版者: Elsevier Ltd
    出版日期: 2013-06
    出處: Computers and Geotechnics, 2013-06, Vol.51, p.12-23
    資源來源: Elsevier ScienceDirect Journals
    版權: 2013 Elsevier Ltd
    識別號: ISSN: 0266-352X
    識別號: EISSN: 1873-7633
    識別號: DOI: 10.1016/j.compgeo.2013.01.008
    Appears in Collections:[Department of Civil Engineering] journal & Dissertation

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