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    Tunnel Probabilistic Structural Analysis Using the FORM

    241296_241296.pdf (1.500Mb)
    Access Status
    Open access
    Authors
    Sharifzadeh, Mostafa
    Mirzaeian, Y.
    Shahriar, K.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Sharifzadeh, M. and Mirzaeian, Y. and Shahriar, K. 2015. Tunnel Probabilistic Structural Analysis Using the FORM. Journal of Geological Research. 2015: pp. 1-9.
    Source Title
    Journal of Geological Research
    DOI
    10.1155/2015/394761
    ISSN
    1687-8833
    School
    Dept of Mining Eng & Metallurgical Eng
    Remarks

    This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by/3.0/

    URI
    http://hdl.handle.net/20.500.11937/6457
    Collection
    • Curtin Research Publications
    Abstract

    In this paper tunnel probabilistic structural analysis (TuPSA) was performed using the first order reliability method (FORM). In TuPSA, a tunnel performance function is defined according to the boundary between the structural stability and instability. Then the performance function is transformed from original space into the standard normal variable space to obtain the design point, reliability index, and also the probability of tunnel failure. In this method, it is possible to consider the design factors as the dependent or independent random parameters with arbitrary probability distributions. A software code is developed to perform the tunnel probabilistic structural analysis (TuPSA) using the FORM. For validation and verification of TuPSA, a typical tunnel example with random joints orientations as well as mechanical properties has been studied. The results of TuPSA were compared with those obtained from Monte-Carlo simulation. The results show, in spite of deterministic analysis which indicates that the rock blocks are stable, that TuPSA resulted in key-blocks failure with certain probabilities. Comparison between probabilistic and deterministic analyses results indicates that probabilistic results, including the design point and probability of failure, are more rational than deterministic factor of safety.

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