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Probabilistic Analysis of Tunnel Liner Performance Using Random Field Theory

Auteur(s):




Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2019
Page(s): 1-18
DOI: 10.1155/2019/1348767
Abstrait:

Tunnel liner is conventionally designed according to the deterministic design methods. However, the loads transmitted from the surrounding ground to the liner are very uncertain. In other words, the tunnel liner is subjected to nonuniform loading conditions which may affect its performance. This is mainly due to the inherent randomness and spatial variability of ground properties. In addition, since borehole drillings are usually carried out before tunnel excavation, the measured borehole data should be considered and reflected in the tunnel liner design practice, especially when it comes to the reliability-based design using the conditional random field theory. This paper presents an investigation of the tunnel liner performance from the perspective of probabilistic analysis and reliability-based design, and a probabilistic procedure for evaluating the tunnel liner performance is fully described. The random behavior of ground properties is accounted for by the conditional random field theory, and the performance of tunnel liner is examined via finite-difference modeling in FLAC 3D. The evaluation procedure is performed within the Monte Carlo simulation framework. An illustrative hypothesized tunnel is introduced to demonstrate the application of the probabilistic evaluation procedure, and the effects of site characterization parameters and conditioning on the tunnel liner performance are also inspected in a series of parametric studies. Before reaching conclusions, the reliability-based design of a real tunnel is performed with respect to the liner strengths and thickness, given target reliability levels, which provides some insights into a more reasonable and economical design of tunnel liner.

Copyright: © Xin Yu et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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    sur cette fiche
  • Reference-ID
    10365043
  • Publié(e) le:
    24.08.2019
  • Modifié(e) le:
    06.10.2019