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    Simulation-Based Analysis of Tunnel Boring Machine Performance in Tunneling Excavation

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    Date
    2016
    Author
    Limao Zhang
    Xianguo Wu
    Miroslaw J. Skibniewski
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    Abstract
    This paper develops a hybrid simulation approach that integrates a dynamic default tree (DFT) and discrete-time Bayesian network (DTBN) to support tunnel boring machine (TBM) performance prediction and diagnosis. A causal network model consisting of 20 nodes is built to simulate shield cutter head failure over time during the TBM operation. A total of three indicators, namely,
    URI
    http://yetl.yabesh.ir/yetl/handle/yetl/81974
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