The stability state of tunnel face is the basis of excavation and support, but it is difficult to detect owing to its large buried depth. At present, the existing localizing algorithms of instability zone usually gave range rather than a certain value due to numerious parameters extracting from tests, while the algorithms of limit support pressure (LSP) contain large error owing to involving complex nonlinear polynomial solution and simplification. In this paper, we proposed a parabolic-arch topology model and differential-element mechanical model for all disturbed zones. Through designing suitable arch geometry contour, each disturbed zone is accurately positioned based on Terzaghi theory, and lateral stress ratio is derived from Mohr stress circle, while LSP is calculated through limit equilibrium principle. In practice, in order to copy with the calculation deviation stemming from humid and miscellaneous soil, we design a neural network(NN), and based on the reversed effect of two uncertain parameter in LSP algorithm, we improve its back propagation(BP) algorithm, reducing adjusting counts. Finally, the rationality and effectiveness are evaluated.


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    Titel :

    Recognition and Prediction of Safety Pattern for Tunnel Face of Shield Tunneling


    Beteiligte:
    Zhang, Jinyu (Autor:in) / Zhang, Yijie (Autor:in) / Shen, Mengru (Autor:in) / Zhang, Dingli (Autor:in)


    Erscheinungsdatum :

    2024-06-01


    Format / Umfang :

    9988059 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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