Model test on the effects of shield machine cutterhead vibration on tunnel face stability in sandy ground

Abstract

Face stability is one of the essential problems in shield tunneling. When tunneling in cobble stratum or mixed face ground conditions, significant cutting-induced cutterhead vibration would occur and affect the face stability. To reveal the mechanism and effect of vibration on the tunnel face stability, a transparent tunnel model with a movable vibration exciter was designed and a series of model tests were performed under different vibration magnitudes A_a and frequencies f. Meanwhile, particle image velocimetry was used to reveal the displacement field and the failure pattern of the tunnel face. The test results indicate that the cutting-induced vibration produces a significant reduction effect on the tunnel face stability, as expressed by the increase of the face support pressure and the failure zone when the vibration magnitude and frequency increase. Compared with the static unloading conditions, the width of the failure wedge L_wt increased by about 5.75% and 35.66% for the loose and dense sand, respectively, under dynamic unloading conditions (A_a = 0.2g, f = 10 Hz). The limit support pressure increased up to about 0.20γD at a vibration of 0.3g and 50 Hz, much larger than those of static conditions, which were about 0.08γD-0.09γD. An observable self-stabilizing arch can be formed in dense sand under static unloading conditions, while under dynamic unloading conditions, the long-time stable soil arch would not occur. The contributions of this paper could provide an insightful understanding of the effects of cutterhead vibration on tunnel face stability.

Keywords

Shield tunnelling / Face stability / Cutting-induced vibration / Limit support pressure

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Meng-Bo Liu: Conceptualization, Formal analysis, Funding acquisition, Methodology, Validation, Writing - original draft. Jun-Hua Xiao: Conceptualization, Supervision, Writing - review & editing. Shao-Ming Liao: Conceptualization, Formal analysis, Methodology, Validation, Writing - review & editing. Zhi-Yong Liu: Investigation, Visualization, Writing - review & editing. Jun-Zuo He: Formal analysis, Methodology, Visualization, Writing - original draft. Yan-Qing Men: Conceptualization, Investigation, Visualization, Writing - review & editing. Jia-Cheng Sun: Data curation, Validation, Visualization, Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The present work is funded by the National Key R&D Program of China (Grant No. 2022YFB2602200), National Natural Science Foundation of China (Grant No. 52308412), China Postdoctoral Science Foundation (Grant No. 2023M732668), and Shanghai Postdoctoral Excellence Program (2022553).

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