PREDICTION OF GROUND SUBSIDENCE BY MODELING TUNNEL BORING MACHINE TECHNOLOGY

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Armen Ter-Martirosyan
Ilya Isaev
Evgenii Kriuchkov
Maksim Shlapak

Abstract

Tunneling using tunnel boring machines (TBMs) induces ground settlement, leading to deformations in buildings and structures located within the zone of influence of the planned construction. Settlement prediction based on volume loss is one of the established practices in Russia; however, this method relies on construction experience and does not directly account for the primary technological parameters affecting soil settlement. In some cases, to obtain accurate deformation predictions using this method, it is necessary to perform a back-calculation of volume loss, considering the tunnel section already excavated. This study examines the modeling of all technological factors involved in TBM tunneling for forecasting settlement resulting from metro tunnel construction. A division of the TBM excavation process into sequential phases is introduced for finite element analysis. Two calculation schemes were formulated for different sections of the Rublyovo–Arkhangelskaya line of the Moscow Metro, in two variants: (1) using volume loss, and (2) accounting for all technological factors. In the latter variant, parameters such as shield face pressure, grout injection pressure, TBM weight, structural stiffness of the TBM, shield tail gap, and others were incorporated. Displacement plots for adjacent buildings were generated from the resulting calculations and compared with measured displacements. A comparative analysis between the volume loss method and the alternative comprehensive technological-factor method was conducted. The comprehensive method demonstrated a high degree of quantitative and qualitative agreement with measured values and allows assessment of the soil’s mechanical behavior over time during TBM excavation.

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Ter-Martirosyan, A., Isaev, I., Kriuchkov, E., & Shlapak, M. (2025). PREDICTION OF GROUND SUBSIDENCE BY MODELING TUNNEL BORING MACHINE TECHNOLOGY. International Journal for Computational Civil and Structural Engineering, 21(4), 114-129. https://doi.org/10.22337/2587-9618-2025-21-4-114-129

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