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A new approach to evaluate the interactions between the surrounding rock microstructure and water inrush for tunnel excavation.

Authors :
Ye, Dayu
Liu, Guannan
Ji, Ming
Wang, Fangtian
Zhou, Jianhua
Source :
Computers & Geotechnics. May2023, Vol. 157, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Risk assessments during tunnel excavation are a constant concern for researchers and practitioners. During excavation in water-rich and karst regions, an assessment of the risk of water inrush mediated by coupled hydrological–mechanical effects is crucial. However, as the major channel for water transport, few published studies have analysed the effects of the fracture microstructure on the risk assessment under the combined effects of in situ stress, matrix deformation and water pressure. Based on fractal theory, this study proposes a highly coupled fractal analysis model for tunnel excavation that is capable of simultaneously and quantitatively investigating the interaction between the distribution and fracture evolution of the surrounding rock, the risk of water inrush, and the tunnel stress. We adopt the maximum fracture length (l max) and fracture fractal dimension (D f) to quantitatively characterize the fracture density and fracture size of the surrounding rock. A comparison with field data and analytical solutions is conducted to verify the correctness. The rock stress, water pressure, deformation and microstructural evolution of rock under different excavation processes of the tunnel have been comprehensively analysed. The contributions of the evolution of various microstructural parameters during tunnel excavation to the risk of water inrush are assessed. This provides a new micro-macro solution for the risk assessment of tunnel water inrush at the engineering scale and provides technical guidance for underground engineering practitioners [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0266352X
Volume :
157
Database :
Academic Search Index
Journal :
Computers & Geotechnics
Publication Type :
Academic Journal
Accession number :
162441508
Full Text :
https://doi.org/10.1016/j.compgeo.2023.105336