Back to Search Start Over

Failure mechanism and deformation prediction of soft rock tunnels based on a combined finite–discrete element numerical method.

Authors :
Deng, Penghai
Liu, Quansheng
Liu, Bin
Lu, Haifeng
Source :
Computers & Geotechnics. Sep2023, Vol. 161, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The large deformation mechanisms and predictions of soft rock tunnels have always been important but difficult to solve problems in the field of geotechnical engineering. A combined finite–discrete element numerical simulation method (FDEM) was used to study large deformation mechanism, classification and prediction. The deformations or failure mechanisms of tunnel surrounding rock were revealed, and the failure modes and displacement value prediction of surrounding rock with different strength-stress ratios were also investigated. The following conclusions were obtained: (1) Critical hysteresis damping can be adopted to simulate the progressive large deformation process of soft rock tunnels, which can obtain the final deformation of unsupported tunnels and avoid a dynamic response. (2) Under concentrated tangential stress, the surrounding rock undergoes X-shaped conjugate shear fracture, and this type of fracture network continues to propagate toward the depth of the surrounding rock until the model reaches a stable state; the reduction in tunnel cross-section is mainly caused by the macroscopic movement and volume expansion of rock fragments, and the latter is due to the generation of a large number of macroscopic voids. (3) As the strength-stress ratio decreases, the deformation or failure modes of the surrounding rock can be divided into four categories: elastic–plastic deformation, closed fracturing, shear dilation and broken expansion. (4) Finally, a prediction equation for isotropic and homogeneous soft rock unsupported tunnel deformation with general size driven by hydrostatic in situ stress is obtained, which indicates that with an increasing strength-stress ratio, the surrounding rock displacement decreases as an exponential function, with a correlation coefficient of R 2 = 0.997. In addition, the robustness and reliability of the prediction equation is verified. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0266352X
Volume :
161
Database :
Academic Search Index
Journal :
Computers & Geotechnics
Publication Type :
Academic Journal
Accession number :
164867566
Full Text :
https://doi.org/10.1016/j.compgeo.2023.105622