Deformation and failure behaviour of straight-wall arched tunnels: effect of minimum principal stress under static stress and low-frequency disturbances

IF 2.2 3区 工程技术 Q2 MECHANICS
Jianing Li, Jianhua Hu, Pengfei Gao, Binglei Li
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引用次数: 0

Abstract

To comprehensively investigate the effect of different minimum principal stresses on the stability of straight-wall arched tunnels, the static stress and low-frequency disturbances are applied in true triaxial loading tests, accompanied by acoustic emissions (AE) and internal image monitoring for damage. The results show that (1) increasing the minimum principal stress (along the axial direction of the tunnel) will improve tunnel stability, and (2) during the damage process of straight-wall arched tunnels, whether caused by static stress or low-frequency disturbances, the dissipated energy and AE count had demonstrated identical increasing trends in their numerical values. (3) When the straight-wall arched roadway had been damaged by low-frequency disturbances, the dissipated energy and AE count had increased gradually at first and then surged rapidly upon macroscopic damage, following a trend similar to an exponential function.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.We have confirmed the correctness of the authors and their  affiliations

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来源期刊
CiteScore
4.40
自引率
10.70%
发文量
234
审稿时长
4-8 weeks
期刊介绍: Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.
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