Mechanical Behavior and Failure Control of an Anchorage Body Using Constant-Resistance Large-Deformation Bolts

作者
Pengfei Guo,Xingyu Zhang,Zhikang Li,Hongye Zhang,Jinzhu Hu,Fuyang Zhang,Xichun Tian,Danyang Yu,Chuangzhou Wu,Manchao He
出处
期刊:International Journal of Geomechanics [American Society of Civil Engineers]
卷期号:26 (11)
标识
DOI:10.1061/ijgnai.gmeng-13914
摘要

Abstract The anchorage body is a crucial subject of geotechnical research due to the unique collaboration between the rock and the bolt. The constant-resistance large-deformation (CRLD) bolt has demonstrated its unusual mechanical behaviors, but the mechanical performance of constant-resistance anchorage body (CRAB) remains largely unexplored, raising fundamental questions about its mechanical properties. This study conducts a series of tests to assess the mechanical behavior and failure mechanism of CRAB. Results show that, in contrast to the random universal cracks formed in the unsupported specimen, CRAB localizes crack initiation near CRLD bolts and transforms tensile cracking into shear failure. This transformation in crack behavior is accompanied by measurable thermal responses during failure, which shows promise as a qualitative auxiliary indicator for localized damage. Furthermore, the influence of different anchorage parameters on CRAB is investigated. Reducing anchorage spacing, increasing the number of anchorages, and enlarging the anchorage angle enhance the CRAB performance. Sensitivity analysis identifies anchorage spacing as the most influential factor in CRAB performance. CRAB demonstrates both higher strength and significantly improved deformation capacity, which is critical for delaying crack propagation and preventing failure. A combined constitutive model is proposed to describe this unique mechanical response, explaining that the CRAB system sustains substantial deformation while remaining stable. Further validation is provided through comparison with the conventional anchorage body, in which CRAB exhibits nearly five times the deformation capacity of traditional systems. These findings advance the understanding of CRAB and underscore its strong potential for application in complex engineering environments.

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