Structural Engineering and Mechanics

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Experimental and numerical study on pre-peak cyclic shear mechanism of artificial rock joints

  • Liu, Xinrong (School of Civil Engineering, Chongqing University) ;
  • Liu, Yongquan (School of Civil Engineering, Chongqing University) ;
  • Lu, Yuming (School of Civil Engineering, Chongqing University) ;
  • Kou, Miaomiao (School of Civil Engineering, Qingdao University of Technology)
  • Received : 2017.06.29
  • Accepted : 2019.11.27
  • Published : 2020.05.10
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Abstract

The pre-peak cyclic shear mechanism of two-order asperity degradation of rock joints in the direct shear tests with static constant normal loads (CNL) are investigated using experimental and numerical methods. The laboratory testing rock specimens contains the idealized and regular two-order triangular-shaped asperities, which represent the specific geometrical conditions of natural and irregular waviness and unevenness of rock joint surfaces, in the pre-peak cyclic shear tests. Three different shear failure patterns of two-order triangular-shaped rock joints can be found in the experiments at constant horizontal shear velocity and various static constant normal loads in the direct and pre-peak cyclic shear tests. The discrete element method is adopted to simulate the pre-peak shear failure behaviors of rock joints with two-order triangular-shaped asperities. The rock joint interfaces are simulated using a modified smooth joint model, where microscopic scale slip surfaces are applied at contacts between discrete particles in the upper and lower rock blocks. Comparing the discrete numerical results with the experimental results, the microscopic bond particle model parameters are calibrated. Effects of cyclic shear loading amplitude, static constant normal loads and initial waviness asperity angles on the pre-peak cyclic shear failure behaviors of triangular-shaped rock joints are also numerically investigated.

Keywords

Acknowledgement

This work is financially supported by the National Natural Science Foundation of China (Grant No. 41772319).

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