Numerical Investigation of the Contribution of Different‐Scale Rock Joint Roughness to Shear Strength

ABSTRACT The shear resistance of rock joints is significantly influenced by the different‐scale surface roughness. In this paper, the revised Grasselli's morphological parameters, and , are demonstrated to describe small‐scale unevenness (second‐order roughness) and large‐scale waviness (first‐order roughness), respectively. This provides a more straightforward approach for roughness decomposition of rock joints. Furthermore, the numerical shear tests are conducted using the Particle Flow Code (PFC) to reproduce the shear behavior of rock joints with progressive degradation of two‐order roughness. The results indicate that the failure of waviness is governed by the tensile strength of the joint walls, whereas the failure of unevenness is controlled by compressive strength. Based on these findings, a modified shear strength model is developed by extending the joint roughness coefficient‐joint compressive strength (JRC‐JCS) model. The proposed model is validated through numerical simulations, laboratory direct shear tests, and published data on rock joints with both standard profiles and natural surfaces. Compared with the JRC‐JCS model, the proposed model provides a more refined description of joint surface roughness by explicitly distinguishing the contributions of waviness and unevenness. It could predict the peak shear strength more accurately and offers better support for the stability assessment of jointed rock masses.

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Publication Details

Journal
International Journal for Numerical and Analytical Methods in Geomechanics
Published
2026-04-14
DOI
https://doi.org/10.1002/nag.70321
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Numerical Investigation of the Contribution of Different‐Scale Rock Joint Roughness to Shear Strength

Chenjie Hong, Hanqian Weng, Man Huang, ZhiCheng Tang et al.
International Journal for Numerical and Analytical Methods in Geomechanics
Rock Mechanics and Modeling
article

Numerical Investigation of the Contribution of Different‐Scale Rock Joint Roughness to Shear Strength

Chenjie Hong, Hanqian Weng, Man Huang, ZhiCheng Tang, Guangtao Zhang, Chuanjiu Zhang, Zhigang Tao, Kai Wang
article en

Abstract

ABSTRACT The shear resistance of rock joints is significantly influenced by the different‐scale surface roughness. In this paper, the revised Grasselli's morphological parameters, and , are demonstrated to describe small‐scale unevenness (second‐order roughness) and large‐scale waviness (first‐order roughness), respectively. This provides a more straightforward approach for roughness decomposition of rock joints. Furthermore, the numerical shear tests are conducted using the Particle Flow Code (PFC) to reproduce the shear behavior of rock joints with progressive degradation of two‐order roughness. The results indicate that the failure of waviness is governed by the tensile strength of the joint walls, whereas the failure of unevenness is controlled by compressive strength. Based on these findings, a modified shear strength model is developed by extending the joint roughness coefficient‐joint compressive strength (JRC‐JCS) model. The proposed model is validated through numerical simulations, laboratory direct shear tests, and published data on rock joints with both standard profiles and natural surfaces. Compared with the JRC‐JCS model, the proposed model provides a more refined description of joint surface roughness by explicitly distinguishing the contributions of waviness and unevenness. It could predict the peak shear strength more accurately and offers better support for the stability assessment of jointed rock masses.

International Journal for Numerical and Analytical Methods in Geomechanics
Shaoxing University (CN), University of Exeter (GB), China University of Mining and Technology (CN), Shenhua Group (China) (CN), China Shenhua Energy (China) (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Rock Mechanics and Modeling
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