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​Correlation between Joint Roughness Coefficient (JRC) and Statistical Roughness Parameters
 

Authors

Tégawendé Nikiema, Nicolas Gonze, Fanny Descamps

DOI

Abstract

Rocks are polycrystalline, heterogeneous, and anisotropic media containing discontinuities that often create planes of weakness. These discontinuities influence the mechanical behavior of the rock mass through their surface morphology, their aperture, and their filling material. Surface morphology is generally characterized by roughness, which is used as an input parameter in analytical or numerical models of rock mass stability.
Quantifying the roughness of discontinuities is a complex operation that requires appropriate methodologies and tools. Barton’s Joint Roughness Coefficient (JRC) is widely used due to its simplicity for quantifying roughness and addressing joint shear strength. However, the visual comparison method is subjective and may cause biases in the JRC estimates. One way of eliminating this bias is to rely on statistical estimators as proposed by several authors. On this basis, the current study examines the added value of 3D optical profilometry for roughness quantification.
In order to test this approach, typical JRC profiles were digitized, and a 3D printer was used to create surfaces reproducing the roughness state of the profiles. These surfaces were analyzed with a 3D optical profilometer to determine statistical estimators. The results are analyzed to identify the most relevant estimators, and correlations with the JRC are proposed. When investigating the mechanical behavior of rock joints, such correlations will help converting statistical roughness estimates from fractures tested in laboratory into comprehensive JRC values to address joint shear strength.

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