The joint roughness coefficient (JRC) is an important factor affecting the shear properties of rock joints, and its accurate estimation is a challenging task in rock engineering. Existing JRC evaluation approaches such as the empirical comparison method and the statistical parameter method have some unresolved defects. In this study, a new method is proposed for JRC estimation to overcome the deficiencies of existing approaches based on back calculation of shear strength. First, the 10 standard roughness joints are established in numerical rock samples generated by the bonded particle method (BPM). Secondly, the microscopic parameters of the intact rock and joints are calibrated, and a series of direct shear tests of joint samples are carried out under different normal stresses. Finally, the empirical relationships between shear strength and JRC are proposed under high correlation conditions. The results show that the modified smooth joint model (MSJM) is proved to better simulate the mechanical properties of rough joints than the smooth joint model (SJM). When the shear strength of target joint is substituted in the corresponding relationship, the JRC of joint along the shear direction can be conveniently obtained. In addition, the JRC values of 10 standard roughness joint profiles under shear direction of from right to left (FRTL) are obtained. By estimating the JRC of 9 target joints in the literature, it can be seen that the new method proposed in this paper can well reflect the directionality of roughness and it is convenient to apply.
Data-driven estimation of joint roughness coefficient
