Abstract

Rock strength is generally divided into the components of cohesion and internal friction. These components are two important parameters for estimating the damaged or disturbed zone around an excavation and its corresponding support design. However, the cohesive and frictional strength components at the same strain increment before peak strength are difficult to separate from each other. In addition, the misperception of their mutual evolution has been in existence for a long time. A numerical code, Rock Failure Process Analysis (RFPA2D), based on the finite element method was used in this study to clarify this misperception. The RFPA2D approach can account for rock heterogeneity and capture the entire rock failure process without prior assumptions regarding where and how microcracks and fracturing develop. Numerical models of rock were copied and reused in uniaxial and biaxial tests to create identical heterogeneous models for use under different confining stress conditions. Forty-five numerical tests (5 homogeneity indexes × 9 confining pressures) were used to calculate the results of the principal stresses (σ 1 and σ 3) at specified increments of axial strain. The intercept and the slope of a linear line fitting to the principal stresses at the same strain before peak strength were obtained in the principal stress space. The intercept is related to the cohesive strength component of the shear resistance, and the slope of the linear line is a pseudo-internal friction coefficient. Through the analysis of the linear fitting results, it has been found that the cohesive strength component increases while the pseudo-internal friction coefficient decreases with increasing homogeneity index of the numerical rock models. The values of cohesion and internal friction vary as a function of the strain state, and they are immediately activated with a strain increment before peak strength. The research results strengthen the understanding of the mobilization of the load-bearing capacity of rock mass surrounding an opening and can improve the design of practical support systems.

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