Rock joint coefficients and their computerized classification

A computerized method for determining rock joint coefficients is presented.Two relative similarity indicators are introduced to classify surface morphology of rock joints.The classification enables to compare investigated and database rock joints.Such a comparison aims at finding the couple of surfaces that are distinguished by the highest dynamical conformity.The first absolute indicator results from the Fourier matrix and evaluates wavy shapes of surfaces.The second absolute indicator quantifies the heights of surface reliefs and is defined as the root mean square height of the surface outline.Numerical reliability of these indicators is tested within the surface analysis of a series of limestone specimens.Besides the computerized assessment,25 people have performed visual assessment of these limestone specimens.The results of visual assessments have been statistically processed and compared to the results received from the computerized procedure.The newly introduced absolute indicators have proved to be prospective numerical tools for evaluating joint rock coefficients.

Investigation on the Indeterminate Information of Rock Joint Roughness through a Neutrosophic Number Approach

To better estimate the rock joint shear strength,accurately determining the rock joint roughness coefficient(JRC)is the first step faced by researchers and engineers.However,there are incomplete,imprecise,and indeterminate problems during the process of calculating the JRC.This paper proposed to investigate the indeterminate information of rock joint roughness through a neutrosophic number approach and,based on this information,reported a method to capture the incomplete,uncertain,and imprecise information of the JRC in uncertain environments.The uncertainties in the JRC determination were investigated by the regression correlations based on commonly used statistical parameters,which demonstrated the drawbacks of traditional JRC regression correlations in handling the indeterminate information of the JRC.Moreover,the commonly used statistical parameters cannot reflect the roughness contribution differences of the asperities with various scales,which induces additional indeterminate information.A method based on the neutrosophic number(NN)and spectral analysis was proposed to capture the indeterminate information of the JRC.The proposed method was then applied to determine the JRC values for sandstone joint samples collected from a rock landslide.The comparison between the JRC results obtained by the proposed method and experimental results validated the effectiveness of the NN.Additionally,comparisons made between the spectral analysis and common statistical parameters based on the NN also demonstrated the advantage of spectral analysis.Thus,the NN and spectral analysis combined can effectively handle the indeterminate information in the rock joint roughness.