Pull Experiment to Validate Photogrammetrically Predicted Friction Angle of Rock Discontinuities

The estimation of the mechanical properties of rock joints is crucial in terms of safety when it comes to design of slopes in open pit mines or caverns used for the storage of hazardous materials, for instance - nuclear waste. Photogrammetry provides a simple, objective method for joints roughness assessment, without the need for expensive and time consuming laboratory tests or subjective empirical methods. In this study, a new photogrammetric method was used to estimate the roughness, shear strength and friction angle of a discontinuity of 2 m by 1 m fresh rock joint. The estimation was done by analyzing the profiles of digital models of joint surface. Surface Length and Slope Measurement methods were used to calculate the values of Joint Roughness Coefficient (JRC) of analyzed surfaces. Next, the shear strength and friction angle of the rock discontinuity were obtained experimentally with multistage pull testing. The results obtained with both methods were analyzed and compared. JRC values from photogrammetrically created digital models of the joint surface were overestimated due to the low density of the models, which resulted in high noise to signal ratio. Shear strength obtained with photogrammetrically created models were overestimates in relation to the results of the pull test by approximately 45%. The errors made during this research are analyzed in the article and recommendations on how to improve reliability of the results are made. Main error in photogrammetric prediction was low density of the point clouds and in laboratory test too low stiffness of the test arrangement. The alternative methodology for photogrammetric studies used in previous stage of the research project was tested during this study and was proven to give significantly higher accuracy of generated digital models. The stiffness of the testing machine and proper positioning of the sample halves on top of each other were identified as the most sensitive aspects of methodology of big scale pull test when it comes to the reliability of results.