The contact area and stress distribution along rock wall joints, play an important role in the behavior and mechanical properties of the rock mass in mining and tunneling. Although properties of rock fractures such as aperture, roughness, filling, contact area, and orientation are highly significant, limited effective methods exist for their investigation at a fundamental level. In this study, laboratory contact electrical resistance profiles are generated for limestone samples, and correlated with uniaxial compression stress measurements. Further, the observed paired resistance-stress laboratory results are simulated using an artificial neural network. Methods, results and analyses are presented to provide insights about complex processes involved in rock wall joint behavior.
Artificial Neural Network Modeling of Contact Electrical Resistance Profiles for Detection of Rock Wall Joint Behavior
Wang, F., and R. B. Kaunda. "Artificial Neural Network Modeling of Contact Electrical Resistance Profiles for Detection of Rock Wall Joint Behavior." Paper presented at the 51st U.S. Rock Mechanics/Geomechanics Symposium, San Francisco, California, USA, June 2017.
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