Using Roughness of Excavated Rock Surface to Predict Cutting Forces: A Numerical Approach
Abstract
This paper utilizes Itasca's PFC3D to simulate linear rock cutting using disc cutters. The objective is to determine the correlation between excavated surface roughness and cutting forces experienced during excavation. The flat-joint BPM model was used to create a synthetic sandstone block in this paper. A rigid wall was modeled as a disc cutter. Cutting was achieved by applying angular and translational velocities to the cutter to achieve both rotational and translational motion. Several cuts were made on the block, completely planing the surface while recording the contact forces on the cutter. The 3D positions of the top-most balls on the excavated surface were determined and used to create a digital elevation model (DEM) of the excavated surface. Roughness parameters were calculated from the DEMs. Analyses of the forces and roughness data show that the surface roughness is positively correlated with the cutting forces. Cutting forces data obtained from laboratory tests that were conducted on rocks similar to the rock modeled in this paper were compared with the numerical results. Though the numerical results were consistently higher than the lab results, they had similar trends.
Recommended Citation
P. E. Ayawah et al., "Using Roughness of Excavated Rock Surface to Predict Cutting Forces: A Numerical Approach," Proceedings of the 53rd U.S. Rock Mechanics/Geomechanics Symposium (2019, Brooklyn, NY), American Rock Mechanics Association (ARMA), Jun 2019.
Meeting Name
53rd U.S. Rock Mechanics/Geomechanics Symposium (2019: Jun. 23-26, Brooklyn, NY)
Department(s)
Geosciences and Geological and Petroleum Engineering
Second Department
Mining Engineering
Keywords and Phrases
Cutting Forces; Disc Cutters; Mechanical Excavation; Numerical Modeling; PFC; Surface Roughness
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 American Rock Mechanics Association (ARMA), All rights reserved.
Publication Date
01 Jun 2019