Comparison of clumps and rigid blocks in three-dimensional DEM simulations: curvature-based shape characterization. (November 2022)

• Record Type: Journal Article
• Authors: Lu, Rui; Luo, Qiang; Wang, Tengfei; Zhao, Chunfa
• Is Part Of: Computers and geotechnics. Volume 151(2022)
• Publication Date: 2022-11
• Subjects: DEM -- Particle shape -- Curvature -- Clump -- Rigid block -- Shape characterization; Engineering geology -- Data processing -- Periodicals; Soil mechanics -- Data processing -- Periodicals; Rock mechanics -- Data processing -- Periodicals; 624.1510285
• DOI: 10.1016/j.compgeo.2022.104991
• Languages: English
• ISSNs: 0266-352X

Abstract

Abstract: Clumps and rigid blocks are two established models in the discrete element method (DEM) for representing digitized shapes of granules. However, few studies compared their shape characterization effectiveness and computational efficiency in describing actual shapes with different accuracies. This research proposes a two-dimensional roundness index ( RI 2 D ) and concave index ( CI ) to quantify surface morphology using a curvature-based method. After collecting material shape information via laser scanning, the models were assessed through three-dimensional DEM simulations at the grain and specimen levels, with balls used as a reference. The findings confirm RI 2 D and CI as two reliable indicators of the degree to which clumps and rigid blocks vary at the angular scale. Based on RI 2 D, both clumps and rigid blocks can robustly and reasonably characterize irregular surfaces. However, further improving the accuracy of clumps while satisfying CI requires a significantly greater number of pebbles (spherical units); rigid blocks are incapable of capturing the concavity feature of real particles. RI 2 D and CI correlate well with the final state in column collapse tests and the shear strength in coupled DEM − FDM (finite difference method) triaxial tests. The difference in simulating granule mechanical behaviors between the two particle models is insignificant with varying levels of accuracy.