GPU based discrete element modeling for convex polyhedral shape particles: Development and validation

Particle dynamics simulations face a significant challenge in understanding the intricate behaviors of convex polyhedral particles due to their complex geometries and interactions. DEM emerges as a key method, illuminating the concealed intricacies of these geometric entities. Traditional algorithms...

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Veröffentlicht in:Powder technology Jg. 449; S. 120407
Hauptverfasser: Mittal, Aman, Mangadoddy, Narasimha, Banerjee, Raja
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 15.01.2025
Schlagworte:
algorithms
Convex polyhedra
geometry
GPU-based DEM
Granular dynamics
mechanical properties
technology
Convex polyhedra
GPU-based DEM
Granular dynamics
ISSN:0032-5910
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Zusammenfassung:Particle dynamics simulations face a significant challenge in understanding the intricate behaviors of convex polyhedral particles due to their complex geometries and interactions. DEM emerges as a key method, illuminating the concealed intricacies of these geometric entities. Traditional algorithms often require cumbersome processes to check each type of contact individually. However, Gilbert–Johnson–Keerthi’s (GJK) and the expanding polytope algorithm (EPA) provide efficient numerical solutions for polyhedral contact detection and contact resolution. These Minkowski difference-based methods streamline contact detection and overlap computation, paving the way for deeper exploration of three-dimensional contact theory within DEM simulations. By leveraging GPU computational power, this paper outlines key algorithmic steps and verifies the solver’s accuracy through comparison with simulated and experimental data, with an average deviation of less than 5%. This study explores the impact of particle shape on the dynamics and mechanical behavior of densely packed systems, particularly in hoppers and tumblers. Spherical particles discharge faster but mix more slowly than polyhedral shapes, with icosahedrons achieving quicker full mixing. These results align with experimental findings, further validating the simulation approach. [Display omitted] •Developed 3D GPU-parallel framework for enhanced efficiency of non-spherical DEM solver.•Uses GJK-EPA algorithms for convex polyhedral contact detection and resolution strategy.•Stability & robustness is tested using cubes stacking & polyhedral particle packing fractions.•Validated mass-flowrates & angle of repose for different shape particles in hopper & tumbler.•Initial mixing rate is higher for spherical shapes, but full mixing is slower than polyhedral.
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ISSN:0032-5910
DOI:10.1016/j.powtec.2024.120407