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Lookup NU author(s): Vasileios AngelidakisORCiD, Dr Sadegh NadimiORCiD, Professor Stefano Utili
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Particle shape plays a key role in the mechanical and rheological behaviour of particulate and granular materials. The simulation of particulate assemblies typically entails the use of Molecular Dynamics, where spheres are the predominant particle shape, and the Discrete Element Method (DEM). Clumps and clusters of spheres have been used to simulate non-spherical particles, primarily due to the simplicity of contact detection among spheres and their ability to approximate practically any irregular geometry. Various approaches have been proposed in the literature to generate such clumps or clusters, while open-source numerical codes applying these are scanty. The CLUMP code, proposed in this paper, provides a unified framework, where a particle morphology can be approximated using different clump-generation approaches from the literature. This framework allows comparing the representations of the particle generated by the different approaches both quantitatively and qualitatively, providing the user with the tools to decide which approach is more appropriate for their application. Also, one novel generation technique is proposed. Outputs are provided in formats used by some of the most popular DEM codes. Moreover, the resulting clumps can be transformed into surface meshes, allowing for easy characterisation of their morphology. Finally, the effect of clump-generation techniques on the mechanical behaviour of granular assemblies is investigated via triaxial compression tests.
Author(s): Angelidakis V, Nadimi S, Otsubo M, Utili S
Publication type: Article
Publication status: Published
Journal: SoftwareX
Year: 2021
Volume: 15
Print publication date: 20/06/2021
Online publication date: 20/06/2021
Acceptance date: 07/06/2021
Date deposited: 22/06/2021
ISSN (electronic): 2352-7110
Publisher: Elsevier
URL: https://doi.org/10.1016/j.softx.2021.100735
DOI: 10.1016/j.softx.2021.100735
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