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CLUMP: A Code Library to generate Universal Multi-sphere Particles

Lookup NU author(s): Vasileios Angelidakis, Dr Sadegh Nadimi, Professor Stefano Utili

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

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.


Publication metadata

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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