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Latest revision as of 10:58, 1 July 2024

Abstract

DEM (discrete element method) is a widely used numerical simulation method, which models the behaviour of a bulk substrate based on the individual interactions of many particles. One of its possible applications is the modelling of sand behaviour in different laboratory tests, e.g., cone penetration tests [1] or direct shear tests [2]. Furthermore, DEM is specifically of interest as a modelling method for investigating air pluviation, because it models the individual inter-particle and particle-environment interactions, both friction and collisions, which determine the compaction and homogeneity of the created samples. However, one disadvantage of DEM is the relatively long computational time [3] especially with decreasing particle sizes. This makes larger particle sizes compared to reality more interesting, especially for large scale or repeating simulations. On the other hand, if the size of the chosen particles is too large, certain interactions, such as interactions with other materials and equipment, may not be simulated in a way that properly represents real behaviour. This would lead to preferring smaller sized particles, which again would lead to longer computational times. Therefore, the chosen particle size as an important aspect of DEM simulations will be discussed, as well as the effects on different simulation aspects. This includes necessary parameter calibrations, the resulting inter-particle and particle-environment interactions as well as the achieved simulation results and accuracies. Of specific interest is the largest particle size, at which accurate and realistic results concerning real-world particle interactions can be achieved. Further, the effects of graded particle sizes to better represent the sand during the pluviation process will be discussed.

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Published on 01/07/24
Accepted on 01/07/24
Submitted on 01/07/24

Volume Numerical Methods and Algorithms in Science and Engineering, 2024
DOI: 10.23967/wccm.2024.057
Licence: CC BY-NC-SA license

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