A graded granular material generation algorithm based on particle number probability distribution by DEM

Weichen Sun, Kai Wu and Haibo Huang

Physica A: Statistical Mechanics and its Applications, 2021, vol. 573, issue C

Abstract: This paper proposes an algorithm based on particle number probability distribution (PNPD), which is validated by two classic grading curves of Rosin–Rammler curve and Fuller curve. The PNPD algorithm is effective for the generation of graded granular materials, including spherical particles, irregular forms of clumps particles, and a mixture of both. The grading curves of generated samples are validated via experimental curves. We verified not only the gradation of granular samples in the entire sample, but also the local locations of the generated samples. In addition, the PNPD algorithm can generate graded granular materials on the conveyor belt in two and three dimensions in a dynamic process, which is consistent with the actual situation.

Keywords: DEM; Gradation; Probability; Irregular forms; Conveyor belt (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:573:y:2021:i:c:s0378437121001916

DOI: 10.1016/j.physa.2021.125919

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