LAPSE:2022.0135
Published Article
LAPSE:2022.0135
A Comparative Study on the Modelling of Soybean Particles Based on the Discrete Element Method
Dongxu Yan, Jianqun Yu, Liusuo Liang, Yang Wang, Yajun Yu, Long Zhou, Kai Sun, Ping Liang
November 6, 2022
To solve the poor universality in the existing modelling approaches of soybean particles, we proposed a soybean particle modelling approach by combining five, nine, and 13 balls. The soybean seeds from three varieties (Suinong42, Jidou17, and Zhongdou39 with a sphericity of 94.78%, 86.86%, and 80.6%, respectively) are chosen as the study objects. By the comparisons between the simulation results and the test results in the “self-flow screening” and “piling angle” tests, it is concluded that the soybean particle modelling approach we presented in this paper is a universal modelling approach appropriate for soybean particles with different sphericities. The five-ball model is appropriate for the soybean particles with high sphericity, and the nine- or 13-ball models are applicable to those with low sphericity. The soybean particle modelling approach we presented is also compared with the ellipsoidal equation modelling approach for soybean particles and with the modelling approaches presented by other researchers. From an overall perspective, the soybean particle modelling approach we presented is better than the ellipsoidal equation modelling approach and those modelling approaches presented by other researchers. Additionally, it is shown that the multiple contacts issue in the multi-ball model has a little influence on the simulation results of soybean particle models. The study in this paper provides a new modelling approach for soybean particles in the DEM simulation of the contacts between soybean particles and the related machines.
Keywords
discrete element method, ellipsoidal equation model, multi-ball model, multiple contacts, particle modelling, soybean particles
Suggested Citation
Yan D, Yu J, Liang L, Wang Y, Yu Y, Zhou L, Sun K, Liang P. A Comparative Study on the Modelling of Soybean Particles Based on the Discrete Element Method. (2022). LAPSE:2022.0135
Author Affiliations
Yan D: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China [ORCID]
Yu J: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Liang L: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Wang Y: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Yu Y: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Zhou L: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Sun K: School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Liang P: Key Laboratory of Bionic Engineering, Jilin University, Ministry of Education of China, Changchun 130022, China
Journal Name
Processes
Volume
9
Issue
2
First Page
286
Year
2021
Publication Date
2021-02-02
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9020286, Publication Type: Journal Article
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LAPSE:2022.0135
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doi:10.3390/pr9020286
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Nov 6, 2022
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Mina Naeini
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