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Experimental verification and simulation analysis of a multi-sphere modelling approach for wheat seed particles based on the discrete element method.

Authors :
Fan, Jianhua
Wang, Hongwei
Sun, Kai
Zhang, Liang
Wang, Lu
Zhao, Jinwen
Yu, Jianqun
Source :
Biosystems Engineering. Sep2024, Vol. 245, p135-151. 17p.
Publication Year :
2024

Abstract

A comprehensive modelling methodology is proposed to describe wheat seeds using the discrete element method. By analysing the geometrical characteristics of wheat seeds, the multi-sphere approach is employed to establish 7-, 11-, 15-, 19-, and 23-sphere models based on ellipsoids. The physical and mechanical characteristics of wheat grain are measured and calibrated. Then, the proposed model is verified with several assessment criteria by contrasting the results of the experiment and simulation, including the wheat seed volume fraction, static angle of repose, hopper discharge, rotating drum and "self-flow screening". By balancing the accuracy of the multi-sphere model and computational efficiency, the 7-sphere or 11-sphere model is found to be the optimal model for determining the static stacking behaviour and hopper discharge of wheat seeds. For the rotating drum and the "self-flow screening", there is a considerable discrepancy between the simulation and experimental findings due to the surface roughness of the 7- and 11-sphere models. However, 15-, 19-, and 23-sphere models show a high accuracy, which can be applied for drying seeds of the rotating drum and accurately reproducing the sieve permeability of the "self-flow screening" experiment. In summary, the proposed multi-sphere method can be extended to related industry fields by demonstrating satisfactory accuracy in several validation tests. • A general multi-sphere modelling approach for wheat seed based on DEM is proposed. • DEM parameters of wheat grain are measured and calibrated. • Wheat grain experiments are conducted to verify the accuracy of the model. • Provides an effective guide for the validation of irregular particle models. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15375110
Volume :
245
Database :
Academic Search Index
Journal :
Biosystems Engineering
Publication Type :
Academic Journal
Accession number :
178909167
Full Text :
https://doi.org/10.1016/j.biosystemseng.2024.07.009