Determination Method of Core Parameters for the Mechanical Classification Simulation of Thin-Skinned Walnuts

Yang Jiang, Yurong Tang, Wen Li, Yong Zeng, Xiaolong Li, Yang Liu and Hong Zhang ()
Additional contact information
Yang Jiang: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Yurong Tang: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Wen Li: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Yong Zeng: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Xiaolong Li: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Yang Liu: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China
Hong Zhang: College of Mechanical and Electronic Engineering, Tarim University, Alar 843300, China

Agriculture, 2022, vol. 13, issue 1, 1-17

Abstract: Simulation can be used to visualize the mechanical classification of walnuts. It can collect microscopic information about walnuts in the classification roller and guide its optimization design. In this process, simulation parameters are essential factors that ensure the effectiveness of the simulation. In this study, the crucial parameters of thin-skinned walnut particles in classification simulation were determined by combining the discrete element method (DEM) and physical tests. Firstly, the moisture content, shear modulus, stacking angle, and some contact parameters in the shell and kernel were obtained by drying test, compression test, cylinder lifting test, and physical test of contact parameters, respectively. A walnut model was constructed using reverse modeling technology. Then, the ranges of the rest contact parameters were determined using simulation inversion based on the Generic EDEM Material Model database. Second, the parameters significantly influencing the stacking angle were screened via the Plackett–Burman test using contact parameters as factors and stacking angle as the index. The results revealed that the walnut–walnut static friction coefficient, walnut–walnut rolling friction coefficient, and walnut–steel plate static friction coefficient significantly affect the stacking angle. The steepest ascent experiment produced the optimal value intervals of crucial parameters. Besides, a quadratic regression model of important parameters was built using the Box–Behnken test to achieve the optimal parameter combination. The stacking and classification experiments verified that the stacking angle and morphology are mostly similar under calibration parameters without any considerable differences. The relative error was only 0.068%. Notably, the relative error of the average staying time of walnut in the classification roller was 0.671%, and the dimensionless distribution curves of stay time were consistent. This study provides technological support to the simulation analysis of walnut classification and recommends novel methods and references to determine the parameters of other shell materials.

Keywords: walnut; classification; discrete element; reverse modelling; parameter calibration (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/13/1/104/pdf (application/pdf)
https://www.mdpi.com/2077-0472/13/1/104/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:13:y:2022:i:1:p:104-:d:1019673

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().