The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters

Establishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. This study focuses on high-moisture corn ears during the early harvest stage, developing a fragmentable corn ear...

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Main Authors: Chunrong Li, Zhounan Liu, Ligang Geng, Tianyue Xu, Weizhi Feng, Min Liu, Da Qiao, Yang Wang, Jingli Wang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Agriculture
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Online Access:https://www.mdpi.com/2077-0472/15/7/752
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author Chunrong Li
Zhounan Liu
Ligang Geng
Tianyue Xu
Weizhi Feng
Min Liu
Da Qiao
Yang Wang
Jingli Wang
author_facet Chunrong Li
Zhounan Liu
Ligang Geng
Tianyue Xu
Weizhi Feng
Min Liu
Da Qiao
Yang Wang
Jingli Wang
author_sort Chunrong Li
collection DOAJ
description Establishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. This study focuses on high-moisture corn ears during the early harvest stage, developing a fragmentable corn ear model and calibrating its bonding parameters. First, based on the Hertz–Mindlin method in the Discrete Element Method, a three-layer corn cob bonding model consisting of pith, woody ring structure, and glume was established. Through a combined experimental and simulation calibration approach, the bonding parameters of the cob were determined using Plackett–Burman tests, the steepest ascent tests, and Box–Behnken tests. Subsequently, the same method was applied to establish a corn kernel bonding model, with the kernel bonding parameters calibrated through the steepest ascent and Box–Behnken tests. In order to arrange the kernel models on the cob model to achieve the construction of a complete ear model, this paper proposes a “matrix coordinate positioning method”. Through calculations, this method enables the uniform arrangement of corn kernels on the cob, thereby accomplishing the establishment of a composite model for the high-moisture corn ear. The bonding parameters between the cob and kernels were determined through compression tests. Finally, the reliability of the model was partially validated through shear testing; however, potential confounding variables remain unaccounted for in the experimental analysis. While this study establishes a theoretical framework for the design and optimization of machinery dedicated to high-moisture corn ear fragmentation processes, questions persist regarding the comprehensiveness of variable inclusion during parametric evaluation. This analytical approach exhibits characteristics analogous to incomplete system modeling, potentially limiting the generalizability of the proposed methodology.
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spelling doaj-art-ee88d39181f3499a9b2cdc7516fe9aeb2025-08-20T03:08:43ZengMDPI AGAgriculture2077-04722025-03-0115775210.3390/agriculture15070752The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding ParametersChunrong Li0Zhounan Liu1Ligang Geng2Tianyue Xu3Weizhi Feng4Min Liu5Da Qiao6Yang Wang7Jingli Wang8College of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaCollege of Biological and Agricultural Engineering, Jilin University, Changchun 130021, ChinaCollege of Engineering and Technology, Jilin Agricultural University, Changchun 130118, ChinaEstablishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. This study focuses on high-moisture corn ears during the early harvest stage, developing a fragmentable corn ear model and calibrating its bonding parameters. First, based on the Hertz–Mindlin method in the Discrete Element Method, a three-layer corn cob bonding model consisting of pith, woody ring structure, and glume was established. Through a combined experimental and simulation calibration approach, the bonding parameters of the cob were determined using Plackett–Burman tests, the steepest ascent tests, and Box–Behnken tests. Subsequently, the same method was applied to establish a corn kernel bonding model, with the kernel bonding parameters calibrated through the steepest ascent and Box–Behnken tests. In order to arrange the kernel models on the cob model to achieve the construction of a complete ear model, this paper proposes a “matrix coordinate positioning method”. Through calculations, this method enables the uniform arrangement of corn kernels on the cob, thereby accomplishing the establishment of a composite model for the high-moisture corn ear. The bonding parameters between the cob and kernels were determined through compression tests. Finally, the reliability of the model was partially validated through shear testing; however, potential confounding variables remain unaccounted for in the experimental analysis. While this study establishes a theoretical framework for the design and optimization of machinery dedicated to high-moisture corn ear fragmentation processes, questions persist regarding the comprehensiveness of variable inclusion during parametric evaluation. This analytical approach exhibits characteristics analogous to incomplete system modeling, potentially limiting the generalizability of the proposed methodology.https://www.mdpi.com/2077-0472/15/7/752high-moisture corn earscrushing modelHertz–Mindlin modelDEM
spellingShingle Chunrong Li
Zhounan Liu
Ligang Geng
Tianyue Xu
Weizhi Feng
Min Liu
Da Qiao
Yang Wang
Jingli Wang
The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
Agriculture
high-moisture corn ears
crushing model
Hertz–Mindlin model
DEM
title The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
title_full The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
title_fullStr The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
title_full_unstemmed The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
title_short The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters
title_sort establishment of a high moisture corn ear model based on the discrete element method and the calibration of bonding parameters
topic high-moisture corn ears
crushing model
Hertz–Mindlin model
DEM
url https://www.mdpi.com/2077-0472/15/7/752
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