AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Publishing Language: Chinese

Calibration of discrete element parameters for the bending failure on the chilled Boer goat ribs

Jia WEI1,2Jiayi FU1,2Shucai WANG1,2Haopeng LIU1,2( )
College of Engineering , Huazhong Agricultural University , Wuhan 430070, China
Key Laboratory of Agricultural Equipment in the Middle and Lower Reaches of the Yangtze River, Ministry of Agriculture and Rural Development, Wuhan 430070, China
Show Author Information

Abstract

Large-scale mutton processing is ever-expanding with the increasing demand for meat production. Mechanized carcass segmentation has been one of the key steps to upgrade the mutton industries. Among them, the goat rib has been the main obstacle during segmentation. A scientific and reliable discrete element model of goat rib can be expected to provide both the analysis of mechanized goat carcass segmentation and the optimization of tool parameters. Taking the chilled Boer goat rib as the research object, this study aims to calibrate the discrete element parameters of the bending failure model using EDEM software. Firstly, a series of tests were carried out to determine the profile, density, Poisson’s ratio, and shear modulus of the goat rib. Next, the collision, inclined plane friction and friction coefficient measurement tests were conducted to measure the contact parameters, such as static friction coefficient, rolling friction coefficient, and collision recovery coefficient. The bending failure test of the goat rib was carried out on the texture analyzer to obtain the peak failure force and cutting position, which were the target values of the simulation. According to the actual test conditions, the discrete element model of goat rib was established to simulate the bending failure using Hertz-Mindlin with the bonding model in EDEM software. The path of the steepest ascent was used to determine the optimal parameters, including the optimal value of bonding parameters. A quadratic polynomial regression model was then optimized between the peak failure force and the four bonding parameters using response surface analysis. The optimal combination of four significant influencing factors was also obtained to solve the regression equation. The results illustrated that the normal stiffness per unit area was 7.07×1013 N/m3, the shear stiffness per unit area was 6.22×1012 N/m3, the critical normal stress was 1.34×108 Pa, and the critical shear stress was 1.87×108 Pa. Finally, the bending failure of five goat ribs was simulated to verify the accuracy and reliability of calibration. The maximum relative error between the simulated and the actual values was less than 6.49%, and the average relative error was 4.19%, indicating the credible calibration. This finding can also provide a theoretical basis for parameter optimization in the mechanized segmentation of goat rib during mutton processing.

CLC number: S233.5 Document code: A

References

【1】
【1】
 
 
Transactions of the Chinese Society of Agricultural Engineering
Pages 285-294

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
WEI J, FU J, WANG S, et al. Calibration of discrete element parameters for the bending failure on the chilled Boer goat ribs. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(21): 285-294. https://doi.org/10.11975/j.issn.1002-6819.202405082

385

Views

2

Downloads

0

Crossref

0

Web of Science

2

Scopus

Received: 13 May 2024
Revised: 28 September 2024
Published: 15 November 2024
© Chinese Society of Agricultural Engineering 2024