LAPSE:2023.1591
Published Article

LAPSE:2023.1591
Calibration of Physical Characteristic Parameters of Granular Fungal Fertilizer Based on Discrete Element Method
February 21, 2023
Abstract
Based on a combination of physical and simulation experiments, a set of basic physical characteristic parameters and contact parameters suitable for granular fungal fertilizers were calibrated, which up to now have received little attention. The physical morphological characteristic parameters (overall dimension, 1000 grain weight, density, and moisture content), mechanical characteristic parameters (Poisson’s ratio, elastic modulus, and shear modulus), and contact parameters (static friction coefficient, rolling friction coefficient and recovery coefficient) of particles were measured through physical experiments. The parameters were screened for significance using the Plackett−Burman test. The results showed that the impact recovery coefficient, static friction coefficient, and rolling friction coefficient for the granular fungal fertilizer particles had a significant effect on the repose angle. The best range for the three parameters was determined using the steepest climbing test. The second-order regression model was optimized using the Box−Behnken design test. The relative error between the simulated repose angle (21.74°) and the physical test repose angle (21.84°) was small (0.50%). These optimal parameters obtained by calibration can provide a basis for the simulation analysis and parameter optimization of variable-rate fertilization systems.
Based on a combination of physical and simulation experiments, a set of basic physical characteristic parameters and contact parameters suitable for granular fungal fertilizers were calibrated, which up to now have received little attention. The physical morphological characteristic parameters (overall dimension, 1000 grain weight, density, and moisture content), mechanical characteristic parameters (Poisson’s ratio, elastic modulus, and shear modulus), and contact parameters (static friction coefficient, rolling friction coefficient and recovery coefficient) of particles were measured through physical experiments. The parameters were screened for significance using the Plackett−Burman test. The results showed that the impact recovery coefficient, static friction coefficient, and rolling friction coefficient for the granular fungal fertilizer particles had a significant effect on the repose angle. The best range for the three parameters was determined using the steepest climbing test. The second-order regression model was optimized using the Box−Behnken design test. The relative error between the simulated repose angle (21.74°) and the physical test repose angle (21.84°) was small (0.50%). These optimal parameters obtained by calibration can provide a basis for the simulation analysis and parameter optimization of variable-rate fertilization systems.
Record ID
Keywords
discrete element, granular fungal fertilizer, Optimization, parameter calibration, repose angle
Subject
Suggested Citation
Yu S, Bu H, Dong W, Jiang Z, Zhang L, Xia Y. Calibration of Physical Characteristic Parameters of Granular Fungal Fertilizer Based on Discrete Element Method. (2023). LAPSE:2023.1591
Author Affiliations
Yu S: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Bu H: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Dong W: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Jiang Z: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Zhang L: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Xia Y: Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Instatute of Technology, Beijing 100081, China
Bu H: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Dong W: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Jiang Z: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Zhang L: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China
Xia Y: Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Instatute of Technology, Beijing 100081, China
Journal Name
Processes
Volume
10
Issue
8
First Page
1564
Year
2022
Publication Date
2022-08-10
ISSN
2227-9717
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Original Submission
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PII: pr10081564, Publication Type: Journal Article
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LAPSE:2023.1591
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https://doi.org/10.3390/pr10081564
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Feb 21, 2023
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