Affiliation:
1. Guilin University of Technology
Abstract
In response to the lack of accurate and reliable parameters in the discrete element simulation analysis of the sugarcane leaf crushing and return device, in this work, the actual and simulated errors of two stacking angles α and β of sugarcane leaves were used as indicators to calibrate the discrete element parameters. The second-order regression models between the important parameters and the indicators were obtained by Plackett-Burman test, steepest climb test, and Box-Behnken optimization test, and the analysis of variance and interaction factors were performed. The response surface method and particle swarm optimization algorithm were used to find the best significance parameters, and the best combination of significance parameters was obtained: the static friction coefficient between sugarcane leaves was 0.306, the rolling friction coefficient between sugarcane leaves was 0.198, and the recovery coefficient of sugarcane leaf-plate collision was 0.102. The relative errors of the simulation results and the physical test stacking angle α and stacking angle β were 0.609% and 1.643%, respectively. The calibration parameters can provide a theoretical reference for the design and research of sugarcane leaf crushing and returning machines, as well as the calibration of discrete element model parameters for leaf crops with high water content.
Subject
Waste Management and Disposal,Bioengineering,Environmental Engineering
Cited by
1 articles.
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