Friction Coefficient Calibration of Sunflower Seeds for Discrete Element Modeling Simulation

Abstract

Sunflower (Helianthus annuus L.) is one of the four major oil crops in the world and has high economic value. However, the lack of discrete element method (DEM) models and parameters for sunflower seeds hinders the application of DEM for computer simulation in the key working processes of sunflower seed sowing and harvesting. The present study was conducted on two varieties of sunflower, and the DEM model of sunflower seeds was established by using 3D scanning technology based on the distribution of triaxial dimensions and volumes of the geometric model of sunflower seeds. Similarly, the physical characteristics parameters of sunflower seeds were determined by physical tests and the simulation parameters were screened for significance based on the Plackett-Burman test. Our results show that the coefficient of static friction between sunflower seeds and the coefficient of rolling friction have significant effects on the repose angle of the simulation test. Furthermore, the optimal range of the significance parameters was further determined by the steepest climb test, and the second-order regression model of the significance parameters and the repose angle was obtained according to the Box-Behnken design test and Response Surface Methodology (RSM), with the repose angle measured by the physical test as the optimized target value to obtain the optimal parameter combination. Finally, a two-sample t-test for the repose angle of the physical test and the repose angle of the simulation test yielded P > 0.05. Our results confirms that the repose angle obtained from simulation is not significantly different from the physical test value, and the relative errors between the repose angle of the simulation test and the physical test are 1.43% and 0.40%, respectively, for the optimal combination of parameters. Based on these results it can be concluded that the optimal parameters obtained from the calibration can be used for DEM simulation experiments related to the sunflower seed sowing and harvesting process.