Parameter calibration for discrete element simulation of Leymus chinensis seeds based on RSM optimization.

Focus on the shortage of Leymus chinensis seeds' discrete element parameters in the research of the seeds in production equipment, the study carried out parameter calibration and verification. The focus of this study is on the shortage of discrete element parameters for Leymus chinensis seeds in research related to seed production equipment. The study involved parameter calibration and verification. First, the physical property parameters of the seeds were measured through physical experiments to determine the range of the simulation parameters. Using Response Surface Methodology, a simulation accumulation test was conducted. Subsequently, the simulation parameters were calibrated and optimized. Specifically, significant parameters affecting the repose angle were identified using the Plackett-Burman Design test. The optimal value range of these parameters was then determined through a steepest slope climbing test. A second-order regression model between the significant parameters and the simulated stacking angle was established through the Box-Behnken Design experiment. The regression model was optimized by using the repose angle from the physical test as the target value. The obtained optimal parameter combination was then used to conduct a simulation test. The results showed that the relative error between the simulation and physical test was only 0.94%. This proves the accuracy, reliability, and authenticity of the simulated contact parameters. The study provides a theoretical basis for the optimization design and simulation research of Leymus chinensis seeds harvesting technology and equipment.