Parameter calibration for simulation of Gentiana seedling substrate based on discrete element method

Abstract

The physical and mechanical parameters of the rotten rice straw (RRS), rice husk biochar (RHB), and the mixture of the two materials (the substrate) were calibrated by Plackett-Burman and Box-Behnken experiments to obtain the parameters for simulation of the forming of the Gentiana seedling substrate mat (GSSM). The particle contact parameters were calibrated, and the repose angle was taken as the response value based on the Hertz-Mindlin approach with the JKR contact model of discrete element method (DEM). A quadratic regression model was established and optimized using Design-Expert software. The parameters that most affected the substrate repose angle were the restitution coefficient of RRS of 0.20, the rolling friction coefficient of RRS of 0.04, the surface energy of RRS for JKR of 0.53, and the surface energy of RHB-RRS for JKR of 2.11. The simulated repose angle of the substrate and the bending strength of GSSM were compared with that of the verified experimental values respectively based on the optimal parameters. The relative errors of repose angles and bending strengths between the values of the simulation and the measurement were 0.71% and 1.39% respectively, indicating that the parameters obtained in this study can provide a reliable reference for the forming of GSSM.

Study on graphite motion law of copper-based graphite composites during friction

“…Numerical simulation methods can discretize the complex dynamic process, it is convenient for further study of friction and wear mechanism. The common numerical simulation methods are finite element method (FEM) (Cotter, 2023;Yang et al, 2022), discrete element method (DEM) (Galashev and Abramova, 2023;Liang et al, 2023), molecular dynamics (MD) method (Cui et al, 2023;Kim et al, 2023), etc. Since the copper-based graphite composites prepared by powder metallurgy are composed of particle systems, the DEM is more suitable to simulate the composite friction process, and the DEM has been successfully used to simulate complex friction and wear processes (Xie et al, 2019;Chen et al, 2022).…”