Discrete Meta-Simulation of Silage Based on RSM and GA-BP-GA Optimization Parameter Calibration

Abstract

The EDEM software (Altair EDEM 2022.0 professional version 8.0.0) was used to create a discrete element model of silage to address the lack of silage evidence parameters and contact parameters between silage and conveying equipment when using the discrete element method to simulate and analyze crucial aspects of silage conveying and feeding. Physical tests and simulations were used to calibrate the significant parameters, and the silage stacking angle obtained from simulation and tests was then validated. The response value of the stacking angle (38.65°) obtained from the physical examination was used as the response value. The response surface (RSM) finding and the GA finding based on the genetic algorithm (GA) artificial neural network (BP) model were used to compare the significance parameters. The PB and steepest climb tests were used to screen the significant factors. Results indicate that the static friction coefficient between silage and silage, the rolling friction coefficient between silage and silage, and the static friction coefficient between silage and the steel body are significant factors affecting the stacking angle of numerical simulation; the parameter optimization effect of GA-BP-GA is superior to that of RSM; the optimal parameter combinations are as follows: 0.495, 0.194, and 0.420, respectively, and the simulated stacking angle is 39.1510°, which matches the empirical test result. The relative error between the simulated and stacking angles derived from the physical test was 1.3%. The results demonstrate that the silage model is reliable within the parameters derived from the calibration, and that the calibrated parameters can be used in other discrete element simulation studies of silage.