Development and validation of a DEM model for predicting impact damage of maize kernels

Abstract

A discrete element method (DEM) simulation was developed to predict the impact damage of maize kernels. The DEM model used an empirically-generated, three-parameter Weibull distribution to describe the damage probability from repeated impacts. The DEM model gave good predictions of the kernel damage fraction for different sample sizes and operating times in a Stein breakage tester. The root-mean-square deviation between the simulated and experimental damage fractions was 0.05. A sensitivity analysis was performed to study the effects of material and interaction properties on damage fraction. The damage resistance parameters, coefficients of restitution, and particle shape representation had significant effects on the damage fraction. The statistics of the contact-level data, e.g., number of contacts and impact speeds, were collected in the simulation to interpret the results of sensitivity analyses at the contact level. The locations where the damage occurs on the kernel and in the operating device were also predicted by the model. The DEM damage model is expected to be useful for providing guidance on designing and operating grain handling processes to minimise kernel damage and, thus, improve grain quality. • Three-parameter Weibull distribution describes damage resistance of maize kernels. • Polyhedra were used to represent maize kernel shapes. • Contact-level statistics from DEM model were used to predict grain damage locations.