Systematic Calibration and Validation Approach for Discrete Element Method (DEM) Modeling of Corn Under Varying Moisture Contents (MC)

Abstract

Abstract. Discrete Element Method (DEM) based simulation of grain threshing and conveyance processing at relatively dry to wet grain moisture content range has been limited. A comprehensive five-step framework of a DEM grain model calibration and validation of flow and grain impacts on equipment was investigated. The framework was examined by developing DEM models for corn grain moisture conditions sampled during crop harvesting, and simulated hopper discharge corn flow, and corn impact forces on a grain paddle elevator of a crop harvesting machine. Five bulk material response parameters were obtained from two calibration experiments of the angle of repose and direct shear test at the MC levels of 11%, 16%, and 26%. Latin hypercube sampling statistical design of experiment points, Gaussian Process Regression surrogate model, and optimization algorithms were successfully implemented to generate Hertz-Mindlin (HM) with Johnson-Kendall-Roberts (JKR) cohesive model of corn at three moisture content levels. The DEM simulation results predict the corn mass flow rate of hopper discharge with relative errors of -5%, -4%, and 1% for corn at 11%, 16%, and 26% MC levels, respectively. The DEM also predicts corn impact forces on a paddle elevator with a relative error of less than 11%. The established DEM calibration methodology, used for simulation of crop threshing, and harvested grain handling processes at extreme grain moisture content, can accelerate the simulation-based design of crop harvesting equipment. Keywords: Calibration, Corn, Discrete Element Method, Moisture Content, Sensitivity analysis, Validation.