Abstract: In order to build the analytic model of soybean kernel using Discrete Element Method (DEM), the shape and size of soybean kernel are measured and analyzed. It is found that the shape of a soybean kernel can be approximated to an ellipsoid. The three axis dimensions follow normal distribution, and there exists a certain correlation between the primary dimension and the secondary dimension. On this basis, a soybean kernel modeling method is proposed based on the sphere filling. The shape of the soybean kernel is approximated to an ellipsoid, and the three axis dimensions are determined as the mean values of measured soybean kernels. The primary dimension of the analytical model of a kernel, which follows normal distribution, is randomly generated, and the secondary dimension of the kernel is calculated according to the relationship between the primary and secondary dimensions. As a result, the assemble model of the soybean kernels with different size and distribution is built. Two varieties of soybean kernels are selected as the research objects. By comparison between the simulated results and the experimental results of the packing test and the self-flowing screening test proposed in this work, it is shown that, when the amount of filling-spheres is five, the simulation results are in good agreement with the experiment results, thus, preliminarily verifying the effectiveness and feasibility of proposed modeling method.

Key words: agricultural engineering, discrete element method, soybean kernel, particle modelling, simulation analysis