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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #292323
Title: Particle models for discrete element modeling of bulk grain properties of wheat kernels

Author
item BOAC, JOSEPHINE - Kansas State University
item Casada, Mark
item MAGHIRANG, RONALDO - Kansas State University
item HARNER, III, JOSEPH - Kansas State University

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 3/11/2013
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Recent research has shown the potential of discrete element method (DEM) in simulating grain flow in bulk handling systems. Research has also revealed that simulation of grain flow with DEM requires establishment of appropriate particle models for each grain type. This research completes the three-part simulation of particle models for the three common and widely used grains: corn, soybeans, and wheat. The third grain type, wheat, was modeled using particle models comprised of one to four overlapping spheres. Bulk properties (i.e., angle of repose, bulk density, and hopper flow) were simulated using DEM with published data on material properties (i.e., particle shape, size distribution, Poisson’s ratio, shear modulus, and density) and interaction properties (i.e., particle coefficients of restitution, static friction, and rolling friction) of wheat kernels as inputs. Predicted results were compared with published experimental data to establish the most appropriate particle models. Preliminary results showed that the most appropriate particle model for wheat kernels may either be single-sphere or a three-sphere particle models that included coefficient of restitution of 0.60 or 0.80, coefficient of static friction of 0.30 or 0.60 for wheat-wheat contact (0.25 or 0.55 for wheat-steel interaction), coefficient of rolling friction of 0.05 or 0.20, and a normal particle size distribution with a standard deviation factor of 0.4. Further simulations are ongoing to determine the effects of shear modulus. This paper will present the methods used to establish appropriate physical properties for the particle model and first results from the DEM simulations.