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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 #398152

Research Project: Advancing Technologies for Grain Trait Measurement and Storage Preservation

Location: Stored Product Insect and Engineering Research

Title: Evaluation of particle models of corn kernels for discrete element method simulation of shelled corn mass flow

Author
item BOAC, JOSEPHINE - Kansas Department Of Health And Environment
item CASADA, MARK - US Department Of Agriculture (USDA)
item PORDESIMO, LESTER - US Department Of Agriculture (USDA)
item PETINGCO, MARVIN - Kansas State University
item MAGHIRANG, RONALDO - University Of Illinois
item HARNER III, JOSEPH - Kansas State University

Submitted to: Smart Agricultural Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/8/2023
Publication Date: 2/9/2023
Citation: Boac, J., Casada, M.E., Pordesimo, L.O., Petingco, M., Maghirang, R., Harner III, J. 2023. Evaluation of particle models of corn kernels for discrete element method simulation of shelled corn mass flow. Smart Agricultural Technology. 4. Article 100197. https://doi.org/10.1016/j.atech.2023.100197.
DOI: https://doi.org/10.1016/j.atech.2023.100197

Interpretive Summary: Optimizing bulk handling of grains is important for efficiently moving grain while minimizing physical deterioration and contamination from impurities in the systems. Simulation studies can replace expensive commercial scale experiments using the discrete element method (DEM) for simulating grain flow in handling operations, but validated models of the individual grain kernels are needed. We tested the capability of over 100 candidate models of corn kernels to predict angle of repose, flow from a hopper, and bulk density determined using the FGIS standard field measurement method. From the study, the most appropriate material input properties for modeling corn kernel using a single-sphere particle geometry included a particle coefficient of restitution of 0.30, particle coefficient of static friction of 0.30 for corn-corn contact, particle coefficient of static friction of 0.20 for corn-steel contact, particle coefficient of rolling friction of 0.05, normal particle size distribution with a standard deviation factor of 0.4, and particle shear modulus of 20 MPa. This model can be used to gain better insight into bulk flow of grain in materials handling equipment that includes operations such as mixing and blending and material segregation and particle deterioration through collision and abrasion.

Technical Abstract: Bulk handling behavior of grains can be studied experimentally, but large-scale investigations of grain flow especially at the commercial scale are expensive and time consuming, but the discrete element method (DEM) can be used for simulating grain flow in handling operations. The application of DEM for simulating grain flow requires development of appropriate particle models for each grain type. In this study, particle geometries comprised of one to four overlapping spheres were developed for shelled corn and tested. With these models, measurement of bulk properties; bulk density, angle of repose, and hopper emptying time, were simulated using EDEM® software with published data of material and interaction properties of shelled corn as model inputs. Variable inputs into the simulation modeling were material properties such as particle geometry, size distribution, Poisson’s ratio, shear modulus, and particle density, and interaction properties such as particle coefficients of restitution, static friction, and rolling friction. Although less precise in shape than multi-sphere particle geometries, single sphere particle geometry was emphasized in this research because they can markedly reduce computation times while providing accurate simulation results. Predicted results for hopper emptying time, bulk density, and angle of repose were compared to experimental results or published data to select the most appropriate material input properties for simulating bulk behavior of corn kernels in free-flowing grain applications using DEM. From the study, the most appropriate material input properties for modeling corn kernel using a single-sphere particle geometry included a particle coefficient of restitution of 0.30, particle coefficient of static friction of 0.30 for corn-corn contact, particle coefficient of static friction of 0.20 for corn-steel contact, particle coefficient of rolling friction of 0.05, normal particle size distribution with a standard deviation factor of 0.4, and particle shear modulus of 20 MPa.