Josephine M. Boac

Applications of Discrete Element Method in Modeling of Grain Postharvest Operations

Grain kernels are finite and discrete materials. Although flowing grain can behave like a continuum fluid at times, the discontinuous behavior exhibited by grain kernels cannot be simulated solely with conventional continuum-based computer modeling such as finite-element or finite-difference methods. The discrete element method (DEM) is a proven numerical method that can model discrete particles like grain kernels by tracking the motion of individual particles. DEM has been used extensively in the field of rock mechanics. Its application is gaining popularity in grain postharvest operations, but it has not been applied widely. This paper reviews existing applications of DEM in grain postharvest operations. Published literature that uses DEM to simulate postharvest processing is reviewed, as are applications in handling and processing of grain such as soybean, corn, wheat, rice, rapeseed, and the grain coproduct distillers dried grains with solubles (DDGS). Simulations of grain drying that involve particles in both free-flowing and confined-flow conditions are also included. Review of the existing literature indicates that DEM is a promising approach in the study of the behavior of deformable soft particulates such as grain and coproducts, and it could benefit from the development of improved particle models for these complex-shaped particles.

Size distribution and rate of dust generated during grain elevator handling

Dust generated during grain handling can pose a safety and health hazard and is an air pollutant. This study was conducted to characterize the particle size distribution (PSD) of dust generated during handling of wheat and shelled corn in the research elevator of the USDA Grain Marketing and Production Research Center and determine the effects of grain lot, repeated transfer, and grain types on the PSD. Dust samples were collected on glass fiber filters with high volume samplers from the lower and upper ducts upstream of the cyclone dust collectors. A laser diffraction analyzer was used to measure the PSD of the collected dust. For wheat, the size distribution of dust from the upper and lower ducts showed similar trends among grain lots but differed between the two ducts. The percentages of particulate matter (PM)-2.5, PM-4, and PM-10 were 5.19%, 9.81%, and 34.1% of the total wheat dust, respectively. The total dust mass flow rate was 0.94 g/s (equivalent to 64.6 g/t of wheat handled). For shelled corn, the size distributions of the dust samples from the upper and lower ducts also showed similar trends among transfers but differed between the two ducts. The percentages of PM-2.5, PM-4, and PM-10 were 7.45%, 9.98%, and 28.8% of the total shelled corn dust, respectively. The total dust mass flow rate was 2.91 g/s (equivalent to 185.1 g/t of corn handled). Overall, the corn and wheat differed significantly in the size distribution and the rate of total dust generated.

3-D and quasi-2-D discrete element modeling of grain commingling in a bucket elevator boot system

Unwanted grain commingling impedes new quality-based grain handling systems and has proven to be an expensive and time-consuming issue to study experimentally. Experimentally validated models may reduce the time and expense of studying grain commingling while providing additional insight into details of the particle flow. In this study, grain commingling in a pilot-scale bucket elevator boot was first modeled in three-dimensional (3-D) discrete element method (DEM) simulations. Experiments on the pilot-scale boot were performed using red-dyed and clear (uncolored) soybeans to validate the 3-D DEM model. Predicted results from the 3-D boot model generally followed the experimental data but tended to underpredict commingling early in the process. To reduce computational time, quasi-two-dimensional (quasi-2-D) DEM simulations were also evaluated. Comparison of predicted average commingling of five quasi-2-D boot models with reduced control volumes (i.e., with boot widths from four to seven times the mean particle diameter) led to the selection of the quasi-2-D model with a boot width of 5.6 times the mean particle diameter (i.e., 5.6d) to reduce computational time. In addition, the 3-D and quasi-2-D (5.6d) models were refined by accounting for the initial surge of particles at the beginning of each test and correcting for the effective dynamic gap between the bucket cups and the boot wall. The quasi-2-D (5.6d) models reduced simulation run time by approximately 70% compared to the 3-D model of the pilot-scale boot. Results of this study can be used to accurately predict commingling levels and improve grain handling, which can help farmers and grain handlers reduce costs and maintain grain purity during transport and export of grain.

Material and Interaction Properties of Selected Grains and Oilseeds for Modeling Discrete Particles

Experimental investigations of grain flow can be expensive and time consuming, but computer simulations can reduce the large effort required to evaluate the flow of grain in handling operations. Published data on material and interaction properties of selected grains and oilseeds relevant to discrete element method (DEM) modeling were reviewed. Material properties include grain kernel shape, size, and distribution; Poisson’s ratio; shear modulus; and density. Interaction properties consist of coefficients of restitution, static friction, and rolling friction. Soybeans were selected as the test material for DEM simulations to validate the model fundamentals using material and interaction properties. Single- and multi-sphere soybean particle shapes, comprised of one to four overlapping spheres, were compared based on DEM simulations of bulk properties (bulk density and angle of repose). A single-sphere particle model best simulated soybean kernels in the bulk property tests. The best particle model had a particle coefficient of restitution of 0.6; particle static friction of 0.45 for soybean-soybean contact (0.30 for soybean-steel interaction); particle rolling friction of 0.05; normal particle size distribution with standard deviation factor of 0.4; and particle shear modulus of 1.04 MPa.

3-D and Quasi-2-D Discrete Element Modeling of Grain Commingling in a Bucket Elevator Boot System

Unwanted grain commingling impedes new quality-based grain handling systems and has proven to be an expensive and time consuming issue to study experimentally. Experimentally validated models may reduce the time and expense of studying grain commingling while providing additional insight into details of the particle flow. In this study, grain commingling in a pilot-scale bucket elevator boot was first modeled in three-dimensional (3-D) discrete element method (DEM) simulations. Experiments on the pilot-scale boot were performed using red and clear soybeans to validate the 3-D DEM model. Predicted results from the 3-D boot model generally followed the experimental data but tended to under predict commingling early in the process. To reduce computational time, quasi-two-dimensional (quasi-2-D) DEM simulations were also evaluated. Comparison of predicted average commingling of five quasi-2-D boot models with reduced control volumes (i.e., with boot widths from four to seven times the mean particle diameter) led to the selection of the quasi-2-D model with boot width of 5.6 times the mean particle diameter (i.e., 5.6d) to reduce computation time. In addition, the 3-D and quasi-2-D (5.6d) models were refined by accounting for the initial surge of particles at the beginning of each test and correcting for the effective dynamic gap between the bucket cups and the boot wall. The quasi-2-D (5.6d) models reduced simulation run time by approximately 70% compared to the 3-D model of the pilot-scale boot. Results of this study will be used to accurately predict impurity levels and improve grain handling, which can help farmers and grain handlers reduce costs and maintain grain purity during transport and export of grain.

Feed pellet and corn durability and breakage during repeated elevator handling

Pelleting of animal feeds is important for improved feeding efficiency and for convenience of handling. Pellet quality impacts the feeding benefits for the animals and pellet integrity during handling. To compare the effect of repeated handling on the quality of feed pellets and corn, a 22.6-t (1000-bu) lot of feed pellets made from corn meal and a 25.4-t (1000-bu) lot of shelled corn, were each transferred alternately between two storage bins in the USDA-ARS, Grain Marketing and Production Research Center research elevator at Manhattan, Kansas, at an average flow rate of 59.4 t/h. Samples from a diverter-type sampler were analyzed for particle size distribution (by sieving) and durability (by the tumbling box method). The apparent geometric mean diameter of pellet samples decreased with repeated transfers, whereas the mass of accumulated broken pellets increased with repeated transfers. The percentage of broken pellets increased by an average of 3.83% with each transfer from an initial value of 17.5%, which was significantly different from the values obtained from shelled corn (p 0.05) during the transfers. The durability index of shelled corn was also not significantly different during the transfers. Analysis of dust removed by the cyclone separators showed that the mass of dust < 0.125 mm was significantly less for feed pellets (0.337 kg/t of pellet mass) than for shelled corn (0.403 kg/t of corn mass).