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)

Wheat Mill Stream Properties for Discrete Element Method Modeling

A discrete phase approach based on individual wheat kernel characteristics is needed to overcome the limitations of previous statistical models and accurately predict the milling behavior of wheat. As a first step to develop a discrete element method (DEM) model for the wheat milling process, this study determined the physical and mechanical properties of wheat mill streams (wheat kernels, break stream, and wheat flour) required as input parameters. The parameters measured were particle size and size distribution, bulk density, Young’s modulus, static and rolling coefficients of friction, and coefficient of restitution. The effect of moisture content (12% to 16% wet basis) on these properties was evaluated. The density, Young’s modulus, and coefficient of restitution tended to decrease while the coefficients of friction tended to increase with increasing moisture content of wheat kernels. The effect of moisture content on material properties was significant for break stream, but there was no significant (p > 0.05) material property change with moisture content for flour. It was concluded that moisture content had a greater significant effect on physical properties (bulk, true, and tapped densities and particle size) of the mill streams than it did on the mechanical properties (Young’s modulus, coefficients of static and rolling friction, and coefficient of restitution)

Optimization and Modeling of Flow Characteristics of Low-Oil DDGS Using Regression Techniques

Citation: R. Bhadra, R. P. K. Ambrose, M. E. Casada, S. Simsek, K. Siliveru. (2017). Optimization and Modeling of Flow Characteristics of Low-Oil DDGS Using Regression Techniques. Transactions of the ASABE. 60(1): 249-258. (doi: 10.13031/trans.11928)Storage conditions, such as temperature, relative humidity (RH), consolidation pressure (CP), and time, affect the flow behavior of bulk solids such as distillers dried grains with solubles (DDGS), which is widely used as animal feed by the U.S. cattle and swine industries. The typical dry-grind DDGS production process in most corn ethanol plants has been adapted to facilitate oil extraction from DDGS for increased profits, resulting in production of low-oil DDGS. Many studies have shown that caking, and thus flow, of regular DDGS is an issue during handling and transportation. This study measured the dynamic flow properties of low-oil DDGS. Flow properties such as stability index (SI), basic flow energy (BFE), flow rate index (FRI), cohesion, Jenike flow index, and wall friction angle were measured at varying temperature (20°C, 40°C, 60°C), RH (40%, 60%, 80%), moisture content (MC; 8%, 10%, 12% w.b.), CP (generated by 0, 10, and 20 kg overbearing loads), and consolidation time (CT; 2, 4, 6, 8 days) for low-oil DDGS. Response surface modeling (RSM) and multivariate analysis showed that MC, temperature, and RH were the most influential variables on flow properties. The dynamic flow properties as influenced by environmental conditions were modeled using the RSM technique. Partial least squares regression yielded models with R2 values greater than 0.80 for SI, BFE, and cohesion as a function of MC, temperature, RH, CP, and CT using two principal components. These results provide critical information for quantifying and predicting the flow behavior of low-oil DDGS during commercial handling and transportation

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 bulk angle of repose) and computation time. 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 coefficient of static friction of 0.45 for soybean‐soybean contact (0.30 for soybean‐steel interaction), particle coefficient of rolling friction of 0.05, normal particle size distribution with standard deviation factor of 0.4, and particle shear modulus of 1.04 MPa

Field-Observed Angles of Repose for Stored Grain in the United States

Citation: Bhadra et al. (2016). Field-Observed Angles of Repose for Stored Grain in the United States. Applied Engineering in Agriculture, 33(1), 131-137. Doi:10.13031/aea.11894Bulk grain angle of repose (AoR) is a key parameter for inventorying grain, predicting flow characteristics, and designing bins and grain handling systems. The AoR is defined for two cases, piling (dynamic) or emptying (static), and usually varies with grain type. The objective of this study was to measure piling angles of repose for corn, sorghum, barley, soybeans, oats, and hard red winter (HRW) wheat in steel and concrete bins in the United States. Angles were measured in 182 bins and 7 outdoor piles. The piling AoR for corn ranged from 15.7° to 30.2° (median of 20.4° and standard deviation of 3.8°). Sorghum, barley, soybeans, oats, and HRW wheat also exhibited a range of AoR with median values of 24.6°, 21.0°, 23.9°, 25.7°, and 22.2°, respectively. Angles of repose measured for the seven outdoor piles were within the ranges measured for the grain bins. No significant correlation was observed between AoR and moisture content within the narrow range of observed moisture contents, unlike previous literature based on laboratory measurement of grain samples with wider ranges of moisture content. Overall, the average measured piling AoR were lower than typical values cited in MWPS-29, but higher than some laboratory measurements

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 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 5.15%, 9.65%, and 33.6% 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 7.46%, 9.99%, and 28.9% 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

Influence of Kernel Shape and Size on the Packing Ratio and Compressibility of Hard Red Winter Wheat

Grain compaction occurs during bin storage, and its determination is important for the grain mass estimation needed for inventory and auditing. The degree of compaction is dependent on grain type, bin type, moisture content, amount of grain, initial grain bulk density, coefficients of friction, lateral-to-vertical pressure coefficient, and variation in kernel size. Previous studies have correlated several of these parameters, such as bulk density and grain packing, with moisture content. This study investigated the influence of wheat kernel shape and size distribution on packing ratio and compressibility. Two dockage-free hard red winter (HRW) wheat samples, with no shrunken or broken kernels, were sieved using U.S. Tyler sieves #6, #7, #8, and #10, and the kernels retained on the sieves were used in the experiments. The kernel dimensional parameters and bulk sample parameters were measured, and additional derived parameters were calculated for each size fraction and variety. Packing ratio and compressibility of the size fractions and of binary and ternary mixtures of the size fractions were also determined for each variety. Packing ratio increased with larger kernel size, while compressibility decreased. Sphericity and flatness shape factor had strong positive linear relationships with packing ratio and strong negative relationships with compressibility, while elongation shape factor behaved the opposite way with packing ratio and compressibility. The higher the percentage mass of the larger kernel fraction in a mixture, the higher was its packing ratio and the lower its compressibility. The two tested varieties of wheat did not significantly differ in packing ratio and compressibility. These findings can be used in developing models for more accurate estimation of grain pack factor and to determine the mass of grain inside bins and other storage structures

Influence of Kernel Shape and Size on the Packing Ratio and Compressibility of Hard Red Winter Wheat

Grain compaction occurs during bin storage, and its determination is important for the grain mass estimation needed for inventory and auditing. The degree of compaction is dependent on grain type, bin type, moisture content, amount of grain, initial grain bulk density, coefficients of friction, lateral-to-vertical pressure coefficient, and variation in kernel size. Previous studies have correlated several of these parameters, such as bulk density and grain packing, with moisture content. This study investigated the influence of wheat kernel shape and size distribution on packing ratio and compressibility. Two dockage-free hard red winter (HRW) wheat samples, with no shrunken or broken kernels, were sieved using U.S. Tyler sieves #6, #7, #8, and #10, and the kernels retained on the sieves were used in the experiments. The kernel dimensional parameters and bulk sample parameters were measured, and additional derived parameters were calculated for each size fraction and variety. Packing ratio and compressibility of the size fractions and of binary and ternary mixtures of the size fractions were also determined for each variety. Packing ratio increased with larger kernel size, while compressibility decreased. Sphericity and flatness shape factor had strong positive linear relationships with packing ratio and strong negative relationships with compressibility, while elongation shape factor behaved the opposite way with packing ratio and compressibility. The higher the percentage mass of the larger kernel fraction in a mixture, the higher was its packing ratio and the lower its compressibility. The two tested varieties of wheat did not significantly differ in packing ratio and compressibility. These findings can be used in developing models for more accurate estimation of grain pack factor and to determine the mass of grain inside bins and other storage structures

Stored Grain Pack Factors for Wheat: Comparison of Three Methods to Field Measurements

Storing grain in bulk storage units results in grain packing from overbearing pressure, which increases grain bulk density and storage unit capacity. This study compared pack factors of hard red winter (HRW) wheat in vertical storage bins using different methods: the existing packing model (WPACKING), the USDA Risk Management Agency (RMA) method, and the USDA Farm Service Agency Warehouse Licensing and Examination Division (FSA-W) method. Grain bins containing HRW wheat were measured in Kansas, Oklahoma, and Texas. Packing was measured in corrugated steel bins and reinforced concrete bins with diameters ranging from 4.6 to 31.9 m (15.0 to 104.6 ft) and equivalent level grain heights ranging from 4.1 to 41.6 m (13.4 to 136.6 ft). The predicted masses of compacted stored wheat based on WPACKING, RMA, and FSA-W were compared to the reported mass from scale tickets. Pack factors predicted by WPACKING ranged from 0.929 to 1.073 for steel bins and from 0.986 to 1.077 for concrete bins. Pack factors predicted by the RMA method ranged from 0.991 to 1.157 for steel bins and from 0.993 to 1.099 for concrete bins. Pack factors predicted by the FSA-W method ranged from 0.985 to 1.126 for steel bins and from 1.012 to 1.101 for concrete bins. The average absolute and median differences between the WPACKING-predicted mass and reported mass were 1.64% and -1.26%, respectively, for corrugated steel bins and 3.75% and 2.16%, respectively, for concrete bins. In most cases, WPACKING underpredicted the mass in corrugated steel bins and overpredicted the mass in concrete bins. Comparison of the RMA-predicted mass and reported mass showed an average absolute difference of 4.41% with a median difference of 1.91% for HRW wheat in steel bins and an average absolute difference of 3.25% with a median difference of 1.03% for concrete bins. For the FSA-W-predicted mass versus reported mass, the average absolute and median differences were 3.40% and 3.86%, respectively, for steel bins and 4.34% and 3.50%, respectively, for concrete bins. Most of the mass values were overpredicted by both the RMA and FSA-W methods. Some of the large differences observed for concrete bins can be attributed to the unique geometry of these bins and the difficulty in describing these bin shapes mathematically. Overall, compared to the reported mass, WPACKING predicted the mass of grain in the bins with less error than the current RMA and FSA-W methods. Some of the differences may be because the RMA and FSA-W methods do not include the effects of grain moisture content, bin wall type, and grain height on pack factors