Location:2013 Annual Report
1a. Objectives (from AD-416):
Obtain new field data to refine and calibrate a science-based model for determining the packing of grains within upright storage structures. The Cooperator will obtain field measurements of grain packing from the major grain producing regions of the U.S. with collaborators at ARS, the University of Kentucky, and the University of Georgia who will also make field measurements. Field data will be collected for wheat, corn, soybeans, grain sorghum, oats, and barley. The effect of aeration systems on packing factor will also be investigated.
1b. Approach (from AD-416):
This research is part of a larger, nationwide project to refine and validate a procedure with known accuracy, based on measurable physical parameters, for determining the packing of grains within upright storage structures. Because grain is somewhat compressible when subjected to the cumulative weight exerted from the material above, accurate packing factors are required to determine the mass of grain in storage from bin dimensions and test weights. Inventory control is critical for stored grain managers due to financial aspects (auditing by state agencies) and for the future utilization of quality management systems. The major variables affecting stored grain packing are grain type, moisture content, test weight, internal friction, and bin wall material, geometry, and dimensions. Variation across different regions of the U.S. must be investigated as well as other minor factors. A preliminary model for determining packing factors for a wide range of grains and bins is being developed at the University of Georgia that employs the differential form of Janssen’s equation to estimate the pressure and in-bin bulk density for a given depth of grain in a bin. In the larger project, this model will be calibrated and validated by measuring packing factors for selected grains in bins in all of the major grain producing regions of the U.S. As part of that nationwide effort, the Cooperator will measure packing factors in selected states west of the Mississippi River. Field measurements of packing factors will be obtained by measuring the height of grain in bins of known dimensions and wall materials as they are filled and/or discharged with a measured mass of grain.
3. Progress Report:
As part of the overall project to improve predictions of stored grain packing factors, existing compaction levels are being measured in the field for numerous bin sizes and types on farms and at grain elevators around the U.S. To date more than 150 bins (including both concrete and corrugated steel) have been measured across the U.S. for determining packing factor. Measurements in the fall of 2012 concentrated on corn and soybean bins with over 60 bins containing these two crops now measured. Other crops were also measured and another 40 bins containing oats, grain sorghum, and barley have been measured to determine packing factor. Measurements of bins with hard red winter (HRW) wheat are largely complete with about 60 bins measured. HRW wheat packing was measured in corrugated steel bins with diameters ranging from 4.6 to 32 m and eave heights ranging from 3 to 27 m and in concrete bins with diameters ranging from 4.6 to 10.3 m and eave heights ranging from 26 to 42 m. The maximum and median differences between the model-predicted mass and scale-measured mass were -4.2% and -1.1%, respectively, for corrugated steel bins, -8% and -0.54% for reinforced concrete bins with hopper bottoms, and 10% and 1.6% for reinforced concrete bins with off-center, side-discharge hopper bottoms (chute-bottoms). In most cases, the model under-predicted the mass with the exception of a single set of chute-bottom bins with chute angle, 34 degrees. Comparison of the difference between predictions of the old method and the scale-measured mass had a maximum value of -22.8%, with a mean absolute difference of 5.61% for all types of bins, indicating that that the new model predicted packing factor better than the old method for HRW wheat. This extensive field data is contributing to a greater understanding stored grain packing factors and should provide greater confidence in the packing factor predictions being developed compared to the old packing factor predictions.