Pack Factor Measurements for Corn in Grain Storage Bins

Abstract

ABSTRACT. Shelled yellow corn is commonly stored in concrete orrain stored in bins is subjected to packing from pressure caused by the overlying grain mass. Grain packing in bins is defined as the increase in grain bulk density caused by compression from the cumulative weight of the overlying grain material. Because this compression causes relatively large increases in bulk density, accurate pack factors that account for the increase are required for determining the exact amount of grain in a bin. While grain is traded on a mass basis, the vast majority of grain inventory and auditing assessments are based on volume measurements. Accurate pack factors are needed by grain elevator managers and farmers for proper inventory control, and by government agencies for auditing. Because of persistent questions about the accuracy of pack factors currently in use, the USDA Risk Management Agency (RMA) requested work to develop new, more accurate pack factors, which led to the study reported here.It is often difficult to predict how grain will compact because bulk grain consists of a complex matrix of irregularly shaped particles, each with its own characteristics. Thus, most bulk grain packing prediction models have been done empirically (Thompson et al., 1991). In powder technology, there is extensive literature on particle packing (Smalley, 1970). Although Smalley (1970) Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. The USDA is an equal opportunity provider and employer.The commonly used to describe the packing of fine powders with very regular shape and size geometry, it failed to address the situation with whole grains, where the particles are of random shape and size and are compressible.Particle packing in whole grains is believed to vary as a function of the stress variation that exists within a given material type, moisture content, and uncompressed bulk density of the material. To understand the phenomenon of grain packing, it is essential to consider the variation in bulk particle properties (such as density changes, moisture changes, compressibility, flow rate, etc.) when stored in bins. While the geometry of a bin can be measured accurately, measuring the variation in bulk material properties of the grain inside the bin can be challenging (Thompson et al., 1987). Bates (1925) was first to research packing of granular materials in storage silos containing wheat, and he proposed that the average packing of wheat was 4.85%. Bates (1925) included dimension of the bin, shape, test weight, and depth of grain in the packing of wheat calculation.The classic theory provided by Janssen (1895) for predicting pressure in grain bins given in differential form is:This equation was solved by Janssen after simplifying assumptions of constant bulk density (D), lateral to vertical pressure ratio (k), and coefficient of friction (μ), giving:where P j is the unit vertical pressure at depth ...

Correlating Bulk Density (with Dockage) and Test Weight (without Dockage) for Wheat Samples

“…However, the degree of compressibility of stored grain varies with grain type, grain properties, and the geometry of the bin in which the grain is stored. Several studies have investigated the compressibility of a variety of food crops, such as ground shelled corn, wheat, corn, soybean, corn meal, sugar beet pulp, cotton seed meal, and distillers grains without solubles (Loewer et al, 1977;Malm and Backer, 1985;Bhadra et al, 2015;Boac et al, 2015). Milani et al (2000) determined that the effects of pressure and moisture on bulk densities of soybean were independent of variety).…”

A Review of Analytical Methods for Calculating Static Pressures in Bulk Solids Storage Structures

“…The pressure field affects bulk solid's packing, flowability, porosity, and tortuosity, to name a few. For example, Janssen along with empirical packing equations has been used to predict the density change within a bin (Thompson et al, 1991;Bhadra et al, 2015Bhadra et al, , 2018Turner et al, 2016;Cheng et al, 2017).…”