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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality Safety and Assessment Research » Research » Publications at this Location » Publication #385340

Research Project: Assessment of Quality Attributes of Poultry Products, Grain, Seed, Nuts, and Feed

Location: Quality Safety and Assessment Research

Title: Modeling Heat and Mass Transfer Within an Eighth-scale Grain Drying System

Author
item Lewis, Micah
item Trabelsi, Samir

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 3/21/2021
Publication Date: 7/12/2021
Citation: Lewis, M.A., Trabelsi, S. 2021. Modeling Heat and Mass Transfer Within an Eighth-scale Grain Drying System. ASABE Annual International Meeting. https://doi.org/10.13031/aim.202101181.
DOI: https://doi.org/10.13031/aim.202101181

Interpretive Summary: An eighth-scale grain drying system using a microwave moisture sensor, developed within USDA, was developed to observe the drying process of cereal grain and oilseed products. The drying system utilizes 8 temperature sensors, 4 relative humidity sensors, and a microwave moisture sensor to measure parameters in real-time during the drying process. For experimentation within the laboratory, the eighth-scale drying bin was filled with corn to a depth of 60 cm. Temperature was measured at the 5-, 15-, 30-, 45-, and 55-cm heights; relative humidity was measured at the 15- and 45-cm heights, and moisture content was measured at the 30-cm height. The empirical data gathered from laboratory tests was used to understand the drying of the bed from bottom to top as heated air was forced through it. To further understand the heat and mass transfer that occurs during drying, the process was modeled using numerical simulation. Heat transfer principles were used to simulate the changes in heat and moisture throughout the bed. The bed of corn was divided into six 10-cm layers to better apply the modeling. The changes in grain temperature, moisture content, humidity, and air within the corn were simulated for each layer over time using the finite difference method. Results from the numerical simulation compared well with the empirical data, having low error. The average error between moisture content predicted in the simulation and measured empirically was 0.42%. The maximum error observed was 0.87%. The drying simulation will be a great tool to further analyze the drying process for various agricultural commodities.

Technical Abstract: An eighth-scale grain drying system was developed with the capability of monitoring moisture content, temperature, and relative humidity at different levels within the bed of grain or seed in real-time throughout the drying process. Empirical data have been used to observe the drying front as it traverses the bed during the drying process. To further analyze the complex transport phenomenon that occurs during drying, the transfer of heat and mass were modeled. Thermodynamic and convective-heat-transfer principles were used to simulate the changes in heat and moisture throughout the bed during drying. The transfer of both entities occurs simultaneously and is influenced by parameters such as inlet air temperature, air velocity and initial grain moisture content. Values for such parameters were obtained from experiments within the laboratory. The deep bed was divided into smaller layers, and the changes in grain temperature, moisture content, humidity, and interstitial air were simulated for each layer over time using the finite difference method. Model predictions were compared to empirical data obtained from the microwave moisture sensor, 8 temperature sensors, and 4 relative humidity sensors while corn dried within the eighth-scale grain drying system. Moisture content determined using the microwave moisture sensor had a standard error of performance (SEP) = 0.55% moisture content when compared to the reference oven drying method. Results from the numerical simulation compared well with the empirical data, having low error. The average error between moisture content predicted in the simulation and measured empirically was 0.42%. The maximum error observed was 0.87%.