Effect of Temperature Sensor Numbers and Placement on Aeration Cooling of a Stored Grain Mass Using a 3D Finite Element Model

Benjamin Plumier and Dirk Maier
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Benjamin Plumier: USDA ARS NCAUR, 1815 N University St., Peoria, IL 61604, USA
Dirk Maier: Department of Agricultural and Biosystems Engineering, Iowa State University, 3325 Elings605 Bissell Rd., Ames, IA 50011, USA

Agriculture, 2021, vol. 11, issue 3, 1-14

Abstract: Grain stored in silos in the United States of America is generally cooled with an aeration system to limit mold spoilage and insect infestation. Monitoring efficacy of aeration and real-time conditions of stored grain is generally done using temperature cables with fixed-spaced sensor locations that are hung from the roof of the silo. Numerous placement options exist in terms of the number of cables and their positions. However, little investigation has been done into the effects of cable placement on aeration system operation decisions and real-time monitoring of stored grain conditions. For a one-year period, the temperatures predicted by sensors in three recommended temperature cable configurations were evaluated for conditions in Ames, IA, USA. The average temperatures of each of the cable sensor configurations were lower than the average temperatures of the entire silo, with as much as an 11.4 °C difference. When sensor locations were used as inputs for aeration control, all cable sensor configurations predicted similar average temperatures. However, the temperature averages varied by as much as 3.6 °C depending on the temperature cable distribution chosen. Results demonstrated that temperature cables near the center or near the edges of the silos produce results that are not representative of the grain mass, resulting in less efficient aerations. Simulations were also conducted with randomized horizontal “wireless” sensor locations at fixed grain depths. The average temperatures were similar, but an increase in the number of sensors reduced variability between simulated storage years as the number of randomized sensors increased.

Keywords: aeration; finite element modeling; stored products; temperature sensors (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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