Mass transfer simulation of pistachio nuts using computational fluid dynamic (CFD) during fluid bed drying

مجله پژوهشهای علوم و صنایع غذایی ایران

Volume 17, Issue 6 - Serial Number 72, January and February 2022, Pages 103-119   

Document Type: Research Article-en

DOI: 10.22067/ifstrj.2021.70119.1038

Authors

Behdad Shadidi^{* 1}; Reza Amiri Chayjan²

¹Assistant Professor, Bu-Ali Sina University, Hamedan, Iran

²Associate professor/Bu-Ali Sina University

Abstract

The drying of food can extend the shelf life of food, reduce transportation and storage costs. Fick's second law is commonly used to evaluate the mass data in the drying process in a standard way and is based on many assumptions. Understanding the meaning of mass transfer in products can improve the drying process and product quality. Computational fluid dynamics (cfd) models fluid flow situations utilizing powerful computer and applied mathematics in order to predict mass transfer in industrial processes. The aim of this research was numerical study of the drying behavior of pistachio nut using CFD method and evaluating the numerical results in the bed condition of fluid, semi fluid and fix bed as well as air temperatures of 90, 75, 60 and 45°C. During drying using computational fluid dynamic and the Fluent CFD code, the external flow and temperature fields around the cylindrical object (7.5× 10 millimeter) will be predicted in the numerical analysis.  A laboratory fluid bed dryer was used for drying experiments. The main parts of the dryer are forward radial fan, drying chamber, electrical heater, inverter, temperature controller. The dryer attachment tools are input and output temperature sensors, anemometer and computer. The numerical part was verified and juxtaposed with the experimental data. The numerical solution result at 60, 75 and 90°C were so close to experimental results except for air temperature of 45°C. Mean absolute error in fix bed, at 60, 75 and 90°C were 0.2123, 0.1257 and 0.0337 which were lower than 45°C temperature and R² values for these temperatures were 0.9903, 0.9705 and 0.9807, respectively. As the temperature decreased, the values of E_abs and X² increased in all bed conditions. The average value of R² for all applied bed conditions was 0.9850. This value showed high correlation between experimental and numerical results.

Keywords

Semi fluid bed drying; Fluid bed drying; Fix bed drying; Experimental results; Modeling; Numerical solution

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