CFD Simulation of Airflow Distribution in a Heat Pump-Assisted Deep-Bed Paddy Dryer

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Applied Engineering in Agriculture. 38(1): 1-8. (doi: 10.13031/aea.14483) @2022
Authors:   M. A. R. Kavindi, K. S. P. Amaratunga, E. M. A.C.. Ekanayake, A. J. Fernando, A. M. S. K. Abesinghe
Keywords:   CFD simulation, COMSOL Multiphysics, Heat pump drying.

Highlights

Uneven drying is an inevitable drawback when using heat pump-based deep-bed dryers in commercial drying industries.

Understanding the drying behavior of the heat pump-based deep-bed dryers is important to optimize the drying technology.

COMSOL Multiphysics is a very helpful tool as it can be used to predict the drying behavior.

Abstract. Heat pump dryers are widely used in drying agricultural products because of its capability in drying products at comparatively lower temperatures in commercial scale. However, deep-bed heat pump drying (HPD) leads to uneven drying because of its poor airflow distribution in the drying chamber. Optimizing the proper design of a heat pump dryer system may reduce the non-uniformity of drying and increases dryer efficiency. This study aimed to investigate the airflow distribution in a deep bed of rough rice dried with a heat pump using Computational Fluid Dynamics (CFD). The Navier-Stokes equation, Heat transfer equation, and Fick‘s Law were used in the mathematical models for simulation of air velocity, temperature, and relative humidity respectively. COMSOL Multiphysics simulation program v5.4 solved all the models with the boundary conditions of inlet velocity, inlet temperature, and drying air moisture content. The simulation was used to predict the temperature and the humidity of drying air at three different dryer locations during the drying process. Finally, the simulated data were verified using experimental results. The values of relative error and mean relative deviation for drying air temperature in paddy bed were less than ±18.05%, 13.52%. Relative error and mean relative error for air moisture in paddy bed were less than ±15.83% and 14.44%, respectively. The results indicated that the simulation model developed could effectively use for predicting the air temperature and air relative humidity with a reasonable accuracy.