International Journal of Research and Innovation in Applied Science (IJRIAS) |Volume VII, Issue IX, September 2022|ISSN 2454-6194
Computer Simulation of Airflow Distribution in a Heat Pump Dryer
Kavindi M. A. R.1*, Amaratunga K.S.P.1, Ekanayake E.M.A.C2
1Department of Agricultural Engineering, Faculty of Agriculture, University of Peradeniya, Sri Lanka.
2Postgraduate Institute of Agriculture, University of Peradeniya, Sri Lanka.
Abstract: Computer simulation is an effective technique for better understanding the physical phenomena of drying. Understanding and predicting the drying behavior before applying the material would increase the dryer efficiency by properly designing existing heat pump dryer systems. This study was done to simulate the airflow in a heat pump dryer chamber using Computational Fluid Dynamics (CFD). COMSOL Multiphysics software v5.4 has been used for simulation. Air velocity, temperature, and relative humidity distribution profile were achieved by solving the Naiver stoke fluid equation, Heat transfer equation, and Transport of diluted species equation (Fick’s law). The simulated data for nine different locations were verified using experimental results. The relative error and mean relative deviation for temperature profile were less than ±1.8% and 7.8%. It was recorded less than ±2.8% and 10.6% values for the relative error and mean relative deviation for relative humidity profiles. Therefore, this would be a suitable prediction method to understand the airflow pattern and conditions inside a chamber
Keywords: COMSOL Multiphysics, Computational Fluid Dynamics (CFD), Computer Simulation, Heat Pump Dryings
I. INTRODUCTION
Even though drying is very essential operation in food industries, it consumes large amounts of energy and time. Any improvement in the existing dryer design will reduce the cost and energy, improve the quality of dried products, and be beneficial for the industry. The development of a heat pump dryer is advantageous due to it provide huge savings for industry. Researchers have proven that compare to other drying methods, it facilitates higher energy efficiency, better product quality, the ability to operate independently of outside ambient weather conditions, environmentally friendly drying condition [7, 9, 15, 21, 24]. In the drying process, drying air temperature, humidity, and velocity are the main factors that affect the product’s drying rate [8, 19].
In deep bed dryers, heat and mass transfer phenomena involve over-drying in the lower zone and under-drying in the upper zone [22]. Therefore, in designing suitable geometric configurations of the drying chamber, predicting the airflow velocity, temperature, and relative humidity inside the dryer helps to optimize the design and improve the drying process before the actual dryer is built [19]. Mathematical modelling has been used to model the airflow behavior inside several kinds of dryers [4, 11, 16]. However, Mathematical modelling is complicated process and need a developed technology to solve the complex formulations.