Performance assessment of a antural convection solar tunnel dryer through experimentation and CFD simulation of temperature and airflow

Natural-convection solar tunnel dryers capable of achieving greater drying rates when drying products. The increased temperature decreases the relative humidity of the air, thereby allowing the air to more efficiently dry the product. However, it is necessary to provide an appropriate solar air heater in order to achieve the required drying air temperature distribution for improved performance of such a dryer. In order to predict variation of moisture content with time during the drying process, it is necessary to have an appropriate drying model. The purpose of this study was to investigate the performance of dryer and apply Computational Fluid Dynamics simulations in visualizing the air flow and temperature. In this study experiments were carried out at the University of Zambia, Department of Agricultural Engineering under natural conditions. Simulations of temperature and air flow within the model of the dryer were done and the results showed average air temperature of up to 70℃ was attained at the drying unit. The average air temperature obtained in the process of the Computational Fluid Dynamics (CFD) simulation was in agreement with the experimental temperature for drying the banana slices with an error of 5.1%. The dryer model describes the transfer process and flow field pattern of air in the tunnel dryer and predicts the instantaneous temperature, air velocity, pressure field pattern at any location of the dryer with emphasis on the collector, drying unit and chimney. From the simulations it was observed that the increasing the collector length from 1.5 to 2 m had a collector temperature percentage increment of 8.98%. The simulation results shows that temperature obtained inside the chamber increases with increase in exposed surface area of collector. A mass of 0.943 kg of banana slices were dried from an initial moisture content of 73.89% (w.b.) to 4.39% (w.b.) in 13 hours. The performance of the dryer was analysed by calculating the collector and drying chamber efficiencies. The efficiencies were found to be 33.09% and 13.5% for the collector and drying chamber, respectively. To find an appropriate thin layer model, 11 thin layer models from literature were analysed using Matlab R2018A curve fitting tool and the best model was determined based on three statistical parameters: coefficient of determination (�� 2 ), Sum of Square Error (������) and Root Mean Square Error (��������). Among the 11 thin layer mathematical models which were established to help predict the drying of banana slices, the Midilli et al and Page models provided excellent fits to the experimental vi data with a value of �� 2 of 0.9990 and 0.9933, respectively. The values of ������ and �������� obtained from both models were less than 0.008335 and 0.02753, respectively. This research also presents an energy and exergy analysis of the solar drying process. From the energy and exergy analysis, the average collector efficiency during the experiment was 33.09 % while the average collector exergy and drying chamber efficiencies were 1.91 % and 63.20%, respectively. On the basis of temperatures obtained from the simulation and experiment results, the drying time achieved for 3 mm banana slices and the collector efficiencies, the dryer performed well. Cost based optimization of the dryer is recommended for further study. Keywords CFD simulation, Temperature and air flow, Natural convection, Solar tunnel dryer, Chimney