Modelling of Solar Dryers for Corn
Grain drying is an important factor that help prevent postharvest losses. The adoption of large-scale electric or gas-powered dryers is challenging in developing countries. Solar dryers have been proposed as an economic alternative, which provide benefits over open sun drying which is common in developing countries. However, predicting solar dryer performance under different climates or to dry different grains is challenging. Optimizing design requires repeatable full-scale tests, which will be expensive and time consuming. In this work, the corn drying process, in three types of solar dryers, was mathematically modeled and simulated using computational fluid dynamics (CFD) approach. The dryers studied were a natural convection cabinet dryer, a natural convection greenhouse dryer, and a forced convection solar bubble dryer. The developed models accounted for the spectral and directional nature of sunlight, and the direct absorption of radiation by the corn. Simulation results were used to visualize the temperature, humidity, and velocity distributions inside the dryers. The predicted temperature and humidity profiles were validated with experimental data collected in Ghana. Based on the simulation results, dryer modifications were proposed that could improve their performance. In the case of the cabinet dryer, the proposed design modification was simulated and the predicted drying rate increased by 11% from the original design.
Kingsly Ambrose, Purdue University.
Off-Campus Purdue Users:
To access this dissertation, please log in to our