Optimization of Evaporative Cooling Chamber using Computational Fluid Dynamics for Storage of Fruits and Vegetables

Abstract

The rise in global temperature is affecting almost all fabrics of our society, including food security. Increase in average temperature leads to a corresponding decrease in relative humidity that affects quality and shelf life of fruits and vegetables (F&V). In Kenya, about 25-45% of total production of fruits and vegetables are wasted because of inappropriate storage facilities. This is particularly alarming amongst rural farmers. In recent years, charcoal cooling has offered hope in Kenya for storage of F&V, but is a major of Greenhouse Gas Emissions. The primary objective of this study was to evaluate the performance of the pumice evaporative cooling chamber (ECC) with energy savings and thermal control and to develop Computational Fluid Dynamics (CFD) model to predict storage temperature. Pumice evaporative cooling chamber of 14.58 m2 capacity with convective and evapotranspiration support, powered by solar energy was designed and constructed at Jomo Kenyatta University of Agriculture and Technology (JKUAT) for the study. Temperature, relative humidity, solar radiation, and wind speed were measured for natural convection cooling, force convection cooling, evaporative cooling, evapotranspiration cooling, and combined cooling system. The data evaporative cooling was usedto develop a CFD model to predict storage temperature. The cooling chamber operated on principle of evaporation to lower temperature and increased relative humidity. It was tested and evaluated under no load condition. The three-dimensional CFD geometry was developed and used to simulate the cooling chamber with the Shear-Stress Transport (SST) k-omega model. The result was compared to experimental data and the model optimized using a single variable optimization method. The mass flow rate was optimized for maximum thermal performance and the optimum point was used to investigate optimal pad thickness. xxx The study showed that with no artificial influence on the cooler, the difference between ambient and storage temperature was 11.47 ᴼC, ambient and storage relative humidity was 42.44%. The cooling pad was 83% effective. With convective cooling, the difference between ambient and storage temperature was 11.77 ᴼC, relative humidity increased by 44.18%, and 85% efficient. The ambient and storage temperature difference was 13.64 ᴼC, humidity increases by 64.44%, and 98.6% efficient for evaporative cooling. The ambient and storage temperature difference was 13.04 ᴼC, humidity increases by 64.44%, and 94% efficient for evapotranspiration cooling. The ambient and storage temperature difference was 13.74 ᴼC, humidity increases by 65.61%, and 99% efficient for combined cooling system. The Computational Fluid Dynamics predicted result was compare against experimental data with a 98% confidence for evaporative cooling. The pad thickness of 200 mm was chosen for the optimized model with 5% standard deviation at optimum water flow rate of 0.105 m3/hr. The study provided useful guidelines for the design of evaporative cooling system with efficient energy savings for storage of F&V. If the use of this technology is adopted at a national level, it has the potential to increased shelf life, food availability, and farmer’s earnings.