Applications of Soft Computing in Solar Drying Systems

In the present scenario, the use of renewable energy is gaining more importance due to environmental degradation and limited energy resources of fossil fuel. However, solar energy is noncontinual, but it is eco-friendly, which is freely available throughout the world. In terms of energy and food security, the solar dryer is vital for reduction of postharvest food losses and electric energy consumption. The drying process of crop involves a complex analysis of heat and mass transfer parameters. In order to address this complex phenomenon, soft computing is important to analyse the drying models which in turn are useful to assess the dryer performance. It is also very helpful in predicting the crop temperature, rate of moisture evaporation, drying efficiency and dried product quality. For prediction of surrounding air temperature and quantity of evaporated moisture, the mathematical models are generated with the help of MATLAB and FORTRAN which are proved to be highly reliable in such scenario. COMSOL Multiphysics, TRNSYS, MATLAB, FORTRAN, CFD Fluent, etc. are employed for model testing and training purposes. Statistical software such as SPSS, Statistica, etc. are very useful tool for statistical data analysis. This chapter comprises different types of software and their application in designing and usage in solar dryers. This comprehensive and extensive analysis of different software will be very useful to the research community, academicians and solar dryer designers.