Numerical techniques for evaluating the performance of solar drying systems

This chapter mainly describes the various numerical methods that can be used for performance evaluation of the solar drying system. The numerical techniques help to develop solar dryers to increase drying effectiveness and analyses, and they forecast the performance of dissimilar types of solar dryers. The numerical analysis is essential for forecasting the relevant parameters, which are highly required in a solar drying system. Computational fluid dynamics (CFD) can be used to analyze and investigate the heat and mass transfer inside the solar dryer. An adaptive-network-based fuzzy inference system (ANFIS) is able to predict the performance of the solar drying system. The artificial neural network can be applied to estimate the quantity of the dehydrated product. Fuzzy logic is an essential tool for precisely forecasting the results with the least inaccuracy.\u3cbr/\u3e\u3cbr/\u3eThe numerical techniques are applied for testing the drying behavior of products in the laboratory as well as on a commercial level. These techniques are beginning to act as an effective tool for researchers and scientists, who play a vital role in saving time and money without conducting any experiments for the same purpose. Thus, the numerical analysis not only results in reduced time, but also lowers the capital cost of a solar dryer. Before the production of a solar drying system, numerical analysis is essential because it gives very supportive information regarding the design and construction of a solar drying system