Detailed analysis of mass transfer in solar food dryer with different methods

Abstract

In this study, the mass transfer, effective diffusion coefficient (Deff), activation energy (Ea), and drying efficiency values of the product dried in the solar food drying system were experimentally investigated. It was determined that Deff values, Ea values, and drying efficiency values calculated with experimental data varied between 0.15 x 10(-10) -0.1 x 10(-10) m(2)/s, between 21.6 and 15.9 kJ/mol, and between 51.8% and 15.9%, respectively. Mass transfer values in the drying system are modeled in detail with four different methods such as numerical analysis method (CFD), machine learning algorithms (ANN, SVM) and drying kinetics mathematical models (Newton, Page, Midilli and Kucuk, Thompson). The root means square error (RMSE) error analysis method was used to determine the validation of the models. For mass transfer studies, the moisture content (MR) values of the 10 mm thick product were taken into account. The novelty of this study is that mass transfer, which is an important parameter for drying system design and product selection, is expressed by mathematical empirical equations, artificial intelligence methods, and numerical analysis methods. The mass transfer of the product is shown by numerical analysis simulation with moisture contours. The method that models the MR values with the least error (0.01 RMSE) is the SVM algorithm.