Mathematical modeling of an innovative hybrid solar-gas dryer

Abstract

This paper is devoted to develop a multivariable model (MM) of an innovative hybrid solar-gas dryer issued from a CFD study. The proposed (MM) was explored to predict the drying chamber temperature in forced convection (0.025kg/s) in two main operating modes (solar mode and gas mode). There is an indirect heating of drying air instead of direct heating inside the drying chamber as it was reported in conventional hybrid solar-gas dryers. CFD technique was used to simulate the temperature and airflow distribution inside the drying chamber. However, CFD simulation requires huge capacity of the processor for calculating and takes significant simulation time. Therefore, the multivariable model was developed to predict the drying temperature instantly with a notable reduction in simulation time. Root Mean Square (RMSE) was used to measure the difference between the predicted values by CFD and (MM) model. It was found that the results shown fairly good agreement with an RMSE lower than 2.35 confirming the pertinence of the proposed model. The developed model led to a quick output parameters estimation related to each climatic condition. Thus, it is very useful for synthesizing a control system of the temperature as well as the optimization of gas consumption.

Keywords

• Renewable energy,Hybrid solar-gas dryer,Least squares methods,CFD,Drying temperature

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