ANN Modeling of Forced Convection Solar Air Heater

P. T. Saravanakumar(1*), K. Mayilsamy(2), V. Boopathi Sabareesh(3)

(1) Associate Professor, Dept of Mechanical Engineering, P.A College of Engineering and Technology, Pollachi, Anna University, India
(2) Professor & Principal, Institute of Road and Transport Technology, Erode, Anna University, India
(3) Professor, Dept of Mechanical Engineering, Akshaya College of Engineering and Technology, Coimbatore, Anna University, Chennai., India
(*) Corresponding author


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Abstract


The design and applicability of solar air heating system require a satisfactory prediction of collector outlet air temperature and the useful energy delivered over a wide range of climate conditions.
The ANN modeling is extensively used for this purpose. This article presents the results of a study carried out to compare the performance prediction by ANN. In this, an ambient temperature, solar intensity and air velocity were used as input layer, while the outputs are collector outlet temperature and first and second law efficiency of the solar air heater. The back propagation learning algorithm methods were used training and test the data. Comparison between predicted and experimental results indicates that the proposed ANN model can be used for estimating some parameters of SAHs with reasonable accuracy.


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Keywords


ANN; SAH; First and Second Law Efficiency; Thermal Storage; Iron Scraps

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