Abstract
AbstractAn artificial neural network (ANN) model was developed to study the heat transfer analysis in an unglazed flat-plate solar collector with air passing behind the absorbing plate. The construction of the solar air collector included the absorber plate, the structural layer under the plate, the air channel, and the back insulation layer. The mean inside temperature at each surface of the solar collector and the heat added to the airflow were estimated by a nonlinear autoregressive exogenous (NARX) model. The obtained results were verified against the mathematical calculation that was used to find the aforementioned values by the optimization technique. It was found that the NARX model may be used to estimate the mean inside temperature at each surface of the flat-plate collector with excellent accuracy with a coefficient of determination of 0.99997. The advantages of the ANN model compared to the conventional testing methods are speed, simplicity, and the capacity of the ANN to learn from examples.
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