ANN model to predict the performance of parabolic dish collector with tubular cavity receiver

In this study, the thermal performance of a parabolic dish concentrator with a rectangular-tubular cavity receiver was investigated. The thermal oil was used as the working fluid in the solar collector system. The performance of the cavity receiverwas studied in twoways as anumericalmodelingmethod and the artificial neural networks (ANNs) methodology. In this study, three variable parameters including the different tube diameters equal to 5, 10, 22, and 35mm, and different cavity depths equal to 0.5a, 0.75a, 1a, 1.5a, and 2a were considered. The purpose of this study is the prediction of the thermal performance of the cavity receiver in differentamounts of solar irradiance, the cavity depth, and the diameter of tube by the ANN methodology. The main benefit of the ANN method, in comparison with the numerical modeling method, is the calculation time and cost saving. The results reveal that the ANN method can accurately predict the thermal performance of the cavity receiver at different variable parameters of the cavity depth, and tube diameter with R-2-0.99 for each prediction.