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Experimental study for predicting the specific heat of water based Cu-Al2O3 hybrid nanofluid using artificial neural network and proposing new correlation
(Wiley-Hindawi, 2020) Colak, A. Batur; Yildiz, Oguzhan; Bayrak, Mustafa; Tezekici, Bekir S.
In this study, an artificial neural network model has been created in order to estimate the specific heat of Cu-Al2O3/water hybrid nanofluid based on temperature (T) and volume concentration (phi). Specific heat values of the Cu-Al2O3/water hybrid nanofluid prepared in five-volume concentration were measured experimentally in the 20 degrees C to 65 degrees C temperature range. The dataset was reserved into three primary parts, with the inclusion of 901 (70%) for the training, 257 (20%) for the test and 129 (10%) for the validation. As a result of comparison with experimental values, it is concluded that this model predicts specific heat with R-value of 0.99994 and an average relative error of approximately 5.84e-9. In addition, a mathematical correlation has been developed to estimate the specific heat of the Cu-Al2O3/water hybrid nanofluid. The data acquired from the mathematical correlation, developed, were in great correlation with all the experimental values with an average deviation of -0.005%. This result has revealed that the developed mathematical correlation is an ideal design for estimating the specific heat of the Cu-Al2O3/water hybrid nanofluid.