Evaluation of MWCNTs-ZnO/5W50 nanolubricant by design of an artificial neural network for predicting viscosity and its optimization

This research presents the design of an artificial neural network (ANN) and experimental evaluation of MWCNTs-ZnO(10%-90%)/5W50 nanolubricant at different temperatures and shear rates, and presentation of a mathematical correlation to predict viscosity and its optimization. The nanofluid experimental evaluation was carried out at the solid volume fractions of 0.05, 0.1, 0.25, 0.5, 0.75 and 1% and the temperature range of 5 to 55 degrees C. Nanofluid viscosity optimization was performed with respect to temperature, volume fraction, and shear rates. A point at the temperature of 54.29 degrees C, solid volume fraction of 0.1%, and shear rate of 1029.89 (1/s) had the optimal minimum viscosity of 38.1654 mPa.s. The ANN designed for the nanofluid included two hidden layers with an optimal structure with 3 neurons in the first layer and 3 neurons in the second layer. The value of R for this neural network was 0.9998057. In the final stage, ANN data have an error lower than 7%. This research reports the ANN model parameters. (C) 2018 Published by Elsevier B.V.