Optimization of Viscosity in MWCNT-MgO (35-65%)/5W50 Nanofluid and Comparison of Experimental Results with the Designed ANN

This study was on the optimization of the viscosity of MWCNT-MgO (35-65%)/5W50 nanofluid and comparison of experimental results with the designed artificial neural network (ANN). The experimental examination was performed at solid volume fraction (SVF) s of 0.05, 0.1, 0.25, 0.5, 0.75, 1% and the temperature of 5-55 degrees C. A mathematical relationship was proposed to predict its viscosity using the RSM method in Design-Expert software. The viscosity of this nanofluid was also optimized concerning temperature, SVF, and shear rate (SR). A point with a specification of T = 54.45 (degrees C), SVF = 0.06%, and SR = 11,899.24 (1/s) had an optimum viscosity of 39.0754 mPa s. Specification parameters of the ANN model were reported in this study as well. The results of the proposed mathematical correlation could not accurately predict, as well as the ANN and the predictions provided by ANN were more accurate.

Automated summary

This study focused on optimizing the viscosity of MWCNT-MgO(35-65%)/5W50 nanofluid and comparing experimental results with an artificial neural network (ANN). The ANN predictions were found to be more accurate compared to the mathematical correlations proposed in the study for viscosity prediction.