Forecasting and Optimization of the Viscosity of Nano-oil Containing Zinc Oxide Nanoparticles Using the Response Surface Method and Sensitivity Analysis

In the current paper, the behavior of zinc oxide/SAE50 nano lubricant as a part of the new generation of coolants and lubricants is examined using response surface method (RSM). The data used in this study were viscosity at dissimilar volume concentrations (0-1.5%) and temperatures (5-50 °C) for dissimilar shear rate values. Therefore, sensitivity analysis based on variation of nanoparticle (NP) concentration and temperature was also implemented. The findings revealed that enhancing the volume fraction (φ) exacerbates the viscosity sensitivity to temperature. Given the noteworthy deviance between the experimental viscosity and the data forecasted by existing classical viscosity correlations, a novel regression model is gained. R2 and adj-R2 for this model were calculated as 0.9966 and 0.9965, respectively, which represent a very good prediction with a standard deviation of 3%.