Mathematical simulation of the rheological behavior of MWCNT (20%)-ZnO (80%)/single-grade SAE50 hybrid nanofluid to introduce the most optimal correlation function and determining the optimal lubrication conditions in hot and cold environments

In the article report, the viscosity of MWCNT (20%)-ZnO(80%)/SAE50 hybrid nanofluid (HNF) is investigated by statistical approach (RSM) and comparatively. The study is carried out in laboratory conditions with temperature T = 25-50 degrees C, volume fraction phi = 1-0.0625% and shear rate gamma(.)= 666.5-7998 s(-1). The intention in this research is to identify and introduce the best function of the modeler by the standard criteria of quality measurement and also to determine the optimal mode of lubrication in cold and hot environmental conditions on a laboratory scale. Studying the thermophysical properties of HNF with a new formulation and determining the target response values in cold and hot environmental conditions (through equating with real conditions) is one of the innovations of this research. Statistical analysis has shown that the Quartic model has a stronger level of significance and predictive power compared to other models. Based on the regression analysis, the coefficient of determination (R-2), correlation deviation (C.D), probability value (P-value) and reliability (C.V) for the Quartic model are respectively equal to 0.9996, 1.89% to + 1.82%, 2.576563 e-250% and 0.96151%. Based on RSM optimization, suitable viscosities for lubrication in a cold environment (when starting the vehicle engine) and a hot environment (in motion mode) are suggested as 284.777 and 226.910, respectively.

Automated summary

The viscosity of MWCNT (20%)-ZnO(80%)/SAE50 hybrid nanofluid (HNF) is investigated using statistical approach (RSM) and compared with other models. The study is conducted under laboratory conditions with varying temperature, volume fraction, and shear rate. The aim of this research is to identify the best model function and determine the optimal lubrication mode in cold and hot environments. The Quartic model shows the highest significance and predictive power among all the models analyzed.