A combined theory model for predicting the viscosity of water-based Newtonian nanofluids containing spherical oxide nanoparticles

Viscosity plays a crucial role in the flow and heat transfer process of nanofluids. To effectively calculate and predict the changing characteristics of nanofluids viscosity, this study presents a theoretical model combining the static interface layer and dynamic Brownian motion mechanisms of spherical nanoparticles for water-based Newtonian nanofluids. The model describes the reasonable dependences of nanofluids viscosity on physical properties of nanoparticles (density, volume fraction, size) and base fluid (temperature, viscosity, density). Taking four kinds of typical water-based Newtonian nanofluids containing spherical oxide nanoparticles (Al₂O₃, CuO, SiO₂ and TiO₂) as examples, the prediction performance of different viscosity models is analyzed in detail. From the comparison studies, it is demonstrated that the new viscosity model developed in this paper can exhibit better prediction performance than many well-known theoretical models and empirical correlations. Not only do the predicted results of model agree well with the experimental data from various studies, but also the effects of different factors are reflected effectively.