Presenting two new empirical models for calculating the effective dynamic viscosity and thermal conductivity of nanofluids

Abstract

In this paper, two new empirical equations for calculating the effective dynamic viscosity and thermal conductivity of nanofluids are presented based on a high number of experimental data available in the literature. These two equations present the effective dynamic viscosity and thermal conductivity of nanofluids as a function of the volume fraction (0 ≤ ϕ ≤ 12%), size (10nm ≤ dp ≤ 5μm) and type (Ag, Cu, Al2O3, TiO2, CuO, SiO2, ZnO, MgO, Fe, Fe3O4, Al, AlN, CaCO3) of the nanoparticles, temperature and thermo-physical properties of the base fluid. The proposed models are compared with frequent used models in literature (Brinkman and Maxwell-Garnett models) and found that these classical models severely underestimate the effective viscosity and thermal conductivity of nanofluids. Two proposed models are also compared with some other theoretical models, as those of Chon, Patel, Corcione, Prasher, Koo, Maiga, Masoumi, etc. The results showed that, present models for spherical nanoparticle are in excellent agreement with experimental data and provide more accurate character predictions for thermos-physical properties of nanofluid in comparison with existing models. In addition, five new equations are also proposed using the least squares method for calculating the viscosity of five common working fluids (Water, Glycerol, Ethylene glycol (EG), Propylene glycol (PG) and Ethanol) as a function of the temperature. Beside the pure comparison between these models, two well-known benchmark cases of conjugate natural (Differentially Heated Cavity) and mixed convection (Two-sided Lid-driven Cavity) of nanofluid are chosen in order to investigate the effects of the volume fraction, size and type of the nanoparticles on the fluid flow and heat transfer performance of nanofluids. Easy to use for numerical simulation purposes, covering a wide range of the solid particle size and having high accuracy in predicting thermos-physical properties of nanofluids make these equations useful and practical for the design of various thermal engineering systems such as heat exchangers.