Numerical Study of Mixing Thermal Conductivity Models for Nanofluid Heat Transfer Enhancement

Abstract

Researchers have paid attention to nanofluid applications, since nanofluids have revealed their potentials as working fluids in many thermal systems. Numerical studies of convective heat transfer in nanofluids can be based on considering them as single- and two-phase fluids. This work is focused on improving the single-phase nanofluid model performance, since the employment of this model requires less calculation time and it is less complicated due to utilizing the mixing thermal conductivity model, which combines static and dynamic parts used in the simulation domain alternately. The in-house numerical program has been developed to analyze the effects of the grid nodes, effective viscosity model, boundary-layer thickness, and of the mixing thermal conductivity model on the nanofluid heat transfer enhancement. CuO–water, Al2O3–water, and Cu–water nanofluids are chosen, and their laminar fully developed flows through a rectangular channel are considered. The influence of the effective viscosity model on the nanofluid heat transfer enhancement is estimated through the average differences between the numerical and experimental results for the nanofluids mentioned. The nanofluid heat transfer enhancement results show that the mixing thermal conductivity model consisting of the Maxwell model as the static part and the Yu and Choi model as the dynamic part, being applied to all three nanofluids, brings the numerical results closer to the experimental ones. The average differences between those results for CuO–water, Al2O3–water, and CuO–water nanofluid flows are 3.25, 2.74, and 3.02%, respectively. The mixing thermal conductivity model has been proved to increase the accuracy of the single-phase nanofluid simulation and to reveal its potentials in the single-phase nanofluid numerical studies. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.