Three-dimensional optimization of a heat sink performance using the combined active and passive methods

The present study aims to investigate the effects of the presence of vortex generators in the cooling fluid flow of a microchannel heat sink and to seek to optimize its performance in terms of heat transfer. In addition, the cooling fluid used is a pure water solution in the presence of aluminum oxide (Al2O3) nanoparticles. The numerical simulation is performed for different cases. Each case is characterized by the rate of the volume fraction of aluminum (Al2O3) in the presence of the base fluid (pure water). Four cases were studied in which the rate of the volume fraction of aluminum (Al2O3) suspended in the base fluid was chosen equal to 1%, 2%, 3%, and 4%, respectively. The heat sink is a microchannel, and the numerical simulations are performed for a Reynolds number in the range (600, 1400). A finite volume scheme resolves the system of differential equations governing the physical problem according to the imposed boundary conditions. The problem of pressure–velocity coupling, imposed by the presence of pressure by its gradient in the equations of the algebraic system to be solved, is solved by using the semi-implicit method for pressure-linked equation (SIMPLE) algorithm. The different thermal factors: the Nusselt number, the friction factor, and the thermal performance enhancement factor, and the two physical fields: the velocity and the temperature field, have been analyzed. The results obtained show that, for Re = 600, the value of Nu increased with increasing concentrations of 5.68, 8.16, 10.08, and 11.66 for a concentration equal to 1%, 2%, 3%, and 4%, respectively. The results also show that playing a vortex generator with a constant concentration equal to 2% could further improve the thermal performance improvement factor from 25 to 67%. Accordingly, the configuration corresponding to Case 2 performs better in heat transfer than the others. Finally, new correlations to predict the friction factor, Colburn j-factor, and Nusselt number as a Reynolds number and design function are located at the end of this study.