Optimization of heat transfer enhancement of nanofluid in a channel with winglet vortex generator

Abstract

A numerical simulation was performed to investigate the effect of the nanoparticles, vortex generator and combination of them on heat transfer and fluid flow characteristics in a rectangular channel using Commercial Computational Fluid Dynamics Code FLUENT. Euler-Lagrangian approach was utilized in the numerical modeling of the nanofluids. The fluid was considered as a continuous phase and the heat and flow fields were analyzed by solving Navier–Stokes and energy equations and the nanoparticles were simulated as a discrete phase in a Lagrangian frame. The thermal and hydraulic performances of the channel were investigated at different nanoparticle concentration, shape and angle of attack of the vortex generator. According to the results, the Nusselt number increases by raising the nanoparticles concentration and adding nanoparticles is more effective than placing VG from thermal point of view in the range of study. Using a combination of these heat transfer enhancers maximizes the thermal performance of the channel as well as the flow resistance. So, in order to achieve the best thermal-hydraulic performance, combination of the computational fluid dynamics analyses, artificial neural networks and multi-objective genetic algorithm was used to determine the optimal values of these parameters. Finally, a set of optimal solutions as well as the best shape, angle of attack of the VG and nanoparticles volume fraction was obtained.