Particle-resolved simulations for nanofluid thermal enhancement in channel flows

Abstract

Nanofluids have been studied extensively for improved heat transfer performances in various thermal systems. In this article, we adopt the particle-resolved method to study the thermal enhancement of nanofluids in channel flows under constant wall temperature (CWT) and constant heat flux (CHF) conditions. The smoothed profile method is employed to describe the nanoparticles suspending in the base fluid and the lattice Boltzmann method is utilized to solve the flow and temperature fields. Unlike the continuum representation of nanofluids, this particle-resolved approach can incorporate the thermophysical properties of the base fluid and nanoparticles directly in simulation, and flow and temperature distributions around nanoparticles are available. Our simulations reveal detailed information on the nanoparticle influence on the wall thermal distributions, and illustrate the enhancement mechanism for heat transfer between the boundary wall and fluid flow: The nanoparticles near the wall increase the local heat flux under CWT and decreases the local wall temperature under CHF condition. The heat transfer coefficient is utilized to characterize the thermal performance for nanofluids, and it increases 6–16% for the nanofluid systems considered in our simulations. The effects of key system parameters, such as the nanoparticle volume fraction, thermal conductivity, and Reynolds number, are also investigated. Our results show that, for both CWT and CHF systems, the particle volume fraction and thermal conductivity can both increase the heat transfer coefficient; however, the particle conductivity effect becomes less significant or even negligible when it is greatly larger than the base fluid conductivity. For the limited range and relatively low values of Reynolds numbers considered in this work, it appears that the Reynolds number has no obvious influence on the system thermal performance. These finding could be beneficial for a better understanding of the complexity of nanofluid systems and for future nanofluid development and applications.