Computational fluid dynamic analysis of graphene oxide/water nanofluid heat transfer over a double backward-facing microchannel

Abstract

Background: Based on the literature, increasing the heat transfer of nanofluids in the backward microchannel owing to the micro scales and significant effects of the step has been introduced as an attractive issue.Methods: The effect of an inclined step combined with different types of obstacles on the heat transfer of graphene oxide nanofluid inside a double backward-facing step (BFS) microchannel is studied in this study. The numerical model according to the finite volume method (FVM) is utilized to discretize continuity, momentum, and energy equations via ANSYS Fluent 19.0 software. The simulation of double BFS microchannel by using computational fluid dynamics (CFD) is carried out to enhance the forced convection heat transfer of graphene oxide–water nanofluid. This work aims to illuminate the influences of the Reynolds numbers (1, 50, and 100), the nanoparticles volume fraction (0, 0.02, and 0.04), the triangular obstacle existence, and the obstacle location.Significant findings: Based on the CFD results, the maximum Nusselt number of 12.7% and heat transfer coefficient of 12.3% are observed compared to the pure water in the case of triangular obstacle at the top of the first step with nanoparticle volume fraction of 4% and Reynolds numbers of 50 and 1, respectively. Furthermore, heat transfer improves with high pressure drop and friction factor is widely affected by the triangular obstacles and their locations.