Numerical simulations of forced convection heat transfer and flow characteristics of nanofluids in small tubes using two-phase models

Abstract

Laminar and turbulent forced convection heat transfer and flow characteristics of nanofluids in small smooth tubes are numerically simulated using two kinds of multiphase-flow models. The simulated results are compared with the experimental results from the published papers and the traditional predicting correlations to investigate the applicability of these models for nanofluids. The multiphase-flow models including mixture model and Eulerian model, and both of them belong to the well-known Euler–Euler model. The effects of various parameters such as Reynolds number and nanoparticles concentration on the heat transfer and flow characteristics are investigated and discussed in each model. The study results show that little deviation exists between the simulated results and the traditional predicting correlations for low concentration nanofluid, which indicates that low concentration nanofluid has no meaningful nano-effect on forced convection heat transfer. While, non-traditional fluid characteristics occur and increase with increasing the nanoparticles concentration, and the simulated results using special models of multiphase flow are closer to the experimental data than that of the traditional correlations, which means the multiphase flow models are more accurate than traditional correlations for high concentration nanofluid. Moreover, the numerical results also indicate that the drag coefficients of simulated results have only little difference less than 0.4% with that of experimental results for nanofluids in the laminar flow region. However, the drag coefficients of simulated results have a increase by about 60–22% compared with the experimental results in the turbulent flow region. As conclusion, the present study indicates that the two-phase models, including mixture model and Eulerian model, can predict the forced convection heat transfer and flow characteristics of nanofluid well, and have important implications for the application of nanofluid.