Abstract:
Macroscopic modeling of nanofluids is necessary for design and analysis of equipment that rely on nanofluids. For the moment, there is no study that covers recent state-of-the-art nanofluid models, and compares their accuracy and computational efficiency. Single and two phase models have been investigated for the characterization of laminar forced convection of Al2O3-water nanofluid in a circular tube. Single-phase thermal dispersion model that uses velocity gradient, is found to be the most accurate single-phase model in prediction of convective heat transfer coefficient. Since, single-phase models fail in predicting pressure drop and friction factor, a new dispersion viscosity model is introduced for a better representation of effective nanofluid viscosity. In the study, Eulerian-Eulerian and Eulerian-Mixture models are also studied and it is found that they are under and over predicting heat transfer coefficient at entry and fully developed regions, respectively. Considering its computational efficiency, Eulerian-Eulerian model is recommended for applications without calibration data, and if prediction of both heat transfer and pressure drop is important. For the first time, it is shown that the computational cost of Eulerian-Eulerian model can be reduced by the use of Full Multiphase Coupling algorithm. In the study, hexagonal boron nitride-water nanofluid is also studied, and results are compared with Al2O3- water nanofluid. Results indicate that non-granular assumption for two-phase models is questionable for highly thermally conductive particles.
