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Turbulent forced convection of Cu–water nanofluid: CFD model comparison
Affiliation:1. Department of Mechanical, Faculty of Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia;2. Department of Mechanical Engineering, University of Sheffield, Sheffield, S1 3JD, UK;3. Institute of Mathematical Sciences, University of Malaya, Kuala Lumpur, 50603, Malaysia;1. Technical University “Gheorghe Asachi” from Iasi, Romania;2. Dipartimento di Ingegneria, Università degli Studi della Campania “Luigi Vanvitelli”, Via Roma 29, 81031 Aversa, CE, Italy;3. Hochschule Niederrhein University of Applied Sciences, Krefeld, Germany;4. Mechanical Engineering Department, Université de Sherbrooke, 2500 Boulevard de l''Université, Sherbrooke, QC J1K2R1, Canada;5. Faculty of Mechanical Engineering, University of Maribor, Slovenia;6. Transilvania University of Brasov, Romania;7. Tensor SRL, Bucharest, Romania
Abstract:This study compares the predictions of five types of computational fluid dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian–Eulerian, mixture and Eulerian–Lagrangian), to investigate turbulent forced convection of Cu–water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is taken between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0% to 2%. The results from the CFD models are compared with results of experimental investigations from literature. According to the results of this study, the non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li's correlation in the prediction of the Nu number. The Eulerian–Eulerian model gives inaccurate results except for φ = 0.5%. The mixture model gives a maximum error of 15%. The Newtonian single-phase model and Eulerian–Lagrangian model, overall, are the recommended models. This work can be used as a reference for selecting an appropriate model for future investigation. The study also gives a proper insight into the important factors such as the Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by each model.
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