Abonnement à la biblothèque: Guest

ISSN Online: 2377-424X

ISBN Print: 978-1-56700-421-2

International Heat Transfer Conference 15
August, 10-15, 2014, Kyoto, Japan

Convective Heat Transfer Characteristics of Low Concentration CuO-Water Nanofluids in the Turbulent Flow Regime Based on an Artificial Intelligence Models

Get access (open in a dialog) DOI: 10.1615/IHTC15.fcv.008461
pages 3277-3284

Résumé

In this paper, two models were developed to predict the convective heat transfer characteristics of CuO-water nanofluid in a fully developed turbulent flow by using FCM-based adaptive neuro-fuzzy inference system (FCM-ANFIS), and GA-PNN hybrid system as well as a set of experimental data. Models have the capability to predict the Nusselt number of the nanofluid as a function of Reynolds number, Prandtl number, nanoparticles volume concentration and average nanoparticles diameter. The outputs of the proposed models compared with experimental data and also available correlations. The results showed that the application of artificial intelligent methods in order to model the turbulent convective heat transfer characteristics of CuO-water nanofluid lead to good agreement with the experimental data.