Nero-fuzzy modeling of the convection heat transfer coefficient for the nanofluid

In this study, experiments were performed by six different volume fractions of Al 2 O 3 nanoparticles in distilled water. Then, actual nanofluid Nusslet number compared by Adaptive neuro fuzzy inference system (ANFIS) predicted number in square cross-section duct in laminar flow under uniform heat f...

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Veröffentlicht in:	Heat and mass transfer 2013, Vol.49 (4), p.575-583
Hauptverfasser:	Salehi, H., Zeinali-Heris, S., Esfandyari, M., Koolivand, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Engineering Engineering Thermodynamics Heat and Mass Transfer Industrial Chemistry/Chemical Engineering Original Thermodynamics
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	In this study, experiments were performed by six different volume fractions of Al 2 O 3 nanoparticles in distilled water. Then, actual nanofluid Nusslet number compared by Adaptive neuro fuzzy inference system (ANFIS) predicted number in square cross-section duct in laminar flow under uniform heat flux condition. Statistical values, which quantify the degree of agreement between experimental observations and numerically calculated values, were found greater than 0.99 for all cases.
ISSN:	0947-7411 1432-1181
DOI:	10.1007/s00231-012-1104-9