Enhancement Heat Transfer of Cu-Water Nanofluids with Thermophysical Properties Modeling by Artificial Neural Network

Fadhil Smaisim, Ghassan

	Enhancement Heat Transfer of Cu-Water Nanofluids with Thermophysical Properties Modeling by Artificial Neural Network
Journal of University of Babylon
Article 1, Volume 25, Issue 5, 2017, Pages 1721-1735
Author
Ghassan Fadhil Smaisim
Abstract
Suspends Cu nanoparticles size in base fluids were adjusted for a formation of nanofluid using the ultrasonic homogenizing. A KD2 PRO was calibrated to measure the thermal conductivities while the dynamic viscosity with measured using the rotating viscometer. Thermal conductivity and dynamic viscosity effects on the other parameters such as volume fractions, base fluids type and the base fluids temperature, which applied an input to the Artificial Neural Network for modeling the nanofluids mathematical expressions and Thermophysical features. The equations of the properties later used in calculating the improvement in heat transfer by ANSYS FLUENT 16.1 to model a fluid flow through the pipe heated by uniform heat flux for laminar Reynolds number 250-2000. Results showed that the temperature and the volume fractions of the nanoparticles had great influences on the thermal conductivity and dynamic viscosity. Thermal conductivities ratio and Nusselt number for Cu-Water nanofluid were depicted with several correlations for previous works. The effect of the nanoparticles diameter on the thermal conductivity ratio was concluded and decided that the thermal conductivity ratio decreased with the increase of the nanoparticles diameter, so the effect of the volume fraction within small particle sizes approximately nil. Results reveal good enhancement in thermal transfers and the maximum heat transfer coefficient enhancement was obtained at 1% Cu nanofluid.
Keywords
Enhancement heat transfer; Cu nanofluid; ANN; ANSYS Fluent; thermal properties

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