M. S. Youssef; Ayman A. Aly

Artificial Neural Network Turbulent Modeling for Predicting the Pressure Drop of Nanofluid

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Author(s)

1. Mechanical Engineering Department, Faculty of Engineering, Taif University, Al-Haweiah, P.O. Box 888, Saudi Arabia

2. Permanent Address: Mechanical Engineering Department, Faculty of Engineering, Assiut University, Assiut P.O. Box 71516, Egypt

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2013.11.02

Received: 15 Apr. 2013 / Revised: 10 Aug. 2013 / Accepted: 4 Sep. 2013 / Published: 8 Oct. 2013

Index Terms

Nanofluids, Particle Concentration, Turbulent Flow, Pressure Drop, Artificial Neural Network

Abstract

An Artificial Neural Network (ANN) model was developed to predict the pressure drop of titanium dioxide-water (TiO2-water). The model was developed based on experimentally measured data. Experimental measurements of fully developed turbulent flow in pipe at different particle volumetric concentrations, nanoparticle diameters, nanofluid temperature and Reynolds number were used to construct the proposed model. The ANN model was validated by comparing the predicted results with the experimental measured data at different experimental conditions. It was shown that, the present ANN model performed well in predicting the pressure drop of TiO2-water nanofluid under different flow conditions with a high degree of accuracy.

Cite This Paper

M. S. Youssef, Ayman A. Aly, "Artificial Neural Network Turbulent Modeling for Predicting the Pressure Drop of Nanofluid", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.11, pp.13-20, 2013. DOI:10.5815/ijitcs.2013.11.02

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International Journal of Information Technology and Computer Science (IJITCS)