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S. Kondaraju, E. K. Jin and J. S. Lee, “Direct Numerical Simulation of Thermal Conductivity of Nanofluids: The Effect of Temperature Two-Way Coupling and Coagulation of Particles,” International Journal of Heat and Mass Transfer, Vol. 53, No. 5-6, 2010, pp. 862-869. doi:10.1016/j.ijheatmasstransfer.2009.11.038

has been cited by the following article:

• TITLE: Computing the Pressure Drop of Nanofluid Turbulent Flows in a Pipe Using an Artificial Neural Network Model

  AUTHORS: Mahmoud S. Youssef, Ayman A. Aly, El-Shafei B. Zeidan

  KEYWORDS: Artificial Neural Networks (ANNs); Turbulent Flow; Nanofluids; Pressure Drop

  JOURNAL NAME: Open Journal of Fluid Dynamics, Vol.2 No.4, December 18, 2012

  ABSTRACT: In this study, an Artificial Neural Network (ANN) model to predict the pressure drop of turbulent flow of titanium dioxide-water (TiO2-water) is presented. Experimental measurements of TiO2-water under fully developed turbulent flow regime in pipe with different particle volumetric concentrations, nanoparticle diameters, nanofluid temperatures and Reynolds numbers have been used to construct the proposed ANN model. The ANN model was then tested by comparing the predicted results with the measured values at different experimental conditions. The predicted values of pressure drop agreed almost completely with the measured values.