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

作     者：Mahmoud S. Youssef Ayman A. Aly El-Shafei B. Zeidan 

作者机构：Department of Mechanical Engineering Faculty of Engineering Taif University Al-Hawiah Saudi Arabia Mechanical Engineering Department Faculty of Engineering Assiut University Assiut Egypt Mechanical Power Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt 

出 版 物：《Open Journal of Fluid Dynamics》 (流体动力学（英文）)

年 卷 期：2012年第2卷第4期

页      面：130-136页

学科分类：08[工学] 0801[工学-力学（可授工学、理学学位）] 

主　　题：Artificial Neural Networks (ANNs) Turbulent Flow Nanofluids Pressure Drop 

摘      要：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.