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

• 作者: Ayman A. Aly El-Shafei B. Zeidan Mahmoud S. Youssef
• 来源期刊: 流体动力学(英文)
• 学科: 物理学
• 关键词: Artificial NEURAL Networks (ANNs) TURBULENT Flow Nanofluids Pressure DROP
• 年，卷（期）: 2012,（4）
• 页码范围: 130-136
• 页数: 7页
• 分类号: O3

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.