Abo Bibliothek: Guest

ISSN Online: 2377-424X

International Heat Transfer Conference 12
August, 18-23, 2002, Grenoble, France

Prediction of void fraction in air/water two-phase flows at elevated temperatures

Get access (open in a dialog) DOI: 10.1615/IHTC12.1010
5 pages

Abstrakt

Radial basis function neural networks have been used to interpolate within the range of available experimental void fraction data for a two-phase air/water flow passing through an upward vertical pipe. The independent parameters are in terms of dimensionless groups such as volumetric flow ratio, density ratio, and Weber number. A comparison between the experimental and predicted data reveals an overall average error of 3.6% for training and 5.8% for unseen data. In addition, the trend of both predicted results and experimental data are consistent.