A methodology and database to quantify the confidence level of methods for gas–liquid two-phase flow pattern prediction

Abstract

A novel methodology is presented to quantify the confidence level in the prediction of gas–liquid two-phase flow patterns in pipes. An experimental flow pattern data base has been collected, consisting of 12 studies (a total of 9029 data points). The experimental data are compared with the predictions of the unified Barnea (1987) model (any other model/method can be used), and the confidence level in the predictions is quantified. Also, gaps in the data base are identified and future studies required in this are discussed.