A New Void Fraction Correlation for Simulation of Two-Phase Flows Using Genetic Algorithm

A New Void Fraction Correlation for Simulation of Two-Phase Flows Using Genetic Algorithm

Void fraction models, which are currently used in thermal-hydraulic analysis codes in the nuclear and other industries, are based on correlations to compute void fraction distribution and slip ratio in two-phase flow. The accuracy of such correlations has a decisive role in determining the correct transport of phases and, subsequently, in the prediction of the correct response of nuclear or industrial systems. The present study aims at presenting a unique and accurate void fraction correlation that could satisfactorily match most of the available experimental data, without working with complex expressions that require iterative schemes or multiple solutions. In order to obtain such a correlation, we have followed the Butterworth idea [1], improved his equation, and proposed a new and more general correlation for void fraction which also includes the effect of mass flux on the aforementioned quantity. Then, we calculated the correlation coefficients with the aid of genetic algorithm, one of the most recent and robust methods for optimizing problems. The presented model for the void fraction is shown to well fit the available empirical counterparts in the literature.