Characterization of Gas–Liquid Two-Phase Flow by Correlation Dimension of Vortex-Induced Pressure Fluctuation

Abstract

Characterization of flow behaviors is one of the most challenging problems in a gas–liquid flow system. In this paper, correlation dimension, a chaotic characteristic indicator, was introduced to characterize the gas–liquid two-phase flow behaviors by using the fluctuating pressure induced by a bluff body. An artificial neural network was trained to help select suitable flow parameters that were combined with correlation dimension to construct a novel gas–liquid flow pattern map, which was able to distinguish between the bubble, bubble/plug transitional, plug, slug, and annular flows with reasonable accuracy. Furthermore, a quantitative correlation with the form of $u_{\mathrm {g}} = AD_{2}^{B}u^{C}$ was established by the universal fitting and the pattern-specific fitting with the coefficients of determination $R^{2}$ approaching to 1. In view of the simplicity and the convenience of vortex generation and pressure measurement, the correlation dimension-based method provides an effective and practical idea to gas–liquid two-phase flows study.