Experimental Investigation for Flow Regime Identification Using Probability Density Function of Void Fraction Signals

Abstract

In this study, upward air–water two-phase flow tests were carried out in a 3 cm diameter pipe under atmospheric pressure, and over 3000 data points were collected from a wide range of superficial gas and liquid velocities (⟨jg⟩ ≈ 0.02–30 m/s and ⟨jf⟩ ≈ 0.02–2 m/s) for the investigation of flow regime identification. The probability density function (PDF) of transient void fraction signals and its full-width at half-maximum (FWHM) were obtained and used for analysis and data classification. Considering the features of PDF profiles, the flow conditions can be classified into four regions, which show a fair agreement with the existing flow regime maps in general trends. Furthermore, by examining the FWHM distributions, two more regions with high-FWHM (HF) values were identified as the transitions of higher-flow bubbly-to-slug and slug-to-churn flows as well as most portion of churn flow, and a valley region next to the HF regions can express the transition of churn-to-annular flows. Overall, six groups of flow conditions can be classified based on the present methodology, and each group can be corresponding to specific flow regimes or transition regions. This study can provide a simple and efficient way for flow regime identification.