Experimental investigation on vertical upward co-current air–water slug flow was carried out at atmospheric pressure, employing optical probes and high-speed photography. Experiments were performed with water superficial velocity ranging from 0.089 to 1.52 m/s and gas superficial velocity ranging from 0.049 to 1.06 m/s in a polymethyl methacrylate tube of 15 mm inner diameter. Taking advantage of the time-domain characteristics of optical probes, slug flow has been disposed as a combination of Taylor bubbles and liquid slugs. Slug flow identification, characteristic parameters measurement and analysis were conducted in the present study. Firstly, combined with subjective observation, a developed methodology of flow pattern identification based on machine learning was proposed, with emphasis on slug flow. Results showed that the proposed method exhibited an outstanding advantage in the identification in the flow pattern transition region. More importantly, extensive data on local void fraction in liquid slugs (αl,LS) and in continuous slug units (αl), gas-phase velocity of Taylor bubble (UTB) and liquid slug (ULS), length of Taylor bubble (LTB) and liquid slug (LLS), were obtained. Through comprehensive analysis, it was found that turbulence intensity and flow pattern transitions were the dominant factors in affecting the characteristics of slug flow parameters.
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