Experimentations are conducted, and kerosene-water counter-current two-phase flow-structure in a duct of 15 mm diameter are identified, categorized, and characterized in five duct-orientations for different combinations of kerosene and water superficial velocities. Some unique counter-current liquid-liquid flow-structures, which have not yet been reported till date, are found through the present experimental investigation. Flow-structures’ interfacial distributions and highly time-varying attributes are captured using a high-resolution DSLR camera and a high-speed video camera, respectively, to distinguish and identify them. The subjective descriptions may confuse the observer. Thus, the objective interpretations of the flow-structures are collected as time-series current and voltage signals using a DPT and in-house fabricated conductivity probes, respectively. Statistical analyses of the time-series data are performed, and statistical parameters are extracted using MATLAB coding. The flow-structures are successfully parameterized and characterized in terms of the ‘non-parametric probability distribution (NPPD)’ plots and those statistical parameters of the objective signatures. These extracted NPPD plots and statistical parameters are found to be very useful for recognizing and distinguishing the individual flow-structures.

进行了实验，并对直径为 15 mm 的管道中的煤油-水逆流两相流动结构进行了识别、分类，并针对煤油和水的表观速度的不同组合以五种管道方向表征。通过目前的实验研究发现了一些迄今为止尚未报道的独特的逆流液-液流动结构。流结构的界面分布和高度时变的属性分别使用高分辨率数码单反相机和高速摄像机捕获，以区分和识别它们。主观描述可能会使观察者感到困惑。因此，流动结构的客观解释被收集为使用 DPT 和内部制造的电导率探针的时间序列电流和电压信号，分别。对时间序列数据进行统计分析，并使用MATLAB编码提取统计参数。根据“非参数概率分布（NPPD）”图和客观特征的那些统计参数，成功地对流结构进行了参数化和表征。发现这些提取的 NPPD 图和统计参数对于识别和区分单个流动结构非常有用。