• Unified multisensor wavelet framework mapping seven gas–liquid flow regimes. • CWT captures transient interfacial energy with localized time–frequency detail. • 3D scalograms and difference maps reveal spatial regime transition behavior. • Statistical descriptors quantify variability, asymmetry, and intermittency. • High-speed imaging validates regime signatures and supports CFD benchmarking. Understanding gas–liquid flow regimes in pipelines is a critical challenge in multiphase transport, where spatiotemporal transitions influence operational performance and safety. Existing diagnostics often lack the resolution to capture transient, multiscale dynamics. This study establishes a unified, experimentally validated framework to decode the evolution of seven flow regimes—small bubble, plug, elongated bubble, slug, slug–churn, annular, and stratified—in inclined pipelines. Five capacitance sensors installed at 1-m intervals along a 6-m test section continuously recorded permittivity signals. Continuous Wavelet Transform (CWT) enabled localized time–frequency decomposition, and 3D scalograms revealed distinct spectral structures for each regime. Adjacent-sensor difference scalograms identified spatial onset and attenuation of transitions. Statistical descriptors (mean, variance, standard deviation, skewness, kurtosis) quantified instability and intermittency. Notably, stratified flow exhibited upstream skewness ≈1.53 and kurtosis ≈5.1, both decreasing downstream as the interface stabilized. Annular flow showed sustained oscillations within 5–35 Hz with high CWT magnitude values ≥0.9. High-speed imaging confirmed the physical accuracy of these fingerprints. The proposed framework improves regime detection, enhances data availability for CFD validation, and supports more reliable flow assurance strategies in industrial pipeline systems.
Al-Alweet et al. (Fri,) studied this question.