Statistical simulator for synthesizing disturbance waves in downward vertical annular flow
Year: 2026
Type: article
Abstract: Annular flow is a gas-liquid flow regime commonly encountered in industrial applications, such as those in nuclear power and oil and gas production. While upward configurations have received substantial attention, detailed investigations of downward vertical annular flow remain comparatively limited. This study presents a statistical synthesis simulator capable of generating representative annular flow time series using only supervisory process parameters typically available in industrial environments, including pipe diameter, volumetric flow rates, and fluid properties (density and viscosity). Experiments were performed in two test sections with internal pipe diameters of 26 mm and 50 mm, where film thickness time series were recorded using a non-intrusive, high-speed conductance sensor. The acquired data were analyzed to extract key characteristics of the disturbance waves, including frequency, amplitude, velocity, and wave shape, which were then used to formulate empirical correlations governing the generation of synthetic unit waves. Using the combined 26-mm and 50-mm databases, the fitted correlations achieved R 2 values of 0.91–0.99 for the main unit-wave geometrical parameters. These correlations were incorporated into the simulator to construct the synthetic film-thickness time series, from which the mean liquid fraction is computed and compared to experimental data. The results fall predominantly within the ±30% band, with overall errors of approximately MAPE ≈ 21%. • •Statistical simulator for synthesizing disturbance waves in downward annular flow. • Uses conductance sensor data to capture liquid film thickness with high temporal resolution. • Extracts key wave parameters: amplitude, frequency, velocity, and unit wave geometry. • Empirical correlations were developed for two pipe diameters (26 mm and 50 mm ID). • Synthesized time series reproduce experimental waveforms with R 2 > 0.95 for most parameters.
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,080
Award: G6727924020
OpenAlex ID: W7118379249