EKSPERIMENTAL'NOE ISSLEDOVANIE GIDRODINAMIKI DVUKHFAZNYKH POTOKOV V VERTIKAL'NYKH TRUBAKH. (Experimental Studies of Hydrodynamics of Two-Phase Flow in Vertical Tubes).

Gas-liquid two-phase flows are present in nature and in different industrial activities alike, such as the chemical, petroleum, and nuclear industries. In this type of flow, the liquid and gas phases assume different spatial configurations inside the pipe, called flow patterns. The mathematical modeling of slug flow comprises from simple steady-state models to more complex models for transient regimes. Those models require closure relationships, e.g., empirical correlations and statistical distributions of characteristic flow parameters. In this paper, a model based on artificial neural networks (ANNs) for predicting the two-phase slug flow behavior is proposed. With this ANN model, the parameters that characterize the flow are extracted from the time series of void fractions obtained experimentally. The variables of interest are superficial velocities of the fluids, liquid slug and gas bubble lengths, and the bubble translational velocity and their standard deviations. The knowledge and understanding of those parameters will improve the characterization of the intermittent slug flows and will also provide information on the development of physical models that describe this phenomenon, such as the unit cell models, the drift flux model and the slug tracking model. In general, the estimation models based on ANNs showed good results compared with reference values obtained experimentally. The results show that the estimation models present a mean square error below 2%. The methodology presented here, combining experimentally obtained void fraction time series and ANN, is an appropriated method to infer flow parameters and thus to support slug flow characterization.

Two-Phase Slug Flow Characterization Using Artificial Neural Networks

A unit cell model for gas-liquid pseudo-slug flow in pipes

A new objective and distribution-based method to characterize pseudo-slug flow from wire-mesh-sensors (WMS) data

Condensation of vapor bubbles in a subcooled liquid is known to influence heat transfer and pressure oscillation in subcooled boiling and direct contact condensation. This study reviews the published literature concerning interfacial heat transfer and bubble dynamics in the process of bubble condensation. The correlations for bubble condensation are analyzed and evaluated with a database covering a wide range of Reynolds, Jacob, and Prandtl numbers. Then, the investigations addressing bubble dynamics are reviewed, which focus on the bubble condensation patterns, motion, collapse, and the pressure oscillations induced by bubble condensation, as well as the effect of noncondensable gas and field. Despite the extensive experiments of bubble condensation available in the literature, it is shown that there is still a shortage of investigation focused on the variation of thermal boundary layer and turbulence formed near the bubble at the micro-scale, which could help to develop the prediction method of bubble condensation in the future. The transportation of noncondensable gas inside the mixture bubble and effect of capillary waves formed on the bubble surface on the actual vapor-liquid contact area and thermal boundary are also suggested to be further investigated to gain the thorough understanding of the bubble condensation process.

Review on direct contact condensation of vapor bubbles in a subcooled liquid

A model for the thin film friction factor in near-horizontal stratified-annular transition two-phase low liquid loading flow

This work focuses on the physical representativeness of slug tracking models. The numerical analyses are supported by a detailed experimental campaign in a horizontal test section with 900 pipe diameters long. The analyses address: (a) the model’s performance in predicting averaged slug flow properties, (b) the bubble overtaking mechanism and the slug flow sensitivity to the wake function, (c) the slug flow sensitivity to the slug insertion process, (d) the capture of the slug’s evolution in flows with distinct slug formation processes and (e) the inclusion of the advection term and the induced slug oscillations. The work presents a compressible, one-dimensional slug tracking model satisfying the mass and momentum equations. The equations are presented in a unified fashion to handle horizontal and inclined gas–liquid flows. The model embodies all terms introduced by the previous models and includes the advection term, so far neglected. The analyses, despite of being supported by the present numerical model, are not constrained to this model, but apply to slug tracking models in general.

Analysis of slug tracking model for gas–liquid flows in a pipe

\n This paper studied the effects of system pressure on oil/gas low–liquid–loading flow in a slightly upward inclined pipe configuration using new experimental data acquired in a high–pressure flow loop. Flow rates are representative of the flow in wet–gas transport pipelines. Results for flow pattern observations, pressure gradient, liquid holdup, and interfacial–roughness measurements were calculated and compared to available predictive models. The experiments were carried out at three system pressures (1.48, 2.17, and 2.86 MPa) in a 0.155–m–inside diameter (ID) pipe inclined at 2° from the horizontal. Isopar™ L oil and nitrogen gas were the working fluids. Liquid superficial velocities ranged from 0.01 to 0.05 m/s, while gas superficial velocities ranged from 1.5 to 16 m/s. Measurements included pressure gradient and liquid holdup. Flow visualization and wire–mesh–sensor (WMS) data were used to identify the flow patterns. Interfacial roughness was obtained from the WMS data.\n Three flow patterns were observed: pseudo-slug, stratified, and annular. Pseudo-slug is characterized as an intermittent flow where the liquid does not occupy the whole pipe cross section as does a traditional slug flow. In the annular flow pattern, the bulk of the liquid was observed to flow at the pipe bottom in a stratified configuration; however, a thin liquid film covered the whole pipe circumference. In both stratified and annular flow patterns, the interface between the gas core and the bottom liquid film presented a flat shape. The superficial gas Froude number, FrSg, was found to be an important dimensionless parameter to scale the pressure effects on the measured parameters. In the pseudo-slug flow pattern, the flow is gravity–dominated. Pressure gradient is a function of FrSg and liquid superficial velocity, vSL. Liquid holdup is independent of vSL and a function of FrSg. In the stratified and annular flow patterns, the flow is friction–dominated. Both pressure gradient and liquid holdup are functions of FrSg and vSL. Interfacial–roughness measurements showed a small variation in the stratified and annular flow patterns. Model comparison produced mixed results, depending on the specific flow conditions. A relation between the measured interfacial roughness and the interfacial friction factor was proposed, and the results agreed with the existing measurements.

Pressure Effects on Low-Liquid-Loading Oil/Gas Flow in Slightly Upward Inclined Pipes: Flow Pattern, Pressure Gradient, and Liquid Holdup


 This paper studies the effects of system pressure in oil-gas low-liquid loading flow in a slightly upward inclined pipe configuration using new experimental data acquired in a high-pressure flow loop. Flow rates are representative of the flow in wet gas transport pipelines. Results for flow pattern observations, pressure gradient, liquid holdup and interfacial roughness measurements are presented and compared to available predictive models. The experiments were carried out at three system pressures (1.48, 2.17 and 2.86 MPa) in a 0.155 m ID pipe inclined at 2° with the horizontal. Isopar-L oil and nitrogen gas were the working fluids. Liquid superficial velocities ranged from 0.01 to 0.05 m/s while gas superficial velocities ranged from 1.5 to 16 m/s. Measurements included pressure gradient and liquid holdup. Flow visualization and Wire-Mesh Sensor (WMS) data were used to identify the flow patterns. Interfacial roughness was obtained from the WMS data.
 Three flow patterns were observed: pseudo-slug, stratified and annular. Pseudo-slug is characterized as an intermittent flow where the liquid does not occupy the whole pipe cross-section as the traditional slug flow does. In the annular flow pattern, the bulk of the liquid was observed to flow at the pipe bottom in a stratified configuration, however, a thin liquid film covered the whole pipe circumference. In both stratified and annular flow patterns, the interface between the gas core and the bottom liquid film presented a flat shape. The superficial gas Froude number, FrSg, was found to be an important dimensionless parameter to scale the pressure effects on the measured parameters. In the pseudo-slug flow pattern, the flow is gravity-dominated. Pressure gradient is a function of FrSg and vSL. Liquid holdup is independent of vSL and a function of FrSg. In the stratified and annular flow patterns the flow is friction-dominated. Both pressure gradient and liquid holdup are functions of FrSg and vSL. Interfacial roughness measurements show a small variation in the stratified and annular flow patterns. Model comparison gives mixed results, depending on the specific flow conditions. A relation between the measured interfacial roughness and the interfacial friction factor is proposed, and the results agree with existing measurements.

Hendy T. Rodrigues

Papers

A new objective and distribution-based method to characterize pseudo-slug flow from wire-mesh-sensors (WMS) data

A model for the thin film friction factor in near-horizontal stratified-annular transition two-phase low liquid loading flow

Analysis of slug tracking model for gas–liquid flows in a pipe

Pressure Effects on Low-Liquid-Loading Oil/Gas Flow in Slightly Upward Inclined Pipes: Flow Pattern, Pressure Gradient, and Liquid Holdup

Pressure Effects on Low-Liquid Loading Oil-Gas Flow in Slightly Upward Inclined Pipes: Flow Pattern, Pressure Gradient and Liquid Holdup