Two-phase Bubbly Flow Research Articles

Uncertainties in measurements of bubbly flows using phase-detection probes

The analysis of bubbly two-phase flows is challenging due to their turbulent nature and the need for intrusive phase-detection probes. However, accurately characterizing these flows is crucial for safely designing critical infrastructure such as dams and their appurtenant structures. The combination of dual-tip intrusive phase-detection probes with advanced signal processing algorithms enables the assessment of pseudo-instantaneous 1-D velocity time series; for which the limitations are not fully fathomed. In this investigation, we theoretically define four major sources of error, which we quantify using synthetically generated turbulent time series, coupled with the simulated response of a phase-detection probe. Based on the analysis of 1010 simulated bubble trajectories, our findings show that typical high-velocity flows in hydraulic structures hold up to 15% error in the mean velocity estimations and up to 35% error in the turbulence intensity estimations for the most critical conditions, typically occurring in the proximity of the wall. Based on thousands of simulations, our study provides a novel data-driven tool for the estimation of these baseline errors (bias and uncertainties) in real-word phase-detection probe measurements of bubbly flows (air concentrations c<40%).

Interfacial area transport modeling of air–water bubbly two-phase flows in inclined orientations

The present work develops closure models for the interfacial area transport equation for inclined-upward bubbly two-phase flows. This includes frictional pressure drop through a Lockhart-Martinelli method; void fraction and void-weighted gas velocity through a drift-flux analysis; and covariance of bubble interaction mechanisms through a novel void-fraction distribution reconstruction method. Bubbly flow data collected in a 25.4 mm air–water test facility for five angles (0°, 30°, 60°, 80°, and 90°) is used for the development and evaluation of the models. The novel void reconstruction models are able to predict the covariance of bubble interaction terms within ±30%, and the transport of interfacial area can be predicted within 9 %.

Self-adaptive and time divide-and-conquer physics-informed neural networks for two-phase flow simulations using interface tracking methods

Physics-informed neural networks (PINNs) are emerging as a promising artificial intelligence approach for solving complex two-phase flow simulations. A critical challenge in these simulations is an accurate representation of the gas–liquid interface using interface tracking methods. While numerous studies in conventional computational fluid dynamics (CFD) have addressed this issue, there remains a notable absence of research within the context of PINNs-based two-phase flow simulations. Therefore, this study aims to develop a robust and generic PINNs for two-phase flow by incorporating the governing equations with three advanced interface tracking methods—specifically, the Volume of Fluid, Level Set, and Phase-Field method—into an improved PINN framework that has been previously proposed and validated. To further enhance the performance of the PINNs in simulating two-phase flow, the phase field constraints, residual connection and the time divide-and-conquer strategies are employed for restricting neural network training within the scope of physical laws. This self-adaptive and time divide-and-conquer (AT) PINNs is then optimized by minimizing both the residual and loss terms of partial differential equation. By incorporating the three different interface tracking methods, it efficiently handles high-order derivative terms and captures the phase interface. The case of single rising bubble in two-phase flow is simulated to validate the robustness and accuracy of the AT PINNs. The simulation's accuracy is evaluated by comparing its performance in terms of velocity, pressure, phase field, center of mass, and rising velocity with that of conventional PINNs and CFD benchmarks. The results indicate that the AT PINNs coupled with these interface tracking methods offers a satisfactory performance in simulating rising bubble phenomenon.

A numerical study on machine-learning-based ultrasound tomography of bubbly two-phase flows

Ultrasound tomography (UT) of bubbly two-phase flows using machine learning (ML) was investigated by performing two-dimensional ultrasound numerical simulations using a finite element method simulator. Studies on UT for two-phase flow measurements have been conducted only for some bubbles. However, in an actual bubbly flow, numerous bubbles are complexly distributed in the cross-section of the flow channel. This limitation of previous studies originates from the transmission characteristics of ultrasound waves through a medium. The transmission characteristics of ultrasound waves differ from those of other probe signals, such as radiation, electrical, and optical signals. This study evaluated the feasibility of combining UT with ML for predicting dense bubble distributions with up to 20 bubbles (cross-sectional average void fraction of approximately 0.29). We investigated the effects of the temporal length of the received waveform and the number of sensors to optimize the system on the prediction performance of the bubble distribution. The simultaneous driving of the installed sensors was simulated to reduce the measurement time for the entire cross-section and verify the method’s applicability. Thus, it was confirmed that UT using ML has sufficient prediction performance, even for a complex bubble distribution with many bubbles, and that the cross-sectional average void fraction can be predicted with high accuracy.

Conception of a compact flow boiling loop for the International Space Station- First results in parabolic flights

The design of a pipe flow boiling experiment for the International Space Station is proposed, taking into account typical weight, power consumption and size constraints. The effect of singularities such as elbows upstream the test section is investigated. Velocity profiles downstream two elbows, measured by Particle Image Velocimetry are in good agreement with numerical simulation and allow to determine a specific distance (decay length) downstream the elbows for which the velocity profile recover its axisymmetry. From these results a breadboard is designed and tested in parabolic flights. Care has been taken to generate boiling downstream the decay length. Two-phase bubbly flow is observed with 2 perpendicular high-speed cameras in the test section and a symmetry of the bubble distribution in the pipe is verified for different gravity conditions when the bubbles are created after the decay length.

Experimental investigation of the critical Reynolds number for bubbly two-phase flow

The critical Reynolds number for dispersed bubbly two-phase flows, gas in liquid, was experimentally investigated. In this experiment, the gas was air and the liquid was water. Water flowed upward through a vertical, translucent pipe, and air was introduced into the water prior to the test section by means of a basswood microbubbler. Dye was injected into the water to indicate when the flow transitioned from laminar to turbulent. Mixtures with gas volume fractions up to 10% were tested, and the Reynolds numbers for which the flow transitioned from laminar to turbulent were recorded. The data showed that the critical Reynolds number fell to roughly one-half of its original single-phase liquid value once the gas volume fractions exceeded 0.1%. These results indicate that the presence of even small amounts of bubbles causes pre-mature transition to turbulence.

Measurement of Bubbly Two-Phase Flow in a Vertical Pipe Using Ultrasonic Velocity Profiler and Digital Optical Imaging

Measurement of Bubbly Two-Phase Flow in a Vertical Pipe Using Ultrasonic Velocity Profiler and Digital Optical Imaging

Design and evaluation of co-currently illuminated two-phase bubbly flow photochemical reactors

Current two-phase flow photochemical reactors are lacking energy efficiency required for industrial applicability. As an alternative, co-currently illuminated bubbly flow photochemical reactors are proposed. These have the advantage of running at higher absorbance values, thereby wasting less photons, improving cost efficiency, and decreasing gas holdup by separating gas and liquid residence time in the reactor. A mathematical model was used in the study in combination with photosensitized reactions, which yielded three coupled differential equations and four non-dimensional groups governing the reactor performance. A parameter study yielded an optimal operating point at a quantum photon balance (ϕtotρ) of 1, an absorbance (AS) of at least 1, a chemical quenching parameter (κA) of less than 0.1, and a sensitizer stability ratio (ϕS/fS) of less than 1. Optimal absorbance was determined via the use of a ray tracing study, yielding a theoretical optimal absorbance of 1.75 using 7 µM of rose bengal. The modelling results are experimentally validated, and the model was shown to be suitable across a wide range of operating conditions. Optimal absorbance was experimentally evaluated to match the modelling results, higher absorbance values lead to more local absorbance, throttling reactor performance. With high reagent concentrations, the reaction was found to be liquid side mass transfer limited. Guidelines are presented to design this novel type of reactor and ways to improve the reactor performance in scaled up versions. The reactor was compared against the current state-of-the-art reactors, yielding an improvement PSTY by 4.5 times and an increased reagent/sensitizer ratio by 100 times, both drastically decreasing operational cost of the reactor.

Solution of the Inverse Problem of Calculating a Gas–Liquid Injector with a Two-Phase Flow

We consider the possibility of solving the inverse problem of calculating a gas–liquid jet injector with a bubbly two-phase flow structure. The parameters governing the injector operation, such as the pressure difference, the orifice diameter, and the air concentration, are determined for the given value of the mean Sauter diameter. For this purpose, the operation of a mixer with a two-phase working body and injectors of different diameters was experimentally investigated in the bubbly operation regime with a water–air working body. In the experiments the parameters of the phases supplied to the mixer (flow rates, pressures, and temperatures) were measured, together with the pressure ahead of the injector. The dispersity and velocity parameters in the spray were measured using the laser shadow method. The statistics thus gathered allow one to obtain the required correlation dependences which makes it possible to solve the problem formulated.

Bubble Trajectory Tracking Based on ORB Algorithm

The system of gas-liquid two-phase bubbly flows is widely found in many industrial fields, such as nuclear energy, chemical, petroleum, and refrigeration. Bubbly two-phase flows measuring including detection and tracking affects the specific engineering problem solving to a great extent. The particle tracking velocity (PTV) algorithm is generally used for the tracking of the particles in the flow field. However, it does not take the shape change of particles into account in the process of flow. In this paper, a kind of bubble feature matching method based on ORB algorithm is proposed, and the edge detection method of findContours in OpenCV is used to extract the bubble contour in the image. The proposed algorithm implements the trajectory tracking of the bubbles with shape change when moving up in liquid. The feasibility of bubble trajectory tracking is shown by displaying of different bubble tracks in the plan, 3D plots and contour changing plots.

Two-Phase Modeling and Simulations of a Polymer Electrolyte Membrane Water Electrolyzer Considering Key Morphological and Geometrical Features in Porous Transport Layers

Polymer electrolyte membrane (PEM) electrolysis has a promising future for large-scale hydrogen production. As PEM electrolysis technology develops, larger operating current densities are required. In order to increase current density, more water should be available at the reaction sites. Moreover, the removal rate of oxygen and hydrogen needs to be effectively improved. This, in turn, necessitates a better understanding of the main mass transport and electrochemical processes. On the anode side, mass transport is particularly crucial because water must be supplied to the catalyst layer (CL) while, at the same time, oxygen bubbles must be eliminated in a parallel flow from the reaction sites into the flow channels. Hence, simulating the two-phase bubbly flow across the cell thickness is necessary to predict PEM electrolysis performance more accurately as a function of the operating current density. This study provides a systematic understanding of how morphological and geometrical features contribute to the polarization curve and performance characteristics of a PEM electrolysis cell. Hence, a multi-phase PEM electrolysis model has been implemented using MATLAB R2022a. Polarization curves have been calibrated against experimental data and then assessed to provide a fundamental understanding of the relationship between the two-phase flow and cell performance.

Intelligent Recognition of Gas-Liquid Two-Phase Flow Based on Optical Image

Gas-liquid two-phase flow is widely involved in many scientific and technological fields, such as energy, electricity, nuclear energy, aerospace and environmental protection. In some fields, extracting the accurate position of bubbles in space can not only accurately capture the characteristics of bubbles in two-phase flow, but also plays an important role in the subsequent research like bubble tracking. It has got some progresses to use Convolutional Neural Network (CNNs) to identify bubbles in gas-liquid two-phase flow, while accurate pixel segmentation map in the bubble identification problem is more desirable in many areas. In this paper, VGG16-FCN model and U-Net model are utilized to identify bubbles in two-phase flow images from the perspective of semantic segmentation. LabelMe is used to label the images in the experiment, which can remove the noise in the original image. In addition, bubble pixels with low ratio relative to the background affects the loss function value tinily which cause the irrational evaluation for the recognition in traditional semantic segmentation, thus, Dice loss is used as the loss function for training to improve the recognition effect. The research results show that the two deep learning models have strong feature extraction ability and accurately detect the bubble boundary.

Simulations of Bubble Formation and Oscillation Behavior in Micro-Leakage Measurement System

In the process of measuring micro-leakage based on the bubble method, the physical parameters of the liquid phase have a great impact on the formation and movement of bubbles, thus affecting the measurement accuracy of the system. Therefore, it is of great significance to study the physical parameters of the liquid phase. At present, it is difficult to independently study the parameters of the liquid phase by experimental methods. In this paper, based on the Cahn-Hilliard phase field model, a gas-liquid two-phase flow model for the expression of leakage is established to independently study the influence of different physical parameters on the formation and movement of bubbles in the measuring system. Firstly, the effects of liquid medium density, dynamic viscosity coefficient and surface tension on the initial shape (aspect ratio), the generation period and the shape oscillation of bubbles after they leave the nozzle are analyzed. Then, an experimental platform for visualization of bubbles in two-phase flow based on machine vision is built, through which the morphological parameters of bubbles in the liquid phase can be obtained in real time. Finally, the results of visualization experiment and numerical simulation are compared. The results show that the initial aspect ratio error of bubbles obtained by visual experiment and numerical simulation is 1.8%, and the average oscillation period error is 12.3%. The results are basically consistent, which proves the rationality and correctness of the mathematical model established. It is found that the liquid with larger dynamic viscosity coefficient μ and density ρ and smaller surface tension σ can be selected as the liquid medium of the measurement system. It is more conducive to the accurate expression of micro-leakage in the measurement system, and the bubble shape can quickly reach a stable state. It provides theoretical support for improving the accuracy and stability of the micro-leakage measurement system.

ON THE VALIDITY CONDITIONS OF THE SATO HYPOTHESIS

Many years ago, Sato and Sekoguchi proposed the additivity of inherent liquid turbulence and bubble-induced liquid pulsations (ordinarily pseudoturbulence) for two-phase bubbly flows. This hypothesis is often used in models of different two-phase flows and in the development of various flow codes, but the validity conditions of this hypothesis are not defined precisely. An electrodiffusional method involving eight double probes is used in this work to detect the wall shear stress in laminar and transitional upward two-phase bubble flows and check this hypothesis. Almost monodispersed spherical bubbles are used. The data show that for small bubbles the coupling of liquid turbulence and bubble pseudoturbulence can be more complex than the simple additivity proposed by Sato and Sekoguchi.

Experimental measurement of bubbly two-phase flow in a 4x4 rod bundle with wire mesh sensor

• Bubbly flow in a 4x4 rod bundle is measured with wire mesh sensor to investigate the effect of mixing-vane spacer grid on void fraction distribution and bubble size. • Effects of bubble injection size on void fraction can hardly be eliminated in the bare rod bundle even when the two-phase flow becomes fully developed. • Bubble entrapment into the swirl core at the tips of mixing vanes produces high localized void fraction and enhances bubble interaction. • Effects of bubble injection size can be eliminated with mixing-vane spacer grid, especially for those with relatively small bubble size. In order to investigate two-phase bubbly flow through fuel assembly of pressurized water reactor (PWR), the wire mesh sensor (WMS) is employed to measure air-water flow in a up-scaled 4x4 rod bundle based on PWR fuel assembly. Measurement is carried out in the bare rod bundle and downstream of mixing-vane spacer grid. Air bubbles are injected equally into 16 subchannels at the inlet with a standalone bubble generator which adjusts the injected bubble size. Distribution of void fraction and bubble size across the rod bundle are derived based on the WMS data. In the bare rod bundle, small-size bubbles (<3mm) are inclined to coalesce and medium-size bubbles (3∼8mm) tends to break up at low gas superficial velocity, while at high gas superficial velocities bubble coalescence produces large-size bubbles (>8mm). High liquid superficial velocity reduces the bubble size. Void fraction distribution of bubble size groups shows that bubbles with diameter less than 4mm mainly reside near the solid walls, while large bubbles with diameter larger than 6mm mainly appear in the subchannel center, which is consistent with Tomiyama’s lift force correlation. The effect of injected bubble size can hardly be eliminated along with flow development in bare rod bundles. When installed with mixing-vane spacer grid, the vortices produced at the tips of mixing vanes induce bubble entrapment into the swirl core, which significantly enhances the interaction between bubbles, as well as the interphase interaction. Such enhancement is even more remarkable in the low-void-fraction cases. As a consequence, the bubble size distribution downstream of the spacer grid shows relatively weak dependence on the injected bubble size. Besides, the vortices lead to strong inter-subchannel void drift of small-size bubbles, which results in void fraction difference between subchannels. The effects of mixing-vane spacer grid decay comparatively fast in the high void fraction cases.

The Initial Corrosion Behavior of 20# Steel under the CO2/Aqueous Solution Gas–Liquid Two-Phase Bubble Flow Condition

The initial corrosion behavior of 20# steel under the condition of gas–liquid (CO2/aqueous solution) two-phase bubble flow was studied through weight loss, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The results showed that the corrosion rate decreased rapidly when the corrosion time was less than 3 h, increased rapidly, even to 19.4% of the initial corrosion rate, when the corrosion time was from 3 h to 5 h, and then decreased slowly to about 63% of the initial corrosion rate after the corrosion time exceeded 5 h under different CO2 pressure conditions. The corrosion happened first at the defects area with a high activity such as the cross points of scratches, gradually formed corrosion pits, and then extended around until the corrosion products covered the whole pipe wall surface. At the beginning stage of the corrosion process, the corrosion products were composed of acicular corrosion products and a small number of flocculent corrosion products and formed the corrosion product layer with micro-cracks. With the extension of the corrosion time, the spherical corrosion particles started to form on the initial corrosion product layer’s surface and gradually covered the initial corrosion product layer completely. The whole corrosion product layer with dual-structure characteristics formed. The inner corrosion product sub-layer was composed of initial corrosion products with columnar characteristics from the cross-section perspective, and the outer corrosion product sub-layer was composed of spherical corrosion products that were relatively dense. There was no obvious interface between the inner columnar sub-layer and the dense outer sub-layer. As time went on, the corrosion product particles with a broccoli shape characteristic formed on the dual-structure corrosion product layer’s surface and finally formed the outermost layer of the whole corrosion product layer. In the end, the whole corrosion product layer with three sub-layers formed, namely, the columnar bottom sub-layer, the relatively dense middle sub-layer, and the surface dense sub-layer composed of particles with a broccoli shape. The main components of the corrosion products were Fe, C, and O, and the main phases of the corrosion products were Fe3C, FeCO3, Fe3O4, Fe2O3, and FeOOH.

Two-phase flow pattern identification in CAES systems with dimensional analysis coupled with support vector machine

Two-phase bubbly flow can lead to challenges during the charging period for hydraulically-compensated Compressed Air Energy Storage systems. In this study, upward two-phase flow systems have been investigated in large diameter vertical pipes to better understand when the transitions to problematic flow regimes occur. A comprehensive dimensional analysis was conducted, considering vertical pipe geometry and fluid thermophysical properties. Nine dimensionless parameters and three two-phase flow maps were created. The plot of liquid Reynolds number, ReL, over the Two-phase Reynolds number, Retp,made classification between the Bubbly, Slug, and Churn flow difficult for large diameter pipes. The plot of the two-phase Capillary number,Catp, over the liquid Reynolds number, ReL, showed large overlap of the data sets extracted from the literature. This may have been due to the weakness of the capillary number in defining the larger pipe flow behaviours. The last flow map based on the Slippage number, Sltp, versus the two-phase Froude number, Frtp, showed an exponential decay relationship between the Froude and Slippage parameter. When this was converted to the semi-log scale it provided a valuable classification map of two-phase flow. Finally, a Support Vector Machine (SVM) technique applied to the 2D plot of (Sltp- Frtp), gave a useful transition boundary to separate regimes in air-water upward flows in large diameter pipes.

Effect of N2 and CO2 bubbles on gas volume fraction and flow pattern in a quasi-2D bubble column by shadow imaging

This study reports the effect of N2 and CO2 bubbles on dilute to dense gas-liquid two-phase bubbly flow. A shadowgraph imaging technique captured bubble images at a high spatiotemporal resolution. The recordings of bubble images allow us to compute gas fraction distribution. It requires challenging segmentation and gas-liquid interface detection approaches in image processing. Hence a novel gas contour characterization technique has been introduced in this study that analyses light intensity per pixel for quantifying the effect of local gas volume fraction. The dominant gas structure and repetitive gas pattern have also been determined here using Fourier transform-based power spectral density and 2D cross-correlation functions, respectively. Gas-liquid flow regimes of dissolved CO2 bubbles are found quite different than that of N2 bubbles. The plausible reasons are that gas fraction distribution at the sparger region may inhibit bubble coalescence and the positive surface charge of CO2 bubbles acts as a barrier to the interface deformation.

Void fraction detection technology of gas-liquid two-phase bubbly flow based on convolutional neural network

Gas-liquid two-phase bubbly flow widely exists in the field of natural gas extraction. The identification and feature extraction of bubbles are becoming more and more important to the pipe system. This study develops a detection method based on Faster R-CNN for real-time bubble recognition, feature extraction, and void fraction calculation. The method detects ellipsoidal large bubbles in gas–liquid two-phase bubbly flow in a vertical closed pipeline with a high void fraction. The uncertainty of the method is 10 %. Then compared to the gas volume holdup from standard flowmeter, average error of this method is 7.07 %, which has high accuracy. This new detection method finds a new way for feature extraction of two-phase flow.

Multiwave Ultrasonic Doppler Method for Bubbly Two-Phase Taylor Couette Flow Measurement

Ultrasonic methods, such as the Ultrasonic Velocity Profile - UVP method, have a number of advantages over other conventional measurement methods. They are non-intrusive, applicable to opaque wall or fluid, and capable of obtaining instantaneous velocity profiles along a measurement line in real time. This paper reports on the development of a multiwave Doppler UVP method for the measurement of bubbly two-phase flow in a Taylor-Couette flow configuration. Due to its highly complex nature, two-phase flow still attracts considerable interest in both experimental measurement as well as numerical simulation. In this study the new multiwave Doppler UVP method exploits two basic ultrasonic frequencies 2 MHz and 8 MHz. The 2 MHz frequency is for the measurement of the bubble phase. The 8 MHz frequency is for that of the liquid phase. The signal processing technique is based on the pulse repetition Doppler method. A new phase discrimination method is proposed to eliminate bubble velocity included in the data of the liquid phase measured by the 8 MHz frequency. Measurements of bubbly two-phase Taylor-Couette flow have been demonstrated and discussed.