Bubble Tracking Method Research Articles

Deep Learning Based Method for Dynamic Tracking of Bubbles in Microfluidic Gas-Driven Water Experiments

Using microfluidic chips for gas displacement experiments is an important approach for studying CO2 displacement mechanisms and gas-liquid exchange processes. Analyzing the micro-scale distribution of gas and water during gas displacement enables the optimization of injection strategies, offering valuable guidance for enhancing oil and gas recovery rates. Traditional image processing techniques often face challenges in effectively handle the complex gas-liquid flow dynamics and irregular bubble shapes encountered in gas displacement experiments. To address this challenge, this paper proposes a gas bubble detection and tracking method for gas-driven water microfluidic experiments based on domain adaptation in deep learning and improved YOLOv8. Using the CycleGAN style transfer network to generate numerous simulated bubble training samples significantly reduces the manual labeling workload for bubbles. Additionally, the SE attention mechanism is integrated into the YOLOv8 backbone network to enhance the feature extraction capability of bubbles, and the Fast-PConv Head structure is incorporated into the detection head to enhance detection efficiency. Experimental results demonstrate that using just 20 annotated experimental images, the bubble detection accuracy of the proposed method can reach 94%. Lastly, DeepSORT is employed to track bubbles and visualize the dynamic trends of bubble changes in the form of visual charts. The deep learning approach proposed in this paper provides a new perspective for intelligent analysis of bubbles in microfluidic chip experiments, and future work aiming to its application to the complex multiphase flow field in porous media.

Boiling heat flux partitioning model with bubble tracking method considering bubble merger and stochastic characteristics

This study presents the development and validation of a numerical tool of heat partitioning model for boiling heat transfer using a bubble tracking method. It was aimed to account for the effect of stochastic phenomena in the boiling process by simulating individual bubbles. Saturated pool boiling conditions on a horizontal plate heater were analyzed to demonstrate the effectiveness of the proposed model. The model was devised based on the observations from high-resolution pool boiling experiments, assuming a truncated sphere for bubble shape and using simplified microlayer size and thickness models. The developed heat partitioning model was verified by comparisons with the conventional heat partitioning model. Afterward, the validation of the model was conducted by comparing the result of the simulation with the experimental data of the saturated pool boiling. In this validation, measured values of nucleation site density, departure diameter, single-phase heat transfer coefficients, etc. were applied. Additionally, the effect of stochastic phenomena on boiling heat transfer was evaluated using the bubble tracking method, focusing on nucleation timing and nucleation site distribution. Stochastic nucleation was found to reduce the bubble merger probability compared to simultaneous nucleation, leading to increased microlayer evaporation. Stochastic site distribution, on the other hand, decreased active nucleation sites due to the site suppression effect, resulting in reduced microlayer evaporation compared to uniform site distribution.

Bubble tracking method based on Kuhn-Munkres algorithm for boiling two-phase flow study

The study of bubble dynamics is important in various engineering applications as it can provide a fundamental understanding of the bubbly flow behavior. This paper presents a novel method for tracking bubble trajectories and classifying bubble behaviors, including formation, extinction, continuous movement, fragmentation, and coalescence. The method is based on the theory of perfect matching in bipartite graphs. By establishing the perfect matching between bubbles identified at adjacent time instants, judging the continuity of bubble motion, and simply calculating the number of bubbles in the neighbor of matching bubbles at adjacent time instants, the method can deal with the challenging situation where the bubble position and volume significantly change between two adjacent time instants. The method is validated in a simulated vertical pipe boiling flow, showing that the tracking accuracy is 100% and classification accuracies for continuous movement, fragmentation, and coalescence events are estimated to be larger than 90% in a wide range of time steps between two adjacent time instants.

Carbon dioxide-water bubbly flow in a vertical pipe with or without chemical absorption

CO2 bubbly pipe flows with or without chemical absorption were measured to obtain spatial evolution of dissolving bubbly flows. The experiments were carried out using pure water and aqueous NaOH solution of pH = 13 at two gas volume fluxes. The spatial evolutions of flow patterns, mean void fractions and bubble diameter distributions were obtained using an image processing method. The enhancement factor correlation proposed in our previous study was implemented into a three-dimensional one-way bubble tracking method to examine its applicability to CO2-water bubbly flow with chemical absorption. The numerical prediction agreed well with the measured spatial evolutions with or without chemical absorption, which confirmed the applicability of the enhancement factor correlation to bubbly pipe flows.

Overlapping bubble detection and tracking method based on convolutional Neural network and Kalman Filter

Gas-liquid bubbly flow is widely applied in chemical process engineering. Geometric and dynamic parameters of bubbles play an essential role in the numerical prediction of mass and heat transfer processes. However, the critical obstacle in bubble detection is the inability of bubble segmentation and reconstruction when the overlapping issue of multiple bubbles is serious under high void fraction conditions. A new detection and tracking technique for overlapping bubbles was proposed in this paper to identify the overlapped bubbles. First, a novel convolutional neural network is used to detect bubbles. Afterward, the relationship between the detected bubbles in two frames is correlated using the Kalman Filter and neural network. The algorithm achieves 85 % accuracy under high overlap rate conditions in a 10 mm narrow rectangular channel with around 0.1 s for an image. In addition, a comparison test was conducted to evaluate the present technique's accuracy and robustness compared with conventional methods.

Computational study of bubble coalescence/break-up behaviors and bubble size distribution in a 3-D pressurized bubbling gas-solid fluidized bed of Geldart A particles

A computational study was carried out on bubble dynamic behaviors and bubble size distributions in a pressurized lab-scale gas-solid fluidized bed of Geldart A particles. High-resolution 3-D numerical simulations were performed using the two-fluid model based on the kinetic theory of granular flow. A fine-grid, which is in the range of 3–4 particle diameters, was utilized in order to capture bubble structures explicitly without breaking down the continuum assumption for the solid phase. A novel bubble tracking scheme was developed in combination with a 3-D detection and tracking algorithm (MS3DATA) and applied to detect the bubble statistics, such as bubble size, location in each time frame and relative position between two adjacent time frames, from numerical simulations. The spatial coordinates and corresponding void fraction data were sampled at 100 Hz for data analyzing. The bubble coalescence/break-up frequencies and the daughter bubble size distribution were evaluated by using the new bubble tracking algorithm. The results showed that the bubble size distributed non-uniformly over cross-sections in the bed. The equilibrium bubble diameter due to bubble break-up and coalescence dynamics can be obtained, and the bubble rise velocity follows Davidson’s correlation closely. Good agreements were obtained between the computed results and that predicted by using the bubble break-up model proposed in our previous work. The computational bubble tracking method showed the potential of analyzing bubble motions and the coalescence and break-up characteristics based on time series data sets of void fraction maps obtained numerically and experimentally.

Advanced boiling heat transfer model for a horizontal tube with numerical analysis of bubble behaviours

The boiling heat transfer model for a horizontal tube is developed herein, with numerical investigations to realistically simulate bubble nucleation site distributions and bubble behaviours. Accordingly, a new heat partitioning model was proposed to reflect the bubble sliding phenomena more realistically than the extant heat partitioning models for horizontal tubes. The bubble trajectories, merging, lift-off, and distribution of nucleation sites were numerically analysed based on the force balance model, bubble tracking method, and Latin-hypercube sampling. The proposed approach can overcome the limitations of the arithmetic heat partitioning model, which does not reflect bubble mergers and the random nature of the nucleation site distribution. Distinctive bubble behaviours on a horizontal tube can be reproduced by the present model, including bubble sliding, departure, lift-off, and merger. The numerical model presented here considers bubble sliding based on a mechanistic force balance model and bubble merger based on the bubble tracking method. The Monte Carlo method was applied to determine the spatial distribution of the nucleation sites, and statistical information on the wall heat transfer and contribution of each heat transfer mechanism were obtained via extensive calculations. The method developed herein was applied to evaluate the wall heat transfer in horizontal heaters. Further, the proposed numerical boiling heat transfer model was validated against an extant experimental database of horizontal heat exchanger tubes, and the model was observed to predict the wall heat flux with satisfactory accuracy.

Spatial Evolution of CO2‐Contaminated Water Bubble Flows in a Vertical Pipe

AbstractExperiments on CO2‐water bubble flows in a vertical pipe were carried out for clean water, an aqueous NaCl solution, and an aqueous NaCl solution with 1‐octanol to obtain databases of spatial evolutions of the flows with the impurities. Mass transfer correlations for bubbles in these liquids were implemented into a one‐way bubble tracking method. Numerical predictions of the spatial evolution, e.g., transition from a bubbly to a slug flow, depending on the impurities agreed well with the experiments.

Application of SIM, HSPIV, BTM, and BIV Techniques for Evaluations of a Two-Phase Air–Water Chute Aerator Flow

Four image-based techniques—i.e., shadowgraphic image method (SIM), high-speed particle image velocimetry (HSPIV), bubble tracking method (BTM), and bubble image velocimetry (BIV)—are employed to investigate an aerator flow on a chute with a 17° inclination angle. The study focuses on their applications to the following issues: (1) to explore the characteristic positions of three water–air interfaces; (2) to interpret the evolution process of air bubbles shed from the wedged tip of the air cavity; (3) to identify the probabilistic means for characteristic positions near the fluctuating free surface; (4) to explore the probability distribution of intermittent appearance of air bubbles in the flow; (5) to obtain the mean streamwise and transverse velocity distributions of the water stream; (6) to acquire velocity fields, both instantaneous and mean, of air bubbles; (7) to construct a two-phase mean velocity field of both water flow and air-bubbles; and (8) to correlate the relationship among the probability distribution of air bubbles, the mean streamwise and transverse velocity profiles of air bubbles, and water stream. The combination of these techniques contributes to a better understanding of two-phase flow characteristics of the chute aerator.

Interface Tracking Investigation of Geometric Effects on the Bubbly Flow in PWR Subchannels

Absorbing heat from the fuel rod surface, water as coolant can undergo subcooled boiling within a pressurized water reactor (PWR) fuel rod bundle. Because of the buoyancy effect, the vapor bubbles generated will then rise along and interact with the subchannel geometries. Reliable prediction of bubble behavior is of immense importance to ensure safe and stable reactor operation. However, given a complex engineering system like a nuclear reactor, it is very challenging (if not impossible) to conduct high-resolution measurements to study bubbly flows under reactor operation conditions. The lack of a fundamental two-phase-flow database is hindering the development of accurate two-phase-flow models required in more advanced reactor designs. In response to this challenge, first-principles–based numerical simulations are emerging as an attractive alternative to produce a complementary data source along with experiments. Leveraged by the unprecedented computing power offered by state-of-the-art supercomputers, direct numerical simulation (DNS), coupled with interface tracking methods, is becoming a practical tool to investigate some of the most challenging engineering flow problems. In the presented research, turbulent bubbly flow is simulated via DNS in single PWR subchannel geometries with auxiliary structures (e.g., supporting spacer grid and mixing vanes). The geometric effects these structures exert on the bubbly flow are studied with both a conventional time-averaging approach and a novel dynamic bubble tracking method. The new insights obtained will help inform better two-phase models that can contribute to safer and more efficient nuclear reactor systems.

Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of subcooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single- and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. These simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

Bubble tracking analysis of PWR two-phase flow simulations based on the level set method

Bubbly flow is a common natural phenomenon and a challenging engineering problem yet to be fully understood. More insights from either experiments or numerical simulations are desired to better model and predict the bubbly flow behavior. Direct numerical simulation (DNS) has been gaining renewed interests as an attractive approach towards the accurate modeling of two-phase turbulent flows. Though DNS is computationally expensive, it can provide highly reliable data for model development along with experiments. The ever-growing computing power is also allowing us to study flows of increasingly high Reynolds numbers. However, the conventional simulation and analysis methods are becoming inadequate when dealing with such ‘big data’ generated from large-scale DNS. This paper presents our recent effort in developing the advanced analysis framework for two-phase bubbly flow DNS. It will show how one can take advantage of the ‘big data’ and translate it into in-depth insights. Specifically, a novel bubble tracking method has been developed, which can collect detailed two-phase flow information at the individual bubble level. Due to the importance of subcooled boiling phenomenon in pressurized water reactors (PWR), the bubbly flow is simulated within a PWR subchannel geometry with the bubble tracking capability. It has been demonstrated that bubble tracking method significantly improves the data extraction efficiency for level-set based interface tracking simulations. Statistical analysis was introduced to post-process the recorded data to study the dependencies of bubble behavior with local flow dynamics.

強制対流サブクール沸騰の数値解析における気泡の伝熱面離脱条件の影響

Numerical simulation of subcooled flow boiling in a vertical rectangular duct was carried out using a one-way bubble tracking method; this method treats each bubble as an individual particle. Although a bubble behavior after lifting off the heated surface depends on the bubble size and velocity at lift-off, these lift-off conditions are not taken into consideration in existing subcooled flow boiling models. In the present simulation, the distributions of lift-off velocity and bubble size were considered. It was demonstrated that the calculated void fraction in subcooled flow boiling is influenced significantly by the lift-off conditions.

NUMERICAL MODELS FOR SIMULATION OF CAVITATION IN DIESEL INJECTOR NOZZLES

This paper examines the applicability of the following three different combinations of cavitation models to simulate cavitating flows in a nozzle of liquid fuel injector for diesel engines. The first model in a house code consists of the Lagrangian bubble tracking method (BTM), the Rayleigh-Plesset (RP) equation, and large eddy simulation (LES). The second model is the combination of the homogeneous equilibrium model (HEM), a barotropic (Baro) equation, and the RANS turbulence model (k-ω SST). The last one utilizes HEM, RANS (k-ε, k-ω SST), and the mass transfer model (MTM), in which bubble dynamics is calculated by the simplified RP equation. OpenFOAM is used for the simulations with the second and third models. Unsteady cavitation in a rectangular injector nozzle is captured by a high-speed camera and the turbulent velocity in the nozzle is measured by laser Doppler velocimetry (LDV); they are compared with the numerical results. As a result, the following conclusions are obtained. The BTM/RP/LES model gives a good prediction for the cavitation length and thickness, as well as cavitation cloud shedding. However, it requires a fine grid and a long CPU time, and is applicable only to incipient cavitation. The HEM/Baro/RANS approach results in a wrong prediction for cavitation length and thickness, and underestimation of the turbulence velocity. It cannot reproduce unsteady cavitation behavior. The combination of HEM/MTM/RANS gives good prediction for the cavitation length and thickness with a relatively coarse grid, and therefore with a short CPU time.

Numerical simulation of incipient cavitation flow in a nozzle of fuel injector

Cavitation clouds shedding in a nozzle of fuel injector for Diesel Engines play a dominant role in the fuel spray atomization process and the subsequent spray combustion. Since a high speed cavitation flow in a tiny nozzle with a complicated geometry is not easy to be visualized and measured, large efforts have been paid to carry out numerical simulations of the transient cavitating flow in the nozzle. Most of the previous simulations are based on the Homogeneous Equilibrium Model (HEM), a simplified bubble dynamics model or a barotropic equation, and the Reynolds-Averaged Navier–Stokes (RANS) turbulence model, which do not predict the cavitation cloud shedding. Cavitation in the nozzle takes various forms, such as a transparent cavitation sheet and clouds of cavitation bubbles, which makes its prediction difficult. As a first step to develop a cavitation model which can accurately treat both the sheet and cloud cavitations, in this study we propose a new combination of Large Eddy Simulation (LES), Eulerian–Lagrangian Bubble Tracking Method (BTM), and the Rayleigh–Plesset (RP) equation to simulate an incipient cavitation, in which only cavitation bubble clouds appear. A precursor simulation of a fully developed turbulent flow in a channel, in which periodic boundary condition is adopted for the inlet and exit, is carried out to generate inlet boundary condition for a nozzle simulation. To verify the validity of the model, transient cavitation motion and turbulent velocity in a rectangular nozzle are acquired by using a high speed camera and Laser Doppler Velocimetry (LDV). As a result, a recirculation flow and a cavitation cloud shedding are accurately predicted by LES using a fine grid, and the RP equation for all nuclei tracked in a Lagrangian manner.

BUBBLE TRACKING SIMULATION OF BUBBLE-INDUCED PSEUDOTURBULENCE

Bubble tracking simulations of bubbly flows in a rectangular column are carried out to examine the applicability of a bubble tracking method to flows involving the bubble-induced pseudoturbulence. Experimental data of void fraction, mean liquid and bubble velocities, and liquid fluctuation velocity are obtained for validation. As a result, the following conclusions are obtained: (1) The order of liquid fluctuation velocity is similar to that of the bubble relative velocity, and the fluctuation is well scaled in terms of the bubble terminal velocity and the void fraction, as Risso & Ellingsen suggested [J. Fluid Mech., vol. 440, pp. 235-268, 2001]. (2) The Reynolds shear stress is not produced by the bubble motion when both void fraction and liquid velocity are uniform. (3) The Reynolds stress model proposed by Lopez de Bertodano et al. [Int. J. Multiphase Flow, vol. 20, pp. 805-818, 1994] underestimates the normal stress, whereas the bubble tracking simulation with a spatial resolution comparable to the bubble size gives better predictions than the model. (4) The fluctuation in liquid velocity induced by bubbles is partly resolved with a spatial resolution comparable to the bubble size, and subgrid turbulence models do not have much influence on predictions. (5) Eddy viscosity models would be a reasonable choice to capture the shear-induced turbulence in the near-wall region in bubble tracking simulations with an inevitably insufficient spatial resolution for large eddy simulation.

Numerical Simulation of Bubble Motion about a Grid Spacer in a Rod Bundle

Numerical simulations based on a three-dimensional two-way bubble tracking method are carried out to predict bubble motions in a square duct with an obstacle and in a two-by-three rod bundle with a grid spacer. Comparisons between measured and predicted bubble motions demonstrate that the two-way bubble tracking method gives good predictions for trajectories of small bubbles in the upstream side of the grid spacer in the rod bundle geometry. The predicted bubble trajectories clearly show that bubbles are apt to migrate toward the rod surface in the vicinity of the bottom of the grid spacer. Analysis of forces acting on the bubbles confirms that pressure gradient force induced by the presence of the spacer is the main cause of the bubble lateral migration toward the rod surface. Motions of steam bubbles at a nominal operating condition of a pressurized water reactor (PWR) are also predicted by using the bubble tracking method, which indicates that steam bubbles also migrate toward the rod surface at the upstream side of the spacer due to the spacer-induced pressure gradient force.

Development of Three-Dimensional One-way Bubble Tracking Method for Boiling Flow

A three-dimensional one-way bubble tracking method is a promising numerical method for calculation of time-spatial evolution of gas-liquid interfacial configuration with use of a little computing resource. Since the method has been applied to only an adiabatic air-water bubble flow, the method is developed for the analysis of a boiling flow in this study. One-dimensional Eulerian equation of energy conservation for a continuous liquid phase and an interface heat transfer equation for dispersed bubbles are introduced. Then, radial liquid temperature distribution, wall heat transfer between a heated wall and subcooled liquid, bubble generation on a heated wall and expansion or condensation of bubbles are taken into account. The developed method is applied to the boiling flow experiment and radial void fraction distribution is compared. It is confirmed that the method can give good prediction of tendency of the void fraction distribution in the boiling flow.

Bubble Dissolution of CO2-Water Two Phase Bubbly Flows in a Vertical Pipe

Spatial evolution of radial void and bubble size distributions in CO2-water gas-liquid bubbly flows in a vertical pipe were measured using a conductivity probe and an image processing method. Numerical simulations were carried out using a three-dimensional one-way bubble tracking method with a mass transfer model, which takes into account the accumulation of surfactants on bubble surface and the absorption and desorption of gas components. As a result, the following conclusions were obtained: (1) the decreasing rate of the total gas volume decreases in the flow direction due to the desorption of N2 and O2, the accumulation of surfactants and the bubble volume expansion due to the decrease in static pressure, and (2) the bubble tracking method gave good predictions for the bubble dissolution process in CO2-water bubbly pipe flows.

Use of a Bubble Tracking Method for Prediction of Downhole Natural Separation Efficiency

For any pumping artificial lift system in the petroleum industry, the free gas significantly affects the performance of the pump and the system above the pump. A model, though not a complete two-phase flow model, has been developed for the effective prediction of separation efficiency across a wide range of production conditions. The model presented is divided into two main parts, the single-phase flow-field solution and the bubble-tracking method. The first part of the model solves the single-phase liquid flow field using the computational fluid dynamics approach. Then, a simple bubble-tracking method was applied to estimate the down-hole natural separation efficiency for two-phase flow. A comparison between the results of the model and the experimental data was conducted. It shows a very good agreement with the experimental data for lower gas void fractions (bubble flow regime).