Gas-liquid Two-phase Flow Research Articles

A re-optimized design of mesh-type transition zone for large-scale PEM fuel cells considering two-phase flow distribution

The flow distribution in the Flow Field Plate (FFP) has a significant impact on the performance and durability of large-scale Proton Exchange Membrane (PEM) fuel cells. Most of the existing studies focused only on gas-phase flow, while the actual cell operation is gas-liquid two-phase flow. In this study, numerical simulations of single- and two-phase flow distributions are performed for three-dimensional FFPs. The Coefficient of Variation (CV), defined as the ratio between the standard deviation and the mean of the velocities in channels, serves as the indicator of flow uniformity. Firstly, the differences between gas- and two-phase flow distribution characteristics of the FFP with the combined-mesh-type transition zone we previously constructed are elucidated. Secondly, a re-optimized layout with horizontal mesh apertures in the distribution zone and the addition of horizontal mesh in the collection zone is proposed. The design philosophy and methodology based on the coupled flow and resistance regulation mechanism are elucidated. The single- and two-phase CV values are further reduced by 41.25% and 6.05%, respectively. Thirdly the re-optimized structure is applied to different FFP geometries, including smaller development spaces and larger cell areas, where the superior effects on flow distribution are validated.

A flow rate estimation method for gas–liquid two-phase flow based on filter-enhanced convolutional neural network

Accurate estimation of flow rate in gas–liquid two-phase flow is crucial for various industrial processes. How to accurately estimate flow rate remains a challenging problem. Previously, deep learning-based methods focused on a few human-set points with single task learning. In addition, the data were not denoised. In this study, a flow rate estimation method based on a filter-enhanced convolutional neural network (FECNN) is proposed for gas–liquid two-phase flow. The method leverages multimodal data from a Venturi tube and an electrical capacitance tomography (ECT) sensor as input, utilizing multilayer perceptron (MLP) to fuse data. Subsequently, a learnable filter module is employed to attenuate noise adaptively, followed by multiscale convolutional neural network (MSCNN) extraction of flow rate features at different scales. Finally, the method enables estimate each single-phase flow rate simultaneously through multi-task learning (MTL). The adaptive noise attenuation capabilities of the learnable filter module are demonstrated, and the ability of the proposed MSCNN to capture multiscale flow rate features through multiple comparative experiments is shown. Additionally, a qualitative comparison with recent flow rate estimation methods is provided. Overall, this study demonstrates the effectiveness and superiority of the proposed FECNN in flow rate estimation.

Simulation Analysis of the Annular Liquid Disturbance Induced by Gas Leakage from String Seals During Annular Pressure Relief

Due to the failure of string seals, gas can leak and result in the abnormal annulus pressure in gas wells, so it is necessary to relieve the pressure in gas wells. In the process of pressure relief, the leaked gas enters the annulus, causes a the great disturbance to the annulus flow field, and thus reduces the protection performance of the annular protection fluid in the string. In order to investigate the influence of gas leakage on the annular flow field, a VOF finite element model of the gas-liquid two-phase flow disturbed by gas leakage in a casing was established to simulate the transient flow field in the annular flow disturbed by gas leakage, and the influences of leakage pressure differences, leakage direction, and leakage time on annular flow field disturbance and wall shear force were analyzed. The analysis results showed that the larger leakage pressure difference corresponded to the faster diffusion rate of the leaked gas in the annulus, the faster the flushing rate of the leaked gas against the casing wall, and a larger shear force on the tubing wall was detrimental to the formation of the corrosion inhibitor film on the tubing wall and casing wall. Under the same conditions, the shear action on the outer wall of tubing in the leakage direction of 90° was stronger than that in the leakage directions of 135° and 45° and the diffusion range was also larger. With the increase in leakage time, leaked gas further moved upward in the annulus and the shear effect on the outer wall of tubing was gradually strengthened. The leaked acid gas flushed the outer wall of casing, thus increasing the peeling-off risk of the corrosion inhibitor film. The study results show that the disturbance law of gas leakage to annular protection fluid is clear, and it was suggested to reduce unnecessary pressure relief time in the annulus to ensure the safety and integrity of gas wells.

Examination on behavior of tip leakage flow in a three-stage gas-liquid two-phase flow pump

Examination on behavior of tip leakage flow in a three-stage gas-liquid two-phase flow pump

A Sensitive Frequency Band Study for Distributed Acoustical Sensing Monitoring Based on the Coupled Simulation of Gas–Liquid Two-Phase Flow and Acoustic Processes

The sensitivity of gas and water phases to DAS acoustic frequency bands can be used to interpret the production profile of horizontal wells. DAS typically collects acoustic signals in the kilohertz range, presenting a key challenge in identifying the sensitive frequency bands of the gas and water phases in the production well for accurate interpretation. In this study, a gas–water two-phase flow–acoustic coupling model for a horizontal well is developed by integrating a gas–water separation flow model with a pipeline acoustic model. The model simulates the sound pressure level (SPL) and amplitude variations of acoustic waves under different flow patterns, spatial locations, and gas–water ratio schemes. The results demonstrate that within the same flow pattern, an increase in the gas–water ratio significantly elevates acoustic amplitude and SPL peaks within the 5–50 Hz frequency band. Analysis of oil field DAS data reveals that the amplitude response range for stages with a lower gas–water ratio falls within 5–10 Hz, whereas stages with a higher gas–water ratio exhibit an amplitude response range of 10–50 Hz.

An entropy measure-based study on flow pattern of gas–liquid two-phase flow in a U-Tube

U-tubes are widely applied in gas–liquid two-phase transportation in chemical engineering. The diverse flow patterns within these tubes significantly affect the pressure loss, heat transfer efficiency, and even the fluid-induced vibration amplitude of the tubes. This study explores the complex flow pattern features in a U-tube in a vertical plane and focuses on recognizing them. For the acquisition and classification of flow patterns, a Computational Fluid Dynamics (CFD) model for gas–liquid two-phase flow is first established, and its quantitative calculation error is ensured to be less than 5%. Then, the spatiotemporal evolution characteristics of flow patterns is analyzed. The real-time pressure drop response is chosen as the representation signal, and its nonlinear features in the time and frequency domain under different flow patterns are explored. A nonlinear time series is constructed by extracting a segment from the real-time pressure drop data, and six entropy measures are applied to analyze and identify them. Finally, the sensitivity of entropy measures to both the time series lengths and the tested sections are evaluated. Results show that there are six typical flow patterns in a U-tube. According to most entropy measures, the bubble flow has the highest complexity; however, the plug flow presents the lowest complexity. In the U-bend, pressure drop signals for the bubble and annular flows show random fluctuations within a specific range, in contrast to the marked periodicity in plug flow signals, while wavy and slug flows exhibit intermittent peak values. Including the upstream and downstream straight pipes in the analysis, rather than focusing solely on the U-bend, significantly increases the complexity of the stratified, plug, and slug flows. Fuzzy entropy is an effective tool for identifying the six flow patterns, demonstrating good resilience to variations in the length of the data series. This characteristic makes it highly useful for real-time identification of flow patterns in the U-bend sections of non-transparent U-tubes, offering considerable potential in chemical equipment.

Determination of grout compactness in rebar grouted splice sleeves using frequency domain characteristics of the excitation process

Grouted splice sleeves are widely used in assembly building connections. However, void defects within the sleeve directly affect the load-bearing capacity of the building structure. This paper presents a new method for detecting void defects inside a grouted splice sleeve based on the frequency domain characteristics of mechanical vibration waves. This method analyses the grouted spliced casing containing void defects as a gas-liquid two-phase flow system. To confirm the validity of the method, this paper builds a test setup for testing. The results showed that the test method can effectively detect the void defects and the volume of the defects inside the grouted splice sleeves when the grout is not solidified.

Study on the Spatio-temporal Evolutionary Properties of Gas-liquid Two-phase Flow in Centrifugal Pump as Turbine (PAT)

With the increasing complexity of the industrial production process, the transmission medium of the hydraulic turbine is no longer satisfied, and the gas-liquid two-phase mixed medium has to be considered. The presence of gas in the transmission medium will alters the internal flow structure of the hydraulic turbine and affect its operational stability. Therefore, for the purpose of clarifying the influence of inlet gas content on the internal flow of PAT, the unsteady flow of the PAT is simulated in this paper using numerical simulation. Based on the numerical simulation results, the influence of inlet gas content on the internal flow characteristics, characteristics of pressure fluctuation in impeller and volute, and vortex evolution of flow field are analyzed. The accumulation of gas phase leads to the emergence of vortices, and regions with low pressure values appear at the vortex generation. The major factor of the periodic variation of pressure fluctuation between volute and cut-water is the dynamic and static interference of impeller. The increase of gas content causes more flow disorder in the cut-water region and the volute contraction section. Since the gas in the flow channel is predominantly on the suction side of blades, the flow field on the suction side is more complex than that on the pressure side, and the amplitude of pressure fluctuation increases appropriately. The vortex structure is mainly distributed on balance hole, inlet area of impeller and suction side of blade. As the blade rotates, there are new shedding and growth of vortices, and finally attached to the volute wall. Increasing gas content enhances the influence of blade rotation on the vortex evolution characteristics in the volute and impeller.

On hydromagnetic two-phase gas-liquid flow in ciliary channel: An application of a metachronal rhythm

On hydromagnetic two-phase gas-liquid flow in ciliary channel: An application of a metachronal rhythm

Study on the Impact of Porous Media on Condensate Gas Depletion: A Case Study of Reservoir in Xihu Sag.

During the depletion and pressure reduction process in condensate gas reservoirs, the precipitation of condensate oil transforms the single-phase gas flow into a two-phase gas-liquid flow, significantly reducing the permeability. Currently, microscopic studies of the phase behavior of condensate gas in porous media mainly focus on observing and describing the occurrence of condensate oil, lacking quantitative calculations and direct observations of condensate oil throughout the entire depletion cycle. This paper uses a microvisualization method to simulate the depletion process of condensate gas reservoirs. Condensate gases with oil contents of 175.3 and 505.5 g/cm3 were prepared by mixing methane, ethane, hexane, and decane in specific proportions. Pore structures were extracted from thin sections of real core casts, and microfluidic chips with a minimum pore diameter of 20 μm and an areal porosity of 20.75% were fabricated by using a chemical wet etching method. Subsequently, microfluidic condensate gas depletion experiments were conducted with chip images recorded during the depletion process. Grayscale analysis of the depletion images was performed using ImageJ software to quantitatively calculate condensate oil saturation and recovery rates, analyzing the effects of different condensate oil contents on condensate gas depletion, and comparing the differences between depletion in porous media and in a PVT cell. The conclusions drawn are as follows: the dew points of high and low in the porous media are 3.15% and 1.85% higher than those in the PVT cell, respectively. In the early stages of depletion, condensate oil saturation in porous media is higher than that in the PVT cell, while in the middle to late stages, condensate oil saturation in porous media is lower than that in the PVT cell. The condensate oil recovery rate in porous media is significantly higher than the depletion recovery rate in the PVT cell. Condensate oil tends to precipitate and disperse at blind ends and corners, while it easily forms patches in mainstream large pores.

Study on Atomization Mechanism of Oil Injection Lubrication for Rolling Bearing Based on Stratified Method

The atomization mechanism of lubrication fluid in rolling bearings under high-speed airflow between the rings was investigated. A simulation model of gas–liquid two-phase flow in angular contact ball bearings was developed, and the jet lubrication process between the bearing rings was simulated using FLUENT computational fluid dynamics software (Ansys 19.2). The complex motion boundary conditions of the rolling elements were addressed through a layered approach. We can obtain more accurate boundary layer flow field changes and statistics of the diameter of oil particles in lubricating oil atomization, which lays the foundation for analyzing the law of influence on lubricating oil atomization. The results show that as the number of boundary layer layers increases, the influence of the boundary layer flow field on the lubricating oil is more obvious. The oil particle size is excessively flat, and the concentration of large particles of oil appears to decrease. As the speed increases, the amount of oil in the cavity decreases, but the oil droplets are also fragmented, which intensifies the atomization and reduces the particle diameter. This reduces the Sauter Mean Diameter (SMD), which is not conducive to the lubrication of the bearing. Under different injection pressures, when the injection pressure is large, it is beneficial to the lubrication of the bearing.

Identification of gas-liquid two-phase flow patterns based on flexible ultrasound array and machine learning

Ultrasound technology has been recognized as the mainstream approach for the identification of gas-liquid two-phase flow patterns, which holds great value in engineering domain. However, commercial rigid probes are bulky, limiting their adaptability to curved surfaces. Here, we propose a strategy for autonomous identification of flow patterns based on flexible ultrasound array and machine learning. The array features high-performance 1–3 piezoelectric composite material, stretchable serpentine wires, soft Eco-flex layers and a polydimethylsiloxane (PDMS) adhesive layer. The resulting ultrasound array exhibits excellent electromechanical characteristics and offers a large stretchability for an intimate interfacial contact to curved surface without the need of ultrasound coupling agents. We demonstrated that the flexible ultrasound array combined with machine learning can accurately identify gas-liquid two-phase flow patterns, in a circular pipeline. This work presents an effective tool for recognizing gas-liquid two-phase flow patterns, offering engineering opportunities in petroleum extraction and natural gas transportation.

Two-group drift-flux model in tight lattice subchannel

Tight lattice rod bundles can increase equipment compactness and improve heat exchange efficiency, and they are widely adopted in heat exchange engineering. Understanding the flow characteristics of gas-liquid two-phase flow in tight lattice subchannels is essential for developing heat exchangers and fuel assemblies with these tight bundles. The drift-flux model (DFM) is a crucial two-phase flow model extensively used in subchannel analysis codes. Investigating the DFM in tight lattice subchannels benefits the advancement of these codes. For two-phase flow interfacial structures, significant two-group characteristics exist, with bubbles divided into small (group-one) and large (group-two) bubbles. The substantial differences in flow characteristics between these two groups provide a solid foundation for developing a two-group DFM. This study examined the two-group characteristics of two-phase flow in a tight lattice interior subchannel and developed a corresponding two-group DFM. The two-group correlations for the distribution parameters and drift velocities at the tight lattice interior subchannel level were proposed and verified using experimental data. The accuracy of the developed two-group DFM in predicting group-wise void fraction and gas velocity was also verified. The standard relative deviation between the model predictions and experimental data was 8.11 % and 13.1 % for group-one and group-two void fractions and 8.33 % and 11.7 % for group-one and group-two gas velocities, respectively. This indicates satisfactory accuracy for the newly developed two-group DFM in a tight lattice interior subchannel.

Development and validation of a 1D gas–liquid model for dissolved Mn(II) removal by oxidation process in a square bubble column

Modeling multiphase reactors requires an in-depth multidisciplinary analysis of various phenomena including the chemical kinetics, oxygen mass transfer, as well as the simulation of flows within these contactors. In this study, a 1D model of two-phase flow for Mn(II) removal from drinking water by aeration process is developed and validated. This model is based on the Eulerian description of two-phase gas–liquid flow with the comparison between a one-medium bubble size and a two-bubble class description to represent the bubble population in the heterogeneous flow regime. All the relevant chemical species are simulated by coupling hydrodynamics, gas–liquid mass transfer, and reaction kinetic. A pseudo-first-order model accounting for homogeneous and heterogeneous kinetics is considered for Mn(II) oxidation. The performance of the developed 1D model is compared and validated with experimental data. The 1D model was able to predict quantitatively Mn oxidation as a function of pH, initial Mn(II) and initial Mn(IV) concentrations.

Gas liquid flow pattern prediction in horizontal and slightly inclined pipes: From mechanistic modelling to machine learning

This paper investigates the prediction of two-phase gas-liquid flow regimes in both horizontal and slightly inclined pipes. For this purpose, the mechanistic model of Taitel et al. (1976) and the machine learning approach have been adopted. First, the mechanistic model was implemented, tested and optimised by introducing factors in the transition equations to determine the configuration that gives the highest prediction accuracy for a specific two-phase system for which experimental data points are available. Second, several machine learning models are trained, tested and additionally validated. This is done by splitting the experimental data set corresponding to the pipe inclination range (−10∘ to 10∘) into training, test and validation sets. The best classifier achieved an accuracy of 95.5% after the test step and up to 98.9% after the validation step. Finally, the Taitel et al. model with the optimal configuration and the best machine learning classifier (XGB classifier) are used to generate the two-dimensional flow regime map.

Investigating of vibration and noise characteristics in two-phase gas-liquid flow through a spiral capillary tube

The vaporization of refrigerant in the liquid-phase in spiral capillary tube induces complex two-phase flow that causes vibrations and noise, which affect the performance and stability of refrigeration systems. Therefore, the flow patterns, vibrations, flow-borne and structure-borne noises in spiral capillary tube are explored, and the effects of coil diameters, pitches and temperatures are analyzed. The results showed that the flow upstream the vaporization point was dominant by liquid-phase, then changed to bubbly flow downstream the vaporization point under various structures, and further changed to mist flow near the outlet, while it changed to gas-phase flow near the outlet under high temperature. The flow-borne noise was mainly affected by the flow turbulence, and the total sound pressure level (TSPL) increased by 17.1 % on average as the temperature increased from 309.6 to 317.6 K, and rose with the increase in pitch. As the coil diameter increased, the TSPL first increased and then decreased. Moreover, the maximum deformation of structure increased by 58.33 % as the diameter increased from 35 to 50 mm, but changed little with various pitches. The changing trends of vibration intensity caused the similar variations of structure-borne noise. The TSPL of structure-borne noise increased by 9.14 % with the diameter increasing from 35 to 50 mm, but it changed little at various pitches. The TSPL of structure-borne noise was much higher than flow-borne noise, which meant that improving the structural vibration can control the noise of refrigerant flow in spiral capillary tube.

Numerical study of proton exchange membrane water electrolyzer performance based on catalyst layer agglomerate model

In this work, a two-dimensional two-phase model of proton exchange membrane water electrolyzer (PEMWE) is developed, in which the catalyst layer (CL) is represented using agglomerate model. The effects of CL composition, porous transport layer (PTL) material properties and operating conditions on PEMWE performance are investigated. The results indicate that small size of catalyst agglomerate around 0.25 μm would benefit PEMWE performance. Appropriate increase of catalyst loading, porosity and ionomer volume fraction in the CL improves PEMWE performance, but their further increment leads to high mass transfer resistance, limiting the improvement of electrolyzer performance. The porosity and ionomer volume fraction of the catalyst layer are suggested to be lower than 0.5 and 0.6, respectively. The catalyst loading should be lower than 1.5 mg cm−2 when the CL porosity is higher than 0.3. The PTLs with high permeability, porosity and low contact angle is beneficial for the gas–liquid two-phase flow and avoiding the overheat and water shortage in the electrolyzer. Increasing the inlet velocity accelerates the bubble removal process, but might results in significant temperature drop, degrading the PEMWE performance. The most suitable temperature of inlet liquid is around 353.15 K. The results provide important guidance for the optimization design of high-performance PEMWE.

Characteristics of gas–liquid two-phase flow in a stirred tank with double-layer punched impeller

This study investigates the gas–liquid two-phase flow characteristics in a stirred tank equipped with a double-layer punched impeller. Numerical simulations are conducted to analyze flow dynamics, gas holdup, bubble sizes, and distributions under various operational conditions. The results show a high degree of agreement between experimental and simulated power values and gas holdup distributions, validating the reliability of the computational fluid dynamics–population balance model coupling approach. The combination of the punched four-inclined-blade up-pumping turbine and the punched Rushton impeller exhibits excellent bubble dispersion characteristics, with overall small bubble sizes. Increasing the rotational speed can enhance turbulence within the flow field and accelerate the liquid phase velocity, which facilitates gas diffusion and improves gas–liquid mixing efficiency. Additionally, higher rotational speed further intensifies the shear effect of the punched impeller, resulting in a reduction in average bubble size.

Experimental investigation of a novel gas-liquid homogenizer methodology for ESP in high GVF flow applications

This paper presents a new homogenizer for Electric Submersible Pumps (ESP). Experiments were carried out using a two-stage radial-type pump with perforated vanes running at 3400 RPM. A test rig was designed to measure pressure and observe flow patterns. Results showed excellent performance for intake GVF ranging from 25 % to 89 %. Using the proposed homogenizer in the multistage ESP improves pump performance for gas-liquid mixtures. The study explored parameters to improve pump performance in high GVF conditions. The proposed homogenizer is more cost-effective and efficient by integrating into the existing pump stage and allowing customizable perforations. This design flexibility improves performance while avoiding the need for extra space or components. Moreover, numerical simulations with a helico-axial rotating multiphase pump and ANSYS-CFX software were conducted to prove the concept numerically. The focus was on gas-liquid two-phase flow and the effects of inlet GVFs. Modifications to the impeller blades, such as grooves, slits, or holes, were designed to enhance performance. The study found that CFD simulations accurately predict pump performance and that modified impellers improve performance in specific GVF ranges.

Investigation of Backpressure Wave Propagation Properties during Gas Kicks in Managed Pressure Drilling

Summary It is often essential to provide backpressure to the wellbore by changing the opening size of the choke valve when a gas kick is detected during managed pressure drilling (MPD), which maintains the pressure in the bottom of the hole. In this study, a mathematical model was developed to explain how backpressure waves spread and weaken in a wellbore during MPD when there is a gas-liquid two-phase flow. The model is founded on a two-phase flow model, which thoroughly accounts for the gravity, shear force, and interphase interactions between the gas and liquid phases. The small perturbation theory was used to compute the backpressure wave’s propagation speed and attenuation coefficient. The outcome showed satisfactory agreement with other scholars’ experimental results. The model was used to study the impacts of the following variables on the backpressure wave propagation properties: void fraction, temperature, pressure, interphase resistance, shear force, density, invading gas composition, displacement of the drilling fluid, rate of intrusion of gas, gas-liquid surface tension, and drilling fluid viscosity. By using an example well, the laws of pressure wave propagation speed, attenuation coefficient, and propagation time with well depth were analyzed. Through evaluative methods in the field of economic management, the principal control variables governing the propagation of backpressure waves were determined. The conclusion is that, in terms of operational feasibility, lower drilling fluid density and reduced drilling fluid displacement are advantageous for a faster propagation of backpressure waves to the bottom of the well.