Two-phase Flow In Pipelines Research Articles

Attachment detection on the inner wall of gas-liquid two phase flow pipe based on ultrasonic guided waves

Gas-liquid two-phase flow pipelines are commonly found in building thermal systems. However, the attachment on the inner wall of the pipeline brings great safety hazards to the system. At present, ultrasonic guided wave technology has been widely used for the structural inspection of pipelines. The boundary conditions significantly affect the propagation characteristics of ultrasonic guided waves and the detection accuracy. Therefore, this paper investigates the influence of the flow pattern on the propagation characteristics of guided waves using semi-analytical finite element method and proposes an excitation frequency selection method independent of the flow pattern to improve the accuracy of the detection of attachments in gas-liquid two-phase flow pipelines. The relationship between the attachment size and the reflection echo characteristics is analyzed. Numerical simulation and experimental results show that the flow pattern leads to the modal coupling phenomenon of the L(0,1) guided wave, and the modes vary with the spatial distribution of the gas plug. The attachment echo contains not only the attachment information but also the position of the gas plug in the fluid. Finally, the maximum error of the attachment position accuracy in two-phase flow pipes with different flow patterns is no more than 3 %. An innovative dispersive surface result reflecting the changes in the propagation characteristics of UGWs along a pipe with changing cross-section (plug flow) is established.

Experimental Study on Gas-Liquid Two-Phase Stratified Flow at High Pressure in a Horizontal Pipe

This study investigates wave-stratified flow in a horizontal pipe at high pressure, and flow characteristics are obtained, such as flow pattern map, liquid film thickness, and pressure drop. Compared with a flow pattern map of a gas-liquid two-phase flow carried out at atmosphere, stratified flow zone is depressed with increasing system pressure and the critical gas superficial velocity decreases for smooth-wave-stratified flow transition, while the critical liquid superficial velocity increases for stratified-intermittent transition. On one hand, the compressed air results in an increase in momentum transfer between gas and liquid phases, which accounts for the smaller gas superficial velocity that is encountered in both smooth-wave and stratified-annular flow transition at higher pressure. One the other hand, it slows down the liquid below the crest, and it makes the interface wave crest unstable and split for the vortex shedding behind the wave crest, which accounts for flow regime transition in gas-liquid two-phase flows in pipelines. As a result, stratified-intermittent flow transition is depressed and delayed. The pressure influence on the liquid film profile is analyzed, and relationships between film thickness and dimensionless numbers are studied, such as liquid Weber number and gas Weber number. Friction factors on different interfaces at high pressure are studied, and new empirical formulas are deduced.

Development of artificial neural networks for the prediction of the pressure field along a horizontal pipe conveying high-viscosity two-phase flow

Pressure fluctuations are one of the primary concerns regarding the safety of two-phase flows in pipelines. Therefore, it is crucial to closely monitor pressure variations and predict their spatiotemporal behavior to the greatest extent possible. In this article, we present the development of a set of models based on artificial neural networks (ANN) to predict the time-dependent behavior of the pressures produced by high-viscosity gas-liquid flows at predetermined locations along a horizontal pipeline. Different volume fractions of glycerin and air constitute the mixtures of interest. The models use the measured values of the mass-flow rates of both fluids at the pipe’s inlet, together with the pressures measured at other locations further downstream. In order to determine the optimal architecture for the artificial neural network, we tested the following four transfer functions for the hidden layer: logsig, tansig, softplus, and swish. Additionally, we utilized the linear function purelin for the output layer. We employed the Levenberg–Marquardt algorithm to train the ANN models and the experimental data set to test their performance.

Scaling two-phase gas-liquid flow in horizontal pipes

Two-phase flow in pipelines is analyzed by experimental facilities and also numerical analysis. The experimental facilities are designed by scale-down field pipelines. Therefore, the accuracy of experimental data is strongly dependent on the scaling method. In this research, an approach for downscaling field pipelines into experimental facilities is proposed. The fluid flows in different scales for various flow patterns including Stratified, Stratified Wavy, Slug, Plug and Bubbly are numerically simulated and validated against full-scale experimental data. The results of the scaled-down model simulation are in excellent agreement with the full-scale facilities, affirming the robustness of the downscaling method. This research enhances the understanding of scaled-down experiments for various flow conditions.

Flow regime and critical deposition velocity of liquid–solid two-phase flow in pipeline: Progress and perspectives

Pipeline liquid–solid two-phase flow is a significantly important multiphase flow phenomenon widely encountered in both industrial and natural settings. The flow regime of liquid–solid two-phase flow in pipelines plays a crucial role as it represents the macroscopic manifestation of the suspension diffusion mechanism and the slip deposition law of solid particles. This paper provides an overview of research related to flow regimes and critical deposition velocity (CDV) in liquid–solid two-phase flow in pipelines. After briefly reviewing pioneering theoretical research in this field, the paper focuses on recent research in flow regime identification and prediction using state-of-the-art experimental methods and techniques. The review also rigorously assesses the reliability and validity of the methods, results, and conclusions related to the establishment of the CDV, identifying the deficiencies in the current research. Drawing on dimensional analysis and Pearson correlation analysis, the particle Reynolds number is introduced to establish a highly accurate correlation for predicting the CDV under conditions of wide volume concentration. The new correlation yields a mean absolute percentage error of 9.23% and a root mean square error of 10.29% within the volume concentration range of 0.7%–50.8%. This paper aims to provide clear guidance to researchers and professionals in related industries, enabling them to conduct more in-depth investigations according to their research interest and enhance their understanding of liquid–solid two-phase flow systems within pipelines.

MFCC-LSTM framework for leak detection and leak size identification in gas-liquid two-phase flow pipelines based on acoustic emission

Two-phase gas–liquid flows are crucial to the pipeline system. Due to their complicated flow state, existing leak detection techniques are unsuitable for two-phase flow pipelines. To avoid accidents caused by a leak of pipelines, we present a framework for combining the Mel-frequency cepstral coefficient and long short-term memory (MFCC-LSTM) based on acoustic emission (AE). A series of experiments are performed considering 1152 operating conditions, including flow pattern, leak size, direction, and location. In addition, the detection capability of the different features of AE signals combined with LSTM is discussed. The results show that the recognition accuracy of the MFCC-LSTM framework reaches 98.4%. Then, we further perform leak size identification under different flow patterns and found that the MFCC-LSTM framework still exhibits excellent performance. The proposed MFCC-LSTM framework provides a promising solution to identify the leak state and size in two-phase flow pipelines based on the AE technique.

Study on a Numerical Model of Hydrate Bed Critical Velocity in Solid–Liquid Two-Phase Flow Pipelines

A hydrate bed critical velocity model is developed, including a hydrate bed limit deposition velocity model and a hydrate bed suspension velocity model. The innovation of this paper is to consider the hydrate bed pressure and liquid bridge force on hydrate particles when building the limit deposition velocity model and to modify Dai’s model by using hydrate experimental and simulation data when building the suspension velocity model. The hydrate bed critical velocity model is negatively correlated with the particle size and positively correlated with the pipe diameter, particle density, and particle volume fraction. The accuracy of the model is demonstrated by validation. The hydrate bed critical velocity model can be used to calculate the hydrate fixed-bed and moving-bed height under different conditions, based on which the flow pattern map of hydrate particles and the hydrate blockage risk classification method are established, which is a certain guidance to ensure the safety of hydrate flow in the pipeline.

Influencing mechanisms of gas bubbles on propagation characteristics of leakage acoustic waves in gas-liquid two-phase flow

Propagation speed of acoustic waves in liquid can be significantly degraded when gas bubbles exist. To reveal the influence of gas bubbles on propagation characteristics of leakage acoustic waves in liquid pipelines, numerical simulation is utilized in the present paper. It can be divided into three stages when leakage acoustic waves propagate through a single gas bubble and the influence of each stage on propagation characteristics of acoustic waves is discussed. In gas-liquid two-phase flow, there are two basic mechanisms of gas resistance on wave propagation: elastic resistance effect and drag resistance effect. The results show that the influence of elastic resistance effect on sound speed is much greater than that of drag resistance effect. When propagating through a long gas bubble with the radius of 2 mm and the length of 7 mm, the elastic resistance effect causes a time delay of 0.00038 s while the drag resistance effect only causes a time delay of 0.00002 s. The results of this paper contribute to better understanding of the differences in acoustic wave propagation characteristics between different flow patterns in gas-liquid two-phase flow, and lay a foundation for the utilization of acoustic leakage detection methods in gas-liquid two-phase flow pipelines.

Research Progress on Numerical Simulation of Heterogeneous Flow Resistance in Sludge Conveying System

Sludge pipeline transportation is increasingly used in different fields. Flow resistance is an important influencing factor in the pipeline transportation of solid-liquid two-phase flow slurry, and studying its characteristics is of great significance for optimizing pipeline design, reducing pipeline erosion and wear, and reducing transportation energy consumption. In view of the complexity of sludge as the resistance characteristics of solid-liquid two-phase flow, it is often necessary to analyze the inline mechanism of solid-liquid two-phase flow in slurry with the help of high-precision turbulent flow model in computational fluid dynamics (CFD), which has become the research focus of heterogeneous solid-liquid two-phase flow pipeline transportation. This paper analyzes and summarizes the CFD simulation status of heterogeneous solid-liquid two-phase flow resistance in pipelines, points out the future research direction, and provides reference for the analysis of heterogeneous flow resistance of sludge pipeline transportation and the optimization design of conveying system.

Measurements of Dispersed Phase Velocity in Two-Phase Flows in Pipelines Using Gamma-Absorption Technique and Phase of the Cross-Spectral Density Function

This paper concerns the application of the gamma radiation absorption method in the measurements of dispersed phase velocity in two-phase flows: liquid–gas flow in a horizontal pipeline and liquid–solid particles in a vertical pipe. Radiometric sets containing two linear 241Am gamma radiation sources and two NaI(Tl) scintillation detectors were used in the research. Due to the stochastic nature of the signals obtained from the scintillation probes, statistical methods were used for their analysis. The linear average velocity of the dispersed phase transportation was calculated using the phase of the cross-spectral density function of the signals registered by the scintillation detectors. It is shown that in the presented cases, the phase method can be more accurate than the most commonly used classical cross-correlation one.

A general numerical method for solid particle erosion in gas–liquid two-phase flow pipelines

A general numerical method is developed to analyse solid particle erosion in gas–liquid mixed pipeline. Tracking particle trajectories is an important intermediate step of the numerical procedure. The present numerical method considers that two factors can affect a particle's trajectory. First, a particle is randomly affected by the gas or liquid phase, and the probability of a certain phase acting is equal to the volume fraction of the phase. Second, surface tension prevents particles from entering the gas phase from the liquid phase and promotes the particles entering the liquid phase from the gas phase. The numerical procedure is well verified by comparison with the experimental data available in the literature. Seventeen cases are used to validate the predicted multiphase flow field and solid particle erosion. In addition, the movement and distribution of particles predicted by the present model are indirectly verified, and the effects of the phase volume fraction and surface tension are discussed in detail.

Effects of particle size and liquid film viscosity on characteristics of particles colliding with dry and wet walls

Particle-wall collisions frequently occur in fluidized beds, granulation processes, and the transportation of gas–solid two-phase flows in pipelines. Exploring the rebound characteristics of particles after colliding with the wall will enable more accurate calculation models of collision rebound, enhanced control of the collision–rebound process, and improved efficiency of industrial production. This paper studies the relationship between the energy consumed by the liquid film and the energy consumed in the collision and investigates the effects of different particle sizes and liquid film viscosities on the liquid bridge morphology, coefficient of restitution (COR), and critical capture angle (CCA). The results show that the normal COR is affected by particle size, incident velocity, and viscosity, while the tangential COR is only related to the existence of the liquid film. Additionally, the maximum size of the liquid bridge and the growth rate of COR change suddenly in a transition region. The particle size and liquid film viscosity have significant effects on the CCA of the particle. The numerical results enable us to propose a general form of the normal wet collision model.

Research and Implementation of Flow Pattern Recognition for Gas-liquid Two-phase Flows Based on GoogLeNet

In order to solve the flow pattern recognition problem of gas-liquid two-phase flow in pipelines, this paper uses high-speed photography to sample the flow patterns of transparent pipe sections and combines the GoogLeNet convolutional neural network model under migration learning to implement a flow pattern recognition method with small samples. In this paper, the GoogLeNet Inception V1 network is used, and the convolutional layer and the pooling layer weights parameters obtained from its training on the imageNet dataset are retained, and the flow pattern samples obtained on the gas-liquid two-phase flow experimental platform are used to train the network model. The recognition accuracy was 98.37% with a training set of 400 and a test set of 100 samples of each flow type. The convolutional neural network directly uses images as data input without operations such as image pre-processing and feature extraction, and its unique fine-grained feature extraction enables the recognition of images by convolutional neural networks at a nearly human level.

CFD-Based Erosion and Corrosion Modeling of a Pipeline with CO2-Containing Gas–Water Two-Phase Flow

A natural gas transportation pipeline with a gas–water two-phase flow containing CO2 is prone to severe flow-assisted corrosion (FAC). The accumulation location of the water phase in the pipeline and the wall shear stress distribution are important factors affecting the severity of this phenomenon. In this work, computational fluid dynamics (CFD) simulations were performed using the realizable k-ε model and volume of fluid (VOF) model to determine the gas–water volume fraction distribution and wall shear stress in a gas–water two-phase pipeline and established a pipeline corrosion prediction model. By determining where the water phase accumulates in the pipeline, the potential corrosion area could be predicted. By alleviating the phenomena of excessive local wall shear stress and bubble cavitation, the FAC due to the formation of stress and acid gas can be controlled. The simulation results lay a certain foundation for the corrosion research of gas–liquid two-phase flow pipelines.

Experimental study on the amplitude characteristics and propagation velocity of dynamic pressure wave for the leakage of gas-liquid two-phase intermittent flow in pipelines

Intermittent flow is one of the most complex flow patterns in gas-liquid two-phase flow in pipelines. The leakage of pipeline intermittent flow poses a threat to the operating safety. In order to improve the application of acoustic method to gas-liquid two-phase leakage detection, the amplitude characteristics and propagation velocity of dynamic pressure wave of intermittent flow for gas-liquid two-phase pipeline leakage were investigated. Experiments with conditions of superficial liquid velocity (vsL) from 0.57 m/s to 1.06 m/s, superficial gas velocity (vsG) from 0.3 m/s to 4.47 m/s, leakage aperture from 4 mm to 9 mm were carried out, and the characteristics were studied by time-domain analysis, frequency-domain analysis and time-frequency analysis. The propagation velocity formula of dynamic pressure wave in two-phase medium was fitted based on Levenberg-Marquardt algorithm, and the propagation velocity of straight pipe and elbow pipe was discussed. The experimental results indicate that the peak-to-peak value of dynamic pressure wave measured by sensor within 4.25 m increases during top or mid sustained leakage when leak aperture is larger than 4 mm in elongated bubble flow and 6 mm in slug flow. The amplitude of sustained leakage dynamic pressure increases as gas flow rate increases. The low frequency energy of signal increases immediately when leakage occurs, the energy of signal mainly concentrates at 0–15 Hz, the frequency amplitude of sustained leakage signal is much higher than normal flow signal and leak occur signal. As the gas volume fraction β increases from 0.23 to 0.75, the dynamic pressure propagation velocity decreases from 33.13 m/s to 26.5 m/s and then increases from 26.5 m/s to 66.25 m/s. The propagation velocity increases when it flows through an elbow pipe section. The results are meaningful for further study of two-phase pipeline slug flow leakage detection and location.

Numerical investigation of gas-liquid two-phase flow in horizontal pipe with orifice plate

Gas-liquid two-phase flow in horizontal or vertical pipeline significantly impacts on the transportation process. In fact, in the pipeline for regulating the flow flux or pressure, orifice plate and other current limiting device are frequently encountered. The flow behaviors of two-phase flow thus become more complicated in the pipeline with orifice plate. In order to explore the characteristics of gas-liquid two-phase flow in the pipeline accompanied by orifice plate, the computational fluid dynamics (CFD) simulation with volume of fluid (VOF) method and SST k−ω eddy viscosity model were imposed to probe the transient two-phase flow in a horizontal pipeline. The reliability of the numerical method was verified by a case of annular multiphase flow in a pipeline. In our research, two transient simulations related to different liquid volume ratios were carried out to explore the developments of the flow regimes. In addition, fluctuations of the area-average fluid pressures acting on the orifice plate surfaces were also monitored. The frequency characteristics of pressure pulsations were extracted via non-uniform fast Fourier transform (NUFFT). The main results show that the jet could be produced after the liquid passes through the orifice plate, and the liquid volume ratio has significant effects on the gas-liquid two-phase flow behaviors, a higher ratio leads to a faster stable and fuller jet. The stability of jet could be reflected via the dimensionless velocity ratio. The gas-liquid two-phase flow in the pipe with orifice plate induces typical broadband excitation.

A Simple Optical Sensor Based on an In-Line Mach–Zehnder Interferometer for Monitoring Single- and Two-Phase Flows in Pipelines

In this article, we proposed a simple optical sensor for flow measurement. The sensor structure is based on an in-line Mach–Zehnder interferometer formed by splicing an input single-mode fiber section and an output single-mode fiber section to a single-mode fiber sandwiched by two multimode fibers; it is called SMSMS sensor. The proposed sensor presents a high sensitivity due to low order modes that propagate in the middle single-mode fiber (SMF) cladding. The sensor is experimentally investigated and validated in which the results show good agreement between the optical power and flow for monitoring single- and two-phase flows using water and air fluids. Using this sensor, it is possible to identify the presence of air in the pipeline, in addition to the identification of the flow pattern. Thus, the proposed sensor is an interesting alternative for measuring single- and two-phase flows.

Precise Prediction of Interface Distribution of Materials in Multiphase Separation Facilities Using a Low-Cost and Simple Technique: ANN

The ability to precisely detect the interface of the different phases in a vessel plays an important role in chemical plants, oil, and petroleum industry. The purpose of this research is to apply the gamma-ray attenuation technique (single point source and single detector) together with MultiLayer Perceptron (MLP) neural network to detect the interface present in water-gasoil two-phase flows in pipelines and vessels, for the first time. The experimental setup is comprised of a plastic rod scintillator (BC400) coupled with two PMT tubes at two sides as a position-sensitive detector, a point gamma-ray source (137Cs), and a vessel between the source and detector. The detection system provides the required data for training and testing the network. Using this proposed method, the interface locations were determined in two-phase with mean relative error percentages less than 0.34% and 0.27% for levels of water and gasoil, respectively. The mean absolute error values were measured less than 1.16 and 1. Also, the correlation coefficients were calculated 0.999 and 1. These results presented the accuracy of the proposed method in order to determine the interface position. The used set-up is simpler than other proposed techniques and cost, radiation safety, shielding requirements, and risk production are minimized.

A novel gas/liquid two-phase flow imaging method through electrical resistance tomography with DDELM-AE sparse dictionary

PurposeThe purpose of this paper is to explore gas/liquid two-phase flow is widely existed in industrial fields, especially in chemical engineering. Electrical resistance tomography (ERT) is considered to be one of the most promising techniques to monitor the transient flow process because of its advantages such as fast respond speed and cross-section imaging. However, maintaining high resolution in space together with low cost is still challenging for two-phase flow imaging because of the ill-conditioning of ERT inverse problem.Design/methodology/approachIn this paper, a sparse reconstruction (SR) method based on the learned dictionary has been proposed for ERT, to accurately monitor the transient flow process of gas/liquid two-phase flow in a pipeline. The high-level representation of the conductivity distributions for typical flow regimes can be extracted based on denoising the deep extreme learning machine (DDELM) model, which is used as prior information for dictionary learning.FindingsThe results from simulation and dynamic experiments indicate that the proposed algorithm efficiently improves the quality of reconstructed images as compared to some typical algorithms such as Landweber and SR-discrete fourier transformation/discrete cosine transformation. Furthermore, the SR-DDELM has also used to estimate the important parameters of the chemical process, a case in point is the volume flow rate. Therefore, the SR-DDELM is considered an ideal candidate for online monitor the gas/liquid two-phase flow.Originality/valueThis paper fulfills a novel approach to effectively monitor the gas/liquid two-phase flow in pipelines. One deep learning model and one adaptive dictionary are trained via the same prior conductivity, respectively. The model is used to extract high-level representation. The dictionary is used to represent the features of the flow process. SR and extraction of high-level representation are performed iteratively. The new method can obviously improve the monitoring accuracy and save calculation time.

A Finite-Volume method for compressible non-equilibrium two-phase flows in networks of elastic pipelines using the Baer–Nunziato model

A novel Finite-Volume scheme for the numerical computations of compressible two-phase flows in pipelines is proposed for the fully non-equilibrium Baer–Nunziato model. The present FV approach is the extension of the method proposed in Daude and Galon (2018) in the context of the Euler equations to the Baer–Nunziato model. In addition, proper approximations of the non-conservative terms are proposed to consider jumps of volume fraction as well as jumps of cross-section in order to respect uniform pressure and velocity profiles preservation. In particular, focus is given to the numerical treatment of abrupt changes in area and to networks wherein several pipelines are connected at junctions. The proposed method makes it possible to avoid the use of an iterative procedure for the solution of the junction problem. The present approach can also deal with general Equations Of State. In addition, the fluid–structure interaction of compressible fluid flowing in flexible pipes is also considered. The proposed scheme is then assessed on a variety of shock-tubes and other transient flow problems and experiments demonstrating its capability to resolve such problems efficiently, accurately and robustly.