Flow Regime Map Research Articles

Identification of flow patterns in an opaque condenser tube by distributed fiber Bragg gratings

Two-phase loops with phase change heat transfer are pivotal for cooling electronics under high heat flux and for thermal control in spacecraft. Numerous studies aim to clarify the mechanisms behind these loops to enhance cooling capacity and stability, which are closely tied to flow patterns. However, conventional flow pattern identification methods, requiring transparent tubes for direct observation, are impractical for simultaneous heat transfer measurement, especially during condensation. This paper introduces a novel approach for identifying flow patterns within an opaque, vertical condensation tube using embedded distributed fiber Bragg gratings (DFBGs) for R134a. The method involves a “fingerprint” derived from temperature profile derivatives and additional criteria based on temperature variation characteristics. These include the relative deviation from saturation temperature, the relative spatial temperature gradients, and the relative amplitude of temperature fluctuations. Validation against high-speed camera images confirms the method’s efficacy. It enables the determination of flow pattern lengths, the endpoint of condensation, and the construction of a flow regime map. Additionally, it allows for the measurement of vapor velocity in slug flow, facilitating the calculation of slip ratio and void fraction, which correlates reasonably with the Zuber-Findlay model, with systematic positive deviations up to 30%. This method also paves the way for simultaneous measurement of in-tube condensation heat transfer characteristics for various flow patterns.

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.

Neural network based two-phase flow classification in a vertical narrow rectangular channel

Flow Regimes in a vertical narrow rectangular channel of cross-section 20×1cm2 are investigated up-to wispy annular flow using a dense test matrix and double sensor conductivity probe at section mid point. The data from the probe is used to calculate void fraction, velocity of interfaces, and chord length of various flow structures. A five unit self organizing neural network is used to identify various flow regimes by using single point geometrical data of flow structures. Six separate flow regimes are found to exist. A new flow regime is identified and is called rolling-wispy flow. A discussion on boiling crisis is given regarding this flow regime. The resultant flow regime map is compared with various existing maps.

Thermo-hydrodynamic characterization and mapping of the two-phase flow in a capillary tube

The study presents an experimental investigation on the behavior of condensate film and liquid–vapor meniscus in the unit cell of a pulsating heat pipe (PHP) at different operating boundary conditions, and their respective roles in determining PHP’s performance. The orientation and the temperatures of evaporator and condenser sections are taken as the variable operating boundary conditions whereas the amplitude of oscillations influences the performance of the PHP. The entire thermo-hydrodynamic phenomenon is captured using high-speed imaging. By tracking the interface of liquid film and vapor, different regimes for film flow in the condenser section are observed and characterized. Also, the oscillation amplitude has been quantified at different operating boundary conditions. Despite a quite small tube diameter, gravity plays a key role in determining the liquid and vapor phase distributions in the tube. The variation of oscillation amplitude is intimately linked with the nuances of film flow regimes and inter-regime transitions. The optimum inclination angle, and evaporator and condenser temperatures are found to exist for the PHP unit cell which maximize the oscillation amplitude. The dependence of optimum inclination angle on condenser temperature has also been understood along with. Further, the associated film flow regime in condenser which facilitates these optima has also been recognized. All variable operating boundary conditions are observed to have a peculiarly mixed influence on the flow regimes and thus oscillation amplitude. The study would help to achieve a better elementary understanding of the role of condensate film flow in determining PHP’s performance and develop a flow regime map particularly for PHPs.

Influence of nanoparticle concentration on the flow regimes of crude oil – Nanosuspension in a microchannel

This paper presents the results of an investigation into the effect of silica nanoparticles on two-phase flow regimes in a Y-shaped microchannel. The following fluids were subjected to investigation: oil, water, and a water-based suspension containing SiO2 nanoparticles at a weight concentration of 1 ≤ φ ≤ 10 %. A systematic investigation of the flow regimes revealed the following: slug, parallel, and droplet regimes. The ranges of existence of the obtained flow regimes were determined and flow regime maps were constructed as a function of fluid flow rates and dimensionless numbers. The results of the study demonstrated that the slug length and frequency of slug formation are influenced by varying silica concentrations. Furthermore, the correlation between slug length and nanoparticle concentration remains consistent as the suspension flow rate increases. The dependence of the ratio of oil layer width to channel width for suspensions with varying nanoparticle concentrations was quantified. A mathematical simulation of two-phase flow of immiscible fluids was conducted. The results of the numerical simulation demonstrated the existence of the flow regimes that had been previously identified through experimentation. The aforementioned methodology may therefore be employed for the investigation of the two-phase immiscible flow of oil and nanosuspension.

Flow regime transition maps and pressure loss prediction of gas, oil and water three-phase flow in the vertical riser downstream 90° bend using data driven approach

The simultaneous flow of gas, oil & water is frequently encountered in pipelines during upstream petroleum operations. The multiphase flow results in different types of flow patterns based on the flow rates of fluids, physical properties and geometry of the flow domain. The flow behavior is characterized based on the governing flow patterns. Hence, the information about the flow patterns, regime maps and resulting pressure loss are important for multiphase flow system design and optimization. The current work is focused on construction of gas, oil and water, three-phase flow regime maps and developing pressure loss prediction correlations for the flow through vertical riser downstream 90° bend. The pipe internal diameter (ID) is 6 inch and the bending radius to pipe diameter ratio is 1. The observed gas-liquid flow patterns are slug, churn, and semi-annular churn flow at the given range of superficial velocities of fluids. The flow pattern data has been used to construct flow regime maps to analyze the variation in flow patterns with flow rates of fluids and compared with the available works in the literature. In addition, the change in pressure loss with respect to flow patterns has been analyzed. Previous models are used for the prediction of pressure loss. However, according to the assessment, the models underpredicted the pressure loss. Based on three-phase pressure loss data, multiple linear regression analysis has been carried out to propose new correlations for pressure loss prediction. Comparison of the calculated and experimental data showed good agreement between the results. The knowledge of flow regime variation and pressure loss correlations can help flow assurance engineers in designing and optimization of multiphase flow systems.

Investigation of Laminar Forced and Mixed Convection in Horizontal Mini Tubes with Uniform Wall Heat Flux Boundary Condition

In this study, a numerical model is established to study the forced and mixed convection heat transfer in the laminar region for horizontal mini tube with different diameters (1.2 mm to 3.0 mm) under the uniform wall heat flux boundary condition. The Reynolds number is set from 100 to 2,000 and the uniform wall heat flux boundary condition is set at 10 and 20 kW/m2. The model is verified with well-established correlation to guarantee good accuracy. The existence of mixed convection is examined by (1) the ratio between the heat transfer coefficients at the top and the bottom of the tube, and (2) the temperature contour plot. Based on the simulation results, the existence of buoyancy superimposed on the main flow is strongly related to the tube diameter, the dimensionless location, the Reynolds number, and the heat flux applied. Under the same heating condition, for small diameter tube with insufficient length, buoyancy effect can never establish. The existing flow regime maps for macro tube were used to predict the forced and mixed convection regimes from the simulated mini tube results and discrepancy was found. A new flow regime map is hence developed for mini tubes, and it classified the simulation results with good accuracy.

Wake transitions of flow past two tandem semi-circular cylinders near a moving wall

Wake transitions of flow past two tandem semi-circular cylinders near a moving wall were numerically investigated using the lattice Boltzmann method at the Reynolds number of 150 with various gap ratios (G/D, where G and D are the spacing between the cylinder and wall and the cylinder diameter, respectively) and spacing ratios (L/D, where L is the distance between the cylinder centers). The analysis aims to clarify the effects of L/D and G/D on wake structures, hydrodynamic forces, Strouhal number, and spectral energy of the flow exerted on both cylinders. This study reveals five distinct flow regimes in the L/D-G/D space, such as overshoot, continuous reattachment, pair-wise, quasi-coshedding, and coshedding. These regimes are identified using plots of vorticity contour, time history of drag and lift coefficients (CD and CL), power spectral density, and proper orthogonal decomposition of the vorticity fluctuation into deterministic spatial structures. Furthermore, the flow regime maps and diagrams of time-averaged pressure coefficients on the surface of the cylinders are given to analyze the influence of the moving wall. A significant change in CD and CL is observed for both cylinders, depending on the L/D and G/D ratios. The time-averaged drag coefficient of the downstream cylinder is remarkably lower than that of the upstream cylinder. A significant increase in the time-averaged lift coefficient of the upstream cylinder is observed when the G/D is small due to near-moving wall effects. The root-mean-squared value of the lift and drag coefficients of the downstream cylinder is lower than that of the upstream cylinder as a result of the proximity effect. Meanwhile, the Strouhal number for both cylinders remains mostly the same.

Microfluidic study of effect of dispersed phase viscosity and continuous phase viscosity on emulsification in a cross-junction chip

Immiscible flow of oil phase and displacing phase with surfactant can cause emulsification during the oil development. However, it is still unclear how the viscosity of each phase influences the emulsification at the micro level. In this study, we investigated the flow regimes and emulsification of two immiscible fluids in a cross-junction device by using an oil-surfactant system and an oil-surfactant/polymer system. Based on the experimental data, we analyzed the flow regimes and draw flow regime maps of the two systems. Moreover, we established the new scaling laws that include the capillary number, the flow rate ratio, and the viscosity ratio of two phases to predict the droplet diameter or slug length. The findings indicated that there are four flow regimes in the oil-surfactant system, including threading, squeezing, dripping, and jetting regimes. Besides, a new type of flow regime, irregular dripping regime, appears in the oil-surfactant/polymer system. According to the regime maps, the area of dripping regime decreases with the increase of the viscosity of dispersed phase or continuous phase. For both systems, the regression equations with the viscosity ratio have better fitting effect than those without the viscosity ratio. Meanwhile, compared with the effect of viscosity ratio of two phases, the flow rate ratio of two phases has higher influence on droplet diameter and slug length. The experiments present detailed emulsification processes at pore scale and provide new insights for the prediction of emulsion droplets and slugs.

Flow regimes identification of air water counter current flow in vertical annulus using differential pressure signals and machine learning

This study investigates the gas–liquid two-phase counter-current flow through a vertical annulus, a phenomenon prevalent across numerous industrial fields. The presence of an inner pipe and varying degrees of eccentricity between the inner and outer pipes often blur the clear demarcation of flow regime boundaries. To address this, we designed a vertical annulus with adjustable eccentricity (outer and inner diameters of 125 mm and 75 mm, respectively). We conducted gas–liquid counter-current flow experiments under specific conditions: gas superficial velocity ranging from 0.06 to 5.04 m/s, liquid superficial velocity from 0.01 to 0.25 m/s, and five levels of eccentricity (e = 0, 0.25, 0.5, 0.75, 1). We collected differential pressure data at two distinct height distances (DP1: 50 mm and DP2: 1000 mm). We used vectors, composed of both the probability density functions (PDFs) of the differential pressure signals and the power spectral density (PSD) reduced via Principal Component Analysis, as features. Using the CFDP clustering algorithm—based on local density—we clustered the flow regimes of the experimental data, thereby achieving an objective and consistent identification of the flow regime of gas–liquid two-phase counter-current flow in a vertical annulus. Our analysis reveals that for DP1, the main differences in the PSD of various flow regimes occur within the 0.5–1 Hz range. Among the three flow regimes involved, the slug flow exhibits the highest power intensity, followed by the bubbly flow, with the churn flow having the least. In terms of differential pressure distribution, the bubbly and churn flows have a concentrated distribution, while the slug flow is more dispersed. For DP2, the PSD differences primarily exist within the 0.5–2 Hz range. The churn flow has the highest power intensity, followed by the slug flow, with the bubbly flow being the weakest. Here, the bubbly flow's differential pressure distribution is concentrated, while the slug and churn flows are more dispersed. Based on the results of the flow regime classification, we generated a flow regime map and analyzed the influence of annulus eccentricity on the flow regime. We found that in most cases, pipe eccentricity does not significantly affect the flow regime. However, in the transition region—such as the bubbly to slug flow transition zone—flows with medium eccentricity values (e = 0.5, 0.75) are more likely to transition to slug flow. We compared the visual recognition results of flow regimes with the clustering results. 4.04% of the total samples showed different results from visual recognition and clustering, primarily located in the flow regime transition area. Since visually distinguishing flow regimes in these areas is typically challenging, our methodology offers an objective classification approach for gas–liquid two-phase counter-current flow in a vertical annulus.

Identifying steady and pulsatile two-phase flow regimes with pressure drop signals and acoustic emissions

Identifying two-phase flow regimes is vital for understanding phase-change heat and mass transfer processes. Traditionally, flow regime identification has relied on subjective flow visualization studies, which are then converted to flow regime maps applicable to specific operating conditions. However, these conventional, largely subjective, maps fall short in predicting abrupt changes in flow patterns that often occur during regular operation of vapor compression and absorption heat pumps and other thermal systems. Conventional flow regime maps are also inadequate for addressing the transient, intermittent, or periodic flow regimes that occur in boiling and condensation enhanced using acoustic and other emerging techniques. Therefore, there is a pressing need for alternative flow regime identification techniques that can adapt and reliably track rapid and local changes in two-phase hydrodynamics. Promising candidates for dynamic flow pattern classification include high-resolution pressure drop signals and acoustic emission spectra, which can provide insights into the local hydrodynamics within a flow channel. To assess the feasibility of these measurement techniques, differential pressure and condenser microphone measurements are recorded alongside high-speed videos of a two-phase flow of saturated R134a. The total mass flux and vapor quality are varied to understand the effects of phase velocity and liquid inventory on wave propagation in the channel. Additionally, forced oscillations are introduced to a steady two-phase flow to analyze their impact on flow patterns and their corresponding pressure drop and acoustic signals. Statistical analyses, including Gaussian mixture modeling, are employed to reveal characteristic pressure drop probability associated with each flow pattern, which form the basis for developing a model capable of predicting flow regimes in both steady and oscillating flows. The resulting framework introduces a new flow regime identification technique that can adapt to dynamic operating conditions, benefiting a wide range of thermal systems and phase-change processes.

Validation of two-group interfacial area transport equation in boiling flow

The Two-Fluid Model is the backbone of thermal-hydraulics and system-analysis codes for nuclear design. The Two-Fluid Model tracks the transfer of conserved quantities—mass, momentum, and energy—without the need for bubble interface tracking. However, two-phase flows are characterized by their different flow regimes which change as more vapor is present in the flow, from bubbly flow to cap/slug flow to annular flow. The two-group Two-Fluid Model can track the progression of boiling flows beyond the bubbly region without the need for flow-regime maps. A two-group wall-boiling model is implemented and coupled with the two-group Interfacial Area Transport Equation. The resulting model is compared against experimental data and predicts the growth in cap/slug bubbles through interaction models rather than through flow-regime maps. The coupled model can predict the growth in void fraction and interfacial area concentration beyond the capability of the one-group model, demonstrating the applicability of a coupled two-group approach to modeling boiling flow.

Experiments and predictions for severe slugging of gas-liquid two-phase flows in a long-distance pipeline-riser system

Experiments concerning the flow regimes observed in gas-liquid two-phase flows in a long-distance pipeline-riser system were carried out and analyzed in this paper. The test loop with 0.075 m inner diameter consisted of a 314 m horizontal pipeline, followed by a 25 m downward-inclined pipe, and finally a 21.5 m riser pipe. An industrial-scale global flow regime map including 5 flow regimes was derived from differential pressure measurements in the riser and was used as a reference for improvements. Electrical capacitance volume tomography installed in the horizontal section was used to reconstruct the phase interface and calculate the average gas void fraction (GVF). An appropriate model for this system was selected by comparing the experimental GVF with different, widely used models. The occurrence of severe slugging flow (SS) can be predicted accurately using an improved model involving additional corrections that consider pipeline length, accurate GVF calculation, and gas density. This study supports the development of a suitable SS prediction model enabling safe design, operation, and control of practical systems.

Flow regime classification using various dimensionality reduction methods and AutoML

Accurate identification of flow regimes is paramount in several industries, especially in chemical and hydrocarbon sectors. This paper describes a comprehensive data-driven workflow for flow regime identification. The workflow encompasses: i) the collection of dynamic pressure signals using an experimentally verified numerical two-phase flow model for three different flow regimes: stratified, slug and annular flow, ii) feature extraction from pressure signals using Discrete Wavelet Transformation (DWT), iii) Evaluation and testing of 12 different Dimensionality Reduction (DR) techniques, iv) the application of an AutoML framework for automated Machine Learning classifier selection among K-Nearest Neighbors, Artificial Neural Networks, Support Vector Machines, Gradient Boosting, Random Forest, and Logistic Regression, with hyper-parameter tuning. Kernel Fisher Discriminant Analysis (KFDA) is the best DR technique, exhibiting superior goodness of clustering, while KNN proved to be the top classifier with an accuracy of 92.5 % and excellent repeatability. The combination of DWT, KFDA and KNN was used to produce a virtual flow regime map. The proposed workflow represents a significant step forward in automating flow regime identification and enhancing the interpretability of ML classifiers, allowing its application to opaque pipes fitted with pressure sensors for achieving flow assurance and automatic monitoring of two-phase flow in various process industries.

Drop encapsulation and bubble bursting in surfactant-laden flows in capillary channels

We present a parametric study of the unsteady phenomena associated with the flow of elongated gas bubbles traveling through liquid-filled square capillaries under high Weber number conditions. These conditions induce the formation of an indentation at the back of the bubble that commonly gives way to a deep reentrant liquid jet penetrating the bubble. Subsequent steps include pinch-off events in the penetrating liquid to generate one or multiple encapsulated drops which may coalesce, in conjunction with the bursting of the bubble-liquid interface by either the liquid jet or the drops. Some of these interfacial instabilities have previously been reported experimentally and numerically for liquid-liquid flow in microchannels. We carry out three-dimensional direct numerical simulations based on a hybrid interface-tracking/level-set method capable of accounting for the presence and dynamic exchange of surfactants between the liquid bulk phase and the liquid-gas interface. Our results indicate that the delicate interplay among inertia, capillarity, viscosity, surfactant adsorption/desorption kinetics, and Marangoni stresses has a dramatic influence over the nonaxisymmetric morphological structures of the encapsulated drops-elongated bubble. This strong coupling also influences the pinch-off time, penetration depth of the liquid, and number, size, and velocity of the encapsulated drops across the bubble. The observed phenomena are summarized in three main morphological regimes based on surfactant-related parameters and dimensionless groups. A discussion of the flow regime maps is also provided. Published by the American Physical Society 2024

Flow pattern visualization and definition of transition criteria for two-phase flow in Chevron-type corrugated channels

This study aims to highlight the factors influencing flow patterns in Plate Heat Exchangers (PHEs) operated with two-phase flows. Our focus is on providing precise definitions of flow regimes and proposing transition boundaries by comparing diverse experimental datasets. To accomplish this, we designed an experimental apparatus for flow visualization through high-speed videos. The videos clarify flow patterns in an upward-flowing air-water mixture within a chevron-type plate heat exchanger. We introduce a new, clearly defined nomenclature and present the results in the form of a flow regime map. Moreover, we reclassify previously documented flow patterns in the literature using our established nomenclature, creating a unified and comparable database of visualization data. Subsequently, we explore semi-theoretical transition criteria and establish new transition boundaries based on the compiled experimental data. These newly determined transition lines are integrated into a comprehensive global flow regime map, advancing our understanding of two-phase flow behavior in PHEs.

Free falling of non-spherical particles in Newtonian fluids, A: Terminal velocity and drag coefficient

The terminal velocity and drag coefficient are vital parameters for designing industrial systems involving free-falling particles. While the literature on spherical particles is abundant, that on non-spherical particles is scarce. Therefore, a comprehensive experimental study was conducted using discs, cylinders, and irregular particles of various sphericities in various fluids. First, the flow mode was analyzed, and seven flow modes were identified and described in a flow regime map. Subsequently, the terminal velocity and drag coefficient were correlated depending on the sphericity of three trends. The first is for nearly spherical particles with sphericities over 0.87, and the other two trend lines are for sphericities lower than 0.87, one for discs and the other for cylinders. Additional experiments enabled the extension of the models to nearly spherical, flat, and long particles within an error of ±30%.

Two-phase flow regime identification using multi-method feature extraction and explainable kernel Fisher discriminant analysis

PurposeIdentifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.Design/methodology/approachA numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.FindingsThe results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.Practical implicationsThis workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.Originality/valueThis paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

Numerical simulations of flow past a backward-facing step under a strong transverse magnetic field

The flow of liquid metal over a backward-facing step (BFS) exhibits unique flow characteristics due to the influence of strong magnetic field. In this study, direct numerical simulation of the BFS flow under a strong magnetic field is conducted based on a quasi-two-dimensional model (with a large interaction number, N≫1, and a large Hartmann number, Ha≫1). The Reynolds number (Re), Hartmann number (Ha), and expansion ratio (ER) are investigated within the ranges of [100−80 000], [100−40 000], and [1.67−5], respectively. Three typical flow regimes are defined based on the evolution of the free shear layer vortices and the separation state of the boundary layer. Furthermore, a comprehensive flow regime map is presented for different ER, revealing a positive correlation between the critical Reynolds number (Rec1) and Ha at the onset of instability. Specifically, Rec1 is proportional to Ha0.5, Ha0.54, and Ha0.56 for ER = 5, 2.5, and 1.67, respectively. Moreover, the maximum relative thickness of the free shear layer at Hac1 appears in the range of approximately 0.7–0.78Lr for ER = 5, while for ER = 2.5, it appears in the range of approximately 0.80–0.85Lr, indicating that the instability position of the free shear layer occurs earlier for large ER. Our numerical investigation also demonstrates that an increase in the transverse magnetic field compresses the free shear layer and delays the process of vortex pairing, thereby suppressing the oscillatory behavior of the shear layer.

Multiple emulsions: A new level-set based two-and-three dimensional simulation of multiphase immiscible flows for droplet formation

The present paper introduces a numerical approach based on the level-set framework to simulate multiphase flow in the context of multiple emulsion formation. The present technique, designed for the flow of n-phases, is applicable for the production of multiphase emulsions and also for the modeling of two and three-dimensional systems. This method is utilized to simulate the formation of single, double, and triple emulsions in a microfluidic cross-junction. The accuracy of the findings is confirmed by conducting an investigation of a single emulsion at home, as well as by referencing experimental and numerical literature on multiple emulsions. Until recently, the prospect of a shift in the double droplet formation regime at a constant capillary ratio between phases had not been taken into account. The present study yielded a flow regime mapping diagram that exhibits a transition in the double droplet formation regime under a constant capillary number ratio between the inner and middle phases. Using a morphological diagram, our method takes into consideration the effect of varying values of interfacial tension between the phases on the formation of double droplets. A comparison of two-dimensional and three-dimensional modeling strategies for double emulsion is also conducted, with the aim of clarifying the dissimilar results obtained from these two techniques.