Phase Flow Regimes Research Articles

Spatio-temporal void fraction visualization in air-water two-phase flow regime transitions by combination of convolutional neural network and long short-term memory implemented into multiple current-voltage (MCV-CNN_LSTM)

Spatio-temporal void fraction in air-water two-phase flow regime transitions has been visualized by combination of convolutional neural network and long short-term memory implemented into multiple -current-voltage (MCV-CNN_LSTM). The MCV-ML is composed of two components, which are MCV-CNN_LSTM training and evaluation. In the first component, four steps are carried out as 1) true void fraction α measurement was conducted by wire-mesh sensor (WMS) as objective variables, 2) simulated MCV voltage U calculation by simulation of MCV measurement for explanatory variable, 3) CNN_LSTM training instance generation, and 4) CNN_LSTM model training and testing. In the second component, two additional steps are experimentally conducted which are 5) actual MCV voltage V measurement by MCV for input of trained ML, and 6) spatio-temporal void fraction α prediction. For the dataset generation, the experiment was conducted on air-water two phase flow regime transitions in vertical pipe with an inner diameter of 25 mm and a length of 350 mm from the elbow. The superficial velocity of liquid and gas phase are varied to present the flow regime transition of bubbly to slug flow. As a result, the estimated spatio-temporal void fraction αˆ by MCV-CNN_LSTM enables the visualization of detailed gas distribution in vertical upward two-phase flow. The spatial averaged instantaneous void fraction measured by WMS and estimated by MCV-CNN_LSTM show qualitative agreement in normalized cross correlation (INCC) of 0.364 on its temporal variation.

The pore-network modeling of gas-condensate flow: Elucidating the effect of pore morphology, wettability, interfacial tension, and flow rate

The gas-condensate flow in the near-well region is significantly influenced by phase behavior, flow regimes, and pore geometries. In conventional gas-condensate reservoirs the key pore-scale parameters affecting gas and condensate relative permeabilities include velocity (i.e., pressure gradient), interfacial tension (IFT), wettability, and pore structure. To examine the impact of these parameters, three-dimensional (3D) and two-dimensional (2D) pore-network models (PNMs) were developed. A proposed compositional model was used to implement the cyclic process of condensate corner flow (film flow for circular tubes) and condensate blockage. Response surface methodology (RSM) was employed to achieve high accuracy in phase equilibrium calculations and to enhance computational speed.The 3D PNM simulations of gas-condensate core-flood experiments confirmed the consistency and accuracy of the implemented methodology. A parametric study of governing factors such as pore shapes, wettability, IFT, and flow rate was conducted using the developed PNMs. The findings revealed that pore geometry and contact angle dictate the condensate meniscus curvature and snap-off process in pore throats. The unblocking of throats by condensate bridges was primarily controlled by contact angle, IFT, and pore cross-section. A shift to neutral wetting substantially improved gas-condensate flow in higher IFTs and angular pore shapes.The positive velocity effect on low-IFT gas-condensate flow, known as the coupling rate effect, was more pronounced in simulations with lower contact angles, and its impact was negligible at neutral wettability, similar to the IFT effect. The simulation results and findings underscore the influence of each factor and offer a method for incorporating the effects of pore shape (i.e., formation type and structure), contact angle, velocity, and IFT in continuum scale simulations.

Chrono-photographic visualization and characterization of the flow regimes in rewetting by bottom flooding

Many engineering applications encounter the highly complicated rewetting phenomenon. The complexity of the process arises as the phenomenon is highly transient and possesses an implicit interplay of several transport processes. In particular, the hydrodynamics of in-conduit rewetting is poorly understood due to lack of visualization. The present study reports an in-depth quantitative representation of the hydrodynamics of different two phase flow regimes associated with rewetting by bottom flooding, perceived from an intelligently fabricated experimental test facility. The technique of chronophotography and image processing based on pixel level information of a fixed region of interest has been utilized to quantitatively characterize different flow regimes like – nucleate boiling, transition boiling, inverted annular film boiling and dispersed flow film boiling. The effects of inlet mass flux and initial wall temperature have been explained based on operating regime maps. The rich hydrodynamics captured in this report provides an in-depth knowledge of the associated heat transfer mechanisms.

Application of Neural Network and Time-Domain Feature Extraction Techniques for Determining Volumetric Percentages and the Type of Two Phase Flow Regimes Independent of Scale Layer Thickness

One of the factors that significantly affects the efficiency of oil and gas industry equipment is the scales formed in the pipelines. In this innovative, non-invasive system, the inclusion of a dual-energy gamma source and two sodium iodide detectors was investigated with the help of artificial intelligence to determine the flow pattern and volume percentage in a two-phase flow by considering the thickness of the scale in the tested pipeline. In the proposed structure, a dual-energy gamma source consisting of barium-133 and cesium-137 isotopes emit photons, one detector recorded transmitted photons and a second detector recorded the scattered photons. After simulating the mentioned structure using Monte Carlo N-Particle (MCNP) code, time characteristics named 4th order moment, kurtosis and skewness were extracted from the recorded data of both the transmission detector (TD) and scattering detector (SD). These characteristics were considered as inputs of the multilayer perceptron (MLP) neural network. Two neural networks that were able to determine volume percentages with high accuracy, as well as classify all flow regimes correctly, were trained.

Experimental investigation of water-gas mixed seepage parameters characteristics in broken coal medium

In order to study the mixed permeability characteristics of broken coal medium, the parameter changes during water-gas permeation are analyzed and discussed in this study. It includes the law of two-phase flow state transformation, the law of permeability evolution and the principle of effective stress action. Firstly, the water-gas mixed permeation test system was designed by independent design. Then the gas and liquid two-phase permeation parameters were measured in real time by using multiple sets of sensors. The results are as follows: In one hand, the two-phase seepage process in broken coal medium, the seepage apparent Reynolds number is mainly distributed between 1230–2207. The difference of two orders of magnitude between the kinematic viscosities of the two fluids leads to an asynchronous transition process between the liquid and gas phase flow regimes. On the other hand, there is a competitive relationship between the relative permeability ratio of water and gas phases. When the proportion of gas phase relative permeability is distributed in the interval 71.7%–85.1%, the proportion of gas phase relative permeability is dominant, and it is most sensitive to the influence of the compaction deformation process of the initial pore structure. At the same time, the permeability k decreases with the increase of the effective stress σov in all three stages of the compaction deformation of the skeleton of the broken coal medium, in accordance with the relationship: σov=0.678/k+0.608. The effective stress will directly determine the pore deformation process of the structure of the broken coal medium.

Data-driven machine learning for accurate prediction and statistical quantification of two phase flow regimes

Two different two-phase flow regimes including slug and dispersed flows are examined through the implementation of system identification methods to attain reduced-order models. The obtained models accurately capture the flow dynamics of the studied regimes. The models also provide state-space frequency by defining the transfer functions. The system identification results are compared with those of the bidirectional neural network to predict the phase fraction of the considered two-phase flows. The result of long short-term memory shows correlations of 91% between the real and predicted phase fractions.

Developing flow pattern maps for accelerated two-phase capillary flows

The prediction of flow pattern transitions is extremely important to understand the coupling of thermal and fluid dynamic phenomena in two phase systems and it contributes to the optimum design of heat exchangers. Two phase flow regimes have been extensively studied under controlled mass flow rate and velocity. On the other hand, less effort has been spent in the literature on the cases where the flow motion is purely thermally induced and consequently the mass flow rate or the velocity of the phases are not known a priori. In the present work, flow pattern transitions and bubble break-up and coalescence events have been investigated in a passive two phase wickless capillary loop, where the mass flow rate is intrinsically not controllable. Modified Froude, Weber and Bond numbers have been introduced, considering the actual acceleration of the fluid and the length of the bubble as merit parameters for the transitions. The proposed nondimensional investigation was developed by analysing experimental data obtained with ethanol and FC-72, as working fluids, different heat input levels (from 9 to 24 W) as well as three different gravity levels (through a parabolic flight campaign). A new empirical diabatic flow pattern map for accelerated two-phase capillary flows is presented, together with quantitative criteria for the calculation of the flow regime transitions, defining the physic limits for the bubble coalescence and break-up. This kind of new regime maps will be useful to the further development of comprehensive designing tools for passive two-phase wickless heat transfer devices.

Predicting the Dynamic Parameters of Multiphase Flow in CFD (Dam-Break Simulation) Using Artificial Intelligence-(Cascading Deployment)

Multiphase flow of oil, gas, and water occurs in a reservoir’s underground formation and also within the associated downstream pipeline and structures. Computer simulations of such phenomena are essential in order to achieve the behavior of parameters including but not limited to evolution of phase fractions, temperature, velocity, pressure, and flow regimes. However, within the oil and gas industry, due to the highly complex nature of such phenomena seen in unconventional assets, an accurate and fast calculation of the aforementioned parameters has not been successful using numerical simulation techniques, i.e., computational fluid dynamic (CFD). In this study, a fast-track data-driven method based on artificial intelligence (AI) is designed, applied, and investigated in one of the most well-known multiphase flow problems. This problem is a two-dimensional dam-break that consists of a rectangular tank with the fluid column at the left side of the tank behind the gate. Initially, the gate is opened, which leads to the collapse of the column of fluid and generates a complex flow structure, including water and captured bubbles. The necessary data were obtained from the experience and partially used in our fast-track data-driven model. We built our models using Levenberg Marquardt algorithm in a feed-forward back propagation technique. We combined our model with stochastic optimization in a way that it decreased the absolute error accumulated in following time-steps compared to numerical computation. First, we observed that our models predicted the dynamic behavior of multiphase flow at each time-step with higher speed, and hence lowered the run time when compared to the CFD numerical simulation. To be exact, the computations of our models were more than one hundred times faster than the CFD model, an order of 8 h to minutes using our models. Second, the accuracy of our predictions was within the limit of 10% in cascading condition compared to the numerical simulation. This was acceptable considering its application in underground formations with highly complex fluid flow phenomena. Our models help all engineering aspects of the oil and gas industry from drilling and well design to the future prediction of an efficient production.

Image Processing Technique for slug length measurement during Mixing and Separation of Two-phase Flows in T sections

Abstract Study of two phase flow regimes in a mini/micro channel finds its applications in micro-fluidic devices such as micro heat exchangers owing to its large heat transfer. Such systems have large surface to volume ratio. The present work detail the results obtained for bubbly and slug flow regimes formed in a T-junction for an air water mixture. Experiments are performed in two different tubes with internal diameters of 0.6mm and 2.5mm having a length of 100mm. Image processing techniques are employed using MATLAB software. The data will be helpful in designing fluid flow mini/micro channels commonly used in thermal MEMS.

Two phase heat transfer and flow regimes of R-134a and R-410A during condensation in horizontal micro-fin tubes

Two phase heat transfer and flow regimes of R-134a and R-410A during condensation in horizontal micro-fin tubes

Effect of Surfactants on Pressure Drop in Vertical Water-Air and Gas Condensate-Air Two-Phase Vertical Flow

The influence of Sodium dodecyl sulfate and Triton X-100 surfactants on the two-phase pressure drop and two phase flow regime of water-air and gas condensate-air in upward vertical pipe were investigated for various gas/liquid flow rates. Sodium dodecyl sulfate and Triton X-100 reduced the pressure drop of single phase water flow by 11% and 29% compared with that of pure water single phase flow at water velocity of 13 m/s. For condensate single phase flow, Sodium dodecyl sulfate and Triton X-100 reduced the pressure drop by 9% and 17% compared with that of condensate single phase flow with no surfactant at gas condensate velocity of 13 m/s. The maximum efficiency of Sodium dodecyl sulfate and Triton X-100 in reducing the pressure drop of water-air system were 67.1% and 79.8%, respectively, compared with that of pure water-air two-phase flow. For gas condensate-air system, the maximum efficiency of Sodium dodecyl sulfate and Triton X-100 in reducing the pressure drop was 57.1% and 36.7%, respectively, compared to that of pure condensate-air two-phase flow.

Pressure drop in liquid chromatography.

Measurement of pressure drop is routinely performed during chromatographic runs. In many cases this information is only used for regulation of mobile phase flow rate to keep pressure drop below defined limit. However, pressure drop can provide additional important information about performance of chromatographic process. In this review different parameters affecting pressure drop such as compressibility of chromatographic media, nature of applied sample and mobile phase flow regime are discussed. Detailed analysis correlating organization of particle based chromatographic media and pressure drop is presented together with its extension to convective media such as membranes and monoliths but also novel 3D printed media. Finally, estimation of layer thickness formed by adsorbed molecules based on a pressure drop data is presented and its applicability is discussed.

Simulation of Two Phase Flow Dynamics in Flexible Riser Exit Geometries for Oil and Gas Applications

Four different riser pipe exit configurations were modelled and the flow across them analysed using STAR CCM+ CFD codes. The analysis was limited to exit configurations because of the length to diameter ratio of riser pipes and the limitations of CFD codes available. Two phase flow analysis of the flow through each of the exit configurations was attempted. The various parameters required for detailed study of the flow were computed. The maximum velocity within the pipe in a two phase flow were determined to 3.42 m/s for an 8 (eight) inch riser pipe. After thorough analysis of the two phase flow regime in each of the individual exit configurations, the third and the fourth exit configurations were seen to have flow properties that ensures easy flow within the production system as well as ensure lower computational cost. Convergence (Iterations), total pressure, static pressure, velocity and pressure drop were used as criteria matrix for selecting ideal riser exit geometry, and the third exit geometry was adjudged the ideal exit geometry of all the geometries. The flow in the third riser exit configuration was modelled as a two phase flow. From the results of the two phase flow analysis, it was concluded that the third riser configuration be used in industrial applications to ensure free flow of crude oil and gas from the oil well during oil production.

Three phase flow in upstream pipes: A review.

In this article, work done by several researchers with respect to predictive models, three phase flow regimes and methods of identifying flow regimes were reviewed. Additionally, effects of water cut and fluid velocities on pressure drop, liquid holdup and flow regimes were also discussed. The three phases under investigation by the researchers were gas, oil and water flowing through horizontal, vertical or inclined pipes. The models reviewed were developed to anticipate liquid phase heights and pressure drop. The multi-fluid and drift-flux methods that can be applied to model the flow, were also reviewed. The two main categories for the flow regimes identified were the oil-based and water-based flow patterns, where the water-based flow patterns would occur upon phase inversion. Conductance, algorithm and network mapping methods of identifying flow patterns were reviewed too. Additionally, it was seen that pressure gradients increased with superificial gas and liquid velocities and water cut had varying impacts on flow pattern transitions. Work done on the effects of temperature and pipe diameter were briefly explored. Furthermore, measurement of fluid flows, ways to measure flows and methods to detect the type of flow and simulate them were briefly investigated.Keywords: Three phase flow; predictive models; flow regimes; oil-dominated; water-dominated; pressure drop

Carbonated water injection under reservoir conditions; in-situ WAG-type EOR

Enriching injection water with CO2 has demonstrated promising results as a method for improving the oil recovery and securely storing CO2 in oil reservoirs. However, mutual interactions taking place between carbonated water and reservoir oil at elevated reservoir conditions are not fully understood. Herein, we present the results of a thorough and direct investigation of the interactions between live-oil/CO2/aqueous-phase leading to additional oil recovery and enhanced CO2 storage in pore-scale and core-scale.CO2 transfer from carbonated water to live oils can trigger liberation of light components in form of a new gaseous phase. This unique phenomenon would bring about higher degrees of oil swelling, and it can also create a three phase flow regime, which leads to effective reduction of residual oil saturation. The observations confirm that the performance of carbonated water injection (CWI) should be investigated under reservoir conditions using multi-components live oil and reservoir cores. From the core displacement tests, it was observed that secondary CWI could recover a significant amount of additional oil, which was 26% compared to conventional seawater injection. When CO2 content of injected CW (carbonated water) was halved, the oil recovery dropped by 1/3 Using live oils, it was found out that CO2 would be trapped in the new phase, which brings about an enhanced CO2 trapping mechanism. Under realistic reservoir conditions where complex mass transfer of CO2 from aqueous phase to oil and gas phases takes place, an “in-situ WAG-type” three-phase flow is generated with more effective sweep efficiency and pore-scale advantages.

Hydrodynamics of three phase flow in upstream pipes

In this article, work done by several researchers with respect to predictive models, three phase flow regimes and methods of identifying flow regimes were reviewed. Additionally, effects of water c...

Experimental investigation of effect of spacer on two phase turbulent mixing rate in subchannels of pressure tube type BWR

Abstract Turbulent mixing rate between adjacent subchannels in a two-phase flow has been known to be strongly dependent on the flow pattern. The most important aspect of turbulent motion is that the velocity and pressure at a fixed point do not remain constant with time even in steady state but go through very irregular high frequency fluctuations. These fluctuations influence the diffusion of scalar and vector quantities. The Advanced Heavy Water Reactor (AHWR) is a vertical pressure tube type, heavy water moderated and boiling light water cooled natural circulation based reactor. The fuel bundle of AHWR contains 54 fuel rods set in three concentric rings of 12, 18 and 24 fuel rods. This fuel bundle is divided into number of imaginary interacting flow channel called subchannels. Alteration from single phase to two phase flow situation occurs in reactor rod bundle with raise in power. The two phase flow regimes like bubbly, slug-churn, and annular flow are generally encountered in reactor rod bundle. Prediction of thermal margin of the reactor has necessitated the investigation of turbulent mixing rate of coolant between these subchannels under these flow regimes. Thus, it is fundamental to estimate the effect of spacer grids on turbulent mixing between subchannels of AHWR rod bundle.

Usage of two transmitted detectors with optimized orientation in order to three phase flow metering

Artificial neural network (ANN) is a good technique used to handle problems of modeling, prediction, control, and classification. In this study, four accurate and precise MLP model were developed. The first one was used in order to determine the type of three phase flow regime. All of the regimes were recognized correctly. Then, according to determined regime, three independent MLP models were used in order to predict the volume fraction percentages of gas, oil and water. The networks were developed based on the validated simulated data from MCNPX code. The volume fractions were measured with Mean Relative Error (MRE) of less than 1.63%.

Proper Orthogonal Decomposition as a technique for identifying two-phase flow pattern based on electrical impedance tomography

Collecting of very large amount of data from experimental measurement is a common practice in almost every scientific domains. There is a great need to have specific techniques capable of extracting synthetic information, which is essential for understanding and modelling the specific phenomena. The Proper Orthogonal Decomposition (POD) is one of the most powerful data analysis methods for multivariate and nonlinear phenomena. Generally, POD is a procedure that takes a given collection of input experimental or numerical data and creates an orthogonal basis constituted by functions estimated as the solutions of an integral eigenvalue problem known as a Fredholm equation. This paper proposes a novel approach by utilising POD to identify flow structure in horizontal pipeline, specially, for slag, plug and wavy stratified air-water flow regimes, , in which POD technique extends the current evaluation procedure of electrical impedance tomography [31]. This capability is extended by the implementation of POD as an identifier for typical horizontal two phase flow regimes. Direct POD method introduced by Lumley and Snapshot POD method introduced by Sirovich are applied The POD snapshot matrices are reconstructed from electrical tomography measurement under specific flow conditions. It is expected that this study may provide new knowledge on two phase flow dynamics in a horizontal pipeline and useful information for further prediction of multiphase flow regime.

Waves, Instabilities, and Rivulets in High Quality Microgap Two-Phase Flow

Two-phase flow in sub-millimeter microgap channels offers highly potent thermal management capability and is the foundation for the emerging "embedded cooling" paradigm of electronic cooling. While the thermofluid characteristics and operational limits of such microcoolers are intimately tied to distinct forms of vapor-liquid aggregation in the microgap channel, insufficient attention has been paid to the formation of distinct wave patterns and instabilities on the thin liquid films associated with high-quality microgap channel flow. This paper focuses on the results of visualization and heat transfer studies of such two-phase flows, under both adiabatic and diabatic conditions, for FC-72 flowing in a 184 micron microgap channel at a mass flux of 230 kg/(m2.s). The study has revealed the existence of a post-annular, high-quality Rivulet flow regime, in which the liquid film breakdown and local wall dryout drives large surface anisothermalities and limits the heat transfer rate from the wall.As predicted by the prevailing flow regime models, annular flow is found to be the dominant flow regime for this microgap configuration.. For the adiabatic conditions, flow qualities ranged between 27% and 81%, and widely spaced, 3D waves, with a wavelength that decreases with increasing flow quality, were observed on the liquid-vapor interface. For the diabatic condition, the inlet flow quality was maintained at 36% and the exit flow quality varied between 47% and 97%. For exit qualities greater than 61%, the liquid film would periodically rupture into rivulet of varying width and length. The spacing, length, and width of the rivulets varied considerably, and can easily stretch well into dryout region. The axial variation of the wall heat transfer coefficient was found to reflect and confirm the expected axial propagation of the two- phase flow regimes and the onset of local dryout associated with the newly-defined Rivulet regime.