Three-phase Flow Systems Research Articles

Characteristics of Methane Hydrate Formation in a Gas–Water–Silt Sand Three-Phase Flow System and Its Effect on Multiphase Flow Behavior

Characteristics of Methane Hydrate Formation in a Gas–Water–Silt Sand Three-Phase Flow System and Its Effect on Multiphase Flow Behavior

A portable microfluidic device for thermally controlled granular sample manipulation.

Effective granular sample manipulation with a portable and visualizable microfluidic device is significant for lots of applications, such as point-of-care testing and cargo delivery. Herein, we report a portable microfluidic device for controlled particle focusing, migration and double-emulsion droplet release via thermal fields. The device mainly contains a microfluidic chip, a microcontroller with a DC voltage control unit, a built-in microscope with a video transmission unit and a smartphone. Five microheaters located at the bottom of the microfluidic chip are used to unevenly heat fluids and then induce thermal buoyancy flow and a thermocapillary effect, and the experiments can be conveniently visualized through a smartphone, which provides convenient sample detection in outdoor environments. To demonstrate the feasibility and multifunctionality of this device, the focusing manipulation of multiple particles is first analyzed by using silica particles and yeast cells as experimental samples. We can directly observe the particle focusing states on the screen of a smartphone, and the particle focusing efficiency can be flexibly tuned by changing the control voltage of the microheater. Then the study focus is transferred to single-particle migration. By changing the voltage combinations applied on four strip microheaters, the single particle can migrate at predetermined trajectory and speed, showing attractiveness for those applications needing sample transportation. Finally, we manipulate the special three-phase flow system of double-emulsion drops in thermal fields. Under the combined effect of the thermocapillary effect and increased instability, the shell of double-emulsion droplets gradually thins and finally breaks, resulting in the release of samples in inner cores. The core release speed can also be flexibly adjusted by changing the control voltage of the microheater. These three experiments successfully demonstrate the effectiveness and multifunctionality of this thermally actuated microfluidic device on granular manipulation. Therefore, this portable microfluidic device will be promising for lots of applications, such as analytical detection, microrobot actuation and cargo release.

Online directed-structural change-point detection: A segment-wise time-varying dynamic Bayesian network approach

High-dimensional data streams exist in many applications. Generally these high-dimensional streaming data have complex directed conditional dependence relationships evolving over time. However, modeling their directed conditional dependence structure and detecting its change over time in an online way has not been well studied in the current literature. To that end, we propose an ONline Segment-wise tiMe-varying dynAmic Bayesian netwoRk model with exTernal information (ONSMART), together with an online score-based inferring algorithm for directed-structural change-point detection in high-dimensional data. ONSMART adopts a linear vector autoregressive (VAR) model to describe directed inter-slice and intra-slice relations of variables. It further takes additional information about similarities of variables into account and regularizes similar variables to have similar structure positions in the network with graph Laplacian. ONSMART allows the parameters of VAR to change segment-wisely over time to describe the evolution of the conditional dependence structure and adopts a customized pruned exact linear time algorithm framework to identify directed-structural change-point detection. The L-BFGS-B approach is embedded in this framework to obtain the optimal dependence structure for each segment. Numerical studies using synthetic data and real data from a three-phase flow system are performed to verify the effectiveness of ONSMART.

Review of bubble dynamics on charged liquid–gas flow

When a fluid is subject to an electric field, it usually processes unique features compared to the conventional fluid that arises from coupling between charged particles and fluid interface. Based on this commonality, we defined the concept of “charged multiphase flow” and constructed a generalized charged multiphase flow system using the “Tai Chi Diagram” to analyze the properties and features of different study objects, with an emphasis on the bubble dynamics on the charged liquid–gas flow object, covering the processes of bubble generation, motion, and interaction, as well as the important dynamic behaviors, involved such as bubble deformation, coalescence, and breakup. Furthermore, in light of the special plasma–liquid interface phenomenon formed by the ionization of the gas/vapor phase in the liquid phase in strong electric fields, the traditional gas–liquid–solid three-phase flow system is expanded into a broader range of multiphase flow systems involving plasma, which enriches the theoretical and frontier scientific problems of the multiphase flow. In addition, technical innovations, remaining work, and future trends in the development of the charged liquid–gas flow, and their potential applications are discussed.

On the Calibration of an Optical, High-Speed, Multiphase Microfluidic Sensor With Droplet Counting Applications in Lab-on-PCB Devices

The integration of microfluidics and droplet-based systems has led to platforms capable of characterizing multiple phases inside microchannels which can be an asset for many industries. Furthermore, recent developments on Lab-on-a-PCB devices focus to meet design specifications such as the ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users). However, most of these systems still present external equipment dependencies, complex setup and manufacturing processes, low reproducibility, along reduced information regarding calibration processes for ASSURED-based sensors. In this work, we developed a rapid and fully integrated calibration process for optical droplet-based Lab-on-PCB devices by means of an interfacial distance constant called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> , to obtain reliable and wide spectrum droplet detection and characterization results. To test the proposed calibration process, a low-cost optical droplet sensor was built using commonly available electronics components, consisting only of a fluid channel between a Light-Emitting Diode (LED) and a Light Dependent Resistor (LDR), which voltage variation is measured and processed with an Arduino Uno. After the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> calibration of the platform, we were able to characterize different multiphase flow properties such as velocity, flow rate, droplet lengths, and volume for velocities up to 1000 droplets per second with the Mean Relative Errors (MRE) ranging from 2.4% up to 17%. The lowest MRE value was obtained using a two-phase flow system for flow from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$20 \mu \text{L}$ </tex-math></inline-formula> /min up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$425 \mu \text{L}$ </tex-math></inline-formula> /min. In contrast, the highest MRE value we report was found for a three-phase flow system for droplets at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$250 \mu \text{L}$ </tex-math></inline-formula> /min.

A distributed principal component regression method for quality-related fault detection and diagnosis

Modern industrial processes are confronted with a large-scale challenge in recent years. In this paper, a novel distributed kernel principal component regression (DKPCR) approach is proposed to study the plant-wide problem of quality-related process monitoring. Along with reducing the scale of abundant measurements, the proposed approach also focuses on the robust issues that arise from the large outliers. In the local phase, every agent of the DKPCR technique processes the data of the partial sections and sends the selected information to the centralized mainframe. The engineer gathers the data from the local agents and then makes a decision based on the Bayesian inference. Additionally, the corresponding weight diagnosis approach is devised to isolate the fault-relevant variables under the smear effect by virtue of the detection results and information. In the end, the Tennessee Eastman case (TEC) and the three-phase flow system (TPFS) are leveraged to demonstrate the detection and diagnosis performance of the proposed approach.

A fully-discrete decoupled finite element method for the conserved Allen–Cahn type phase-field model of three-phase fluid flow system

In this article, we develop and analyze a novel fully discrete decoupled finite element method to solve a flow-coupled ternary phase-field model for the system consisting of three immiscible fluid components. Based on the L2-gradient flow approach, the conserved Allen–Cahn type dynamics is used to describe the free interface motion, where multiple nonlocal type Lagrange multipliers are used to accurately conserve the volume of each phase. The scheme is also linear, second-order time accurate, and unconditionally energy stable, due to the combination of several effective numerical techniques, including the two-step backward differentiation scheme, finite element discretization, explicit-SAV (scalar auxiliary variable) method for handling the nonlinearity, and projection method of Navier–Stokes equation. At each time step, the non-local splitting technique only requires solving several decoupled constant-coefficient elliptic equations. The implementation issues are discussed in detail. The solvability and the unconditional energy stability of the scheme are rigorously proved. Plenty of 2D and 3D numerical simulations are carried out to numerically demonstrate the accuracy, energy stability, and applicability of the proposed scheme.

On the relationship between capillary pressure, saturation, and interfacial area for three-phase flow in water-wet porous media

We encounter three-phase flow in porous media within a range of settings, such as enhanced oil recovery, geologic CO2 sequestration, and groundwater remediation. While an abundance of studies has been performed on the behavior of two fluid phases (e.g. oil/water or air/water) in porous media, relatively little information exists for three-phase flow systems (e.g. oil/water/air). This work explores the relationships between capillary pressure (Pc), saturation (S) and fluid-fluid interfacial area (a) for water-wet three-phase flow systems where water is the wetting phase, oil is the intermediate-wet phase, and air (or gas) is the non-wetting phase. Specifically, we examine whether the Pc-S-a relationships exhibit hysteresis during drainage and imbibition cycles. We present data collected via x-ray microtomography resulting in high-resolution three-dimensional images of the fluid configurations for varying degrees of saturation. Among the findings of the study (based on the available data), we highlight that (1) the Pc-S-a relationship is non-hysteretic for both the oil-water fluid pair, and the air-oil fluid pair, and (2) that this same relationship is independent of the initial water saturation at the point of air injection. This finding suggests that both the oil-water and air-oil fluid pairs in a three-phase system can be adequately described by the thermodynamics-based theory originally proposed by Hassanizadeh and Gray (1993), as is the case for the equivalent two-phase system.

Multivariate multiscale increment entropy: a complexity measure for detecting flow pattern transition in multiphase flows

Multivariate time series are routinely measured in real complex systems, and effective multivariate multiscale methods for uncovering the complexity of multivariate complex systems are certainly needed. In this paper, a new complexity measure for multiscale analysis of multivariate time series, namely multivariate multiscale increment entropy (MMIE), is proposed and applied to detect the nonlinear dynamic complexity of flow pattern transition in oil–gas–water three-phase flow. The MMIE can map each increment into a word of two letters, which contains sign information and magnitude information, and make coupling analysis of multivariate time series. These endow the MMIE an ability to detect the complexity of multivariate time series. The simulation analysis of typical time series shows the importance of multiscale coupling analysis of multivariate time series and the effectiveness of MMIE in mining the complexity of different multivariate time series. Finally, the MMIE is employed to analyze the multichannel sensor signals of oil–gas–water three-phase flow system, which are of multivariate and correlated. The results indicate that MMIE can effectively reveal the dynamic complexity of different flow patterns and their evolution behavior with the change of flow condition.

Dynamics and controllability of droplet fusion under gas-liquid-liquid three-phase flow in a microfluidic reactor.

Gas–liquid–liquid three-phase flow systems have unique advantages of controlling reagent manipulation and improving reaction performance. However, there remains a lack of insight into the dynamics and controllability of water droplet fusion assisted by gas bubbles, particularly scaling laws for use in the design and operation of complex multiphase flow processes. In the present work, a microfluidic reactor with three T-junctions was employed to sequentially generate gas bubbles and then fuse two dispersed water droplets. The formation of the dispersed phase was divided into multiple stages, and the bubble/droplet size was correlated with operating parameters. The formation of the second dispersed droplet at the third T-junction was accompanied by the fusion of the two dispersed water droplets that were formed. It revealed a two-stage process (i.e. drainage and fusion) for the two droplets to fuse while becoming mature by breaking-up with the secondary water supply stream. In addition, a droplet contact model was employed to understand the influence on the process stability and uniformity of the merged/fused droplets by varying the surfactant concentration (in oil), the viscosity of the water phase, and the flow rates of different fluids. The study provides a deeper understanding of the droplet fusion characteristics on gas–liquid–liquid three-phase flow in microreactors for a wide range of applications.

Compositional simulation of three-phase flow in mixed-wet shale oil reservoir

Three-phase flow is often involved during the production of shale oil reservoir. Relative permeability, which is often used to characterize multiphase flow, is found a strong function of wettability. Meanwhile, the mixed wettability in shale reservoir has been well characterized and may have impacts on fluid flow. In this work, to describe the mix-wet condition in shale, matrix is divided into organic and inorganic matrix which are hydrophobic and hydrophilic respectively. Relative permeabilities under different condition of wettability are applied in each kind of matrix. To construct permeability for three-phase flow, water-oil and oil-gas systems are evaluated separately with the assumption that water/gas permeabilities are only functions of their own saturations. Specifically, water-oil relative permeability is obtained by simulating multiphase flow directly on a digital rock sample using the lattice Boltzmann method. Oil-gas relative permeability is calculated from capillary pressure obtained from confined vapor liquid equilibria (VLE) coupled with Young-Laplace equation. Compositional simulation shows that the rich hydrocarbon in organic matrix is difficult to be produced due to the relatively lower permeability and poorer oil mobility under oil-wet condition. Since organic matter is a dispersed phase inside inorganic matter, fluids in organic matrix must flow through inorganic matrix before reaching the fractures. The dispersed nature of organic matter makes the relative permeability in inorganic matrix a dominant factor that controls the overall production in shale oil reservoir. The effect of relative permeability in organic matrix however has limited effect.

Slurry bubble column measurements using advanced electrical capacitance volume tomography sensors

A novel approach to studying dynamic three phase systems using Electrical Capacitance Volume Tomography (ECVT) is proposed and verified against previously published pressure gauge techniques and hydrodynamics patterns. In this three-phase study, hold up of water, glass beads, and air are measured simultaneously in a slurry bubble column reactor. Application of ECVT to investigate three phase systems holds several advantages over pressure gauges including the ability to deliver non-invasive real time direct measurements without making assumptions about the hydrodynamics. Results support the conclusion that ECVT can be used in place of pressure gauges to obtain accurate holdup measurements of three-phase flow systems in real time applications. The holdup of each phase inside of a three-phase slurry bubble column were measured using pressure sensors and an ECVT sensor. The results suggest that ECVT can be used in place of pressure sensors to obtain accurate holdup measurements of three-phase flows in real time. • Pressure and ECVT phase holdup measurements closely match. • ECVT reconstructed solid holdup images used to analyze bed expansion and contraction. • Solids and gas holdup measurements reflect hydrodynamic principles. • ECVT presents a valid replacement for pressure measurements in three-phase flows.

A Novel Multiphase Methodology Simulating Three Phase Flows in a Steel Ladle

Mixing phenomena in metallurgical steel ladles by bottom gas injection involves three phases namely, liquid molten steel, liquid slag and gaseous argon. In order to numerically solve this three-phase fluid flow system, a new approach is proposed which considers the physical nature of the gas being a dispersed phase in the liquid, while the two liquids namely, molten steel and slag are continuous phases initially separated by a sharp interface. The model was developed with the combination of two algorithms namely, IPSA (inter phase slip algorithm) where the gas bubbles are given a Eulerian approach since are considered as an interpenetrating phase in the two liquids and VOF (volume of fluid) in which the liquid is divided into two separate liquids but depending on the physical properties of each liquid they are assigned a mass fraction of each liquid. This implies that both the liquid phases (steel and slag) and the gas phase (argon) were solved for the mass balance. The Navier–Stokes conservation equations and the gas-phase turbulence in the liquid phases were solved in combination with the standard k-ε turbulence model. The mathematical model was successfully validated against flow patterns obtained experimentally using particle image velocimetry (PIV) and by the calculation of the area of the slag eye formed in a 1/17th water–oil physical model. The model was applied to an industrial ladle to describe in detail the turbulent flow structure of the multiphase system.

Combination of a gamma radiation-based system and the adaptive network-based fuzzy inference system (ANFIS) for calculating the volume fraction in stratified regime of a three-phase flow

Understanding the volume fraction of water-oil-gas three-phase flow is of significant importance in oil and gas industry. The current research attempts to indicate the ability of adaptive network-based fuzzy inference system (ANFIS) to forecast the volume fractions in a water-oil-gas three-phase flow system. The current investigation devotes to measure the volume fractions in the stratified three-phase flow, on the basis of a dual-energy metering system consisting of the 152Eu and 137Cs and one NaI detector using ANFIS. The summation of volume fractions is equal to 100% and is also a constant, and this is enough for the ANFIS just to forecast two volume fractions. In the paper, three ANFIS models are employed. The first network is applied to forecast the oil and water volume fractions. The next to forecast the water and gas volume fractions, and the last to forecast the gas and oil volume fractions. For the next step, ANFIS networks are trained based on numerical simulation data from MCNP-X code. The accuracy of the nets is evaluated through the calculation of average testing error. The average errors are then compared. The model in which predictions has the most consistency with the numerical simulation results is selected as the most accurate predictor model. Based on the results, the best ANFIS net forecasts the water and gas volume fractions with the mean error of less than 0.8%. The proposed methodology indicates that ANFIS can precisely forecast the volume fractions in a water-oil-gas three-phase flow system.

Numerical modelling of a three-phase internal air-lift circulating photocatalytic reactor.

The photocatalytic degradation process has been recognized as a low-cost, environmentally friendly and sustainable technology for water and wastewater treatment. As a key carrier of the photocatalytic process, the semiconductor TiO2 has been used in many studies. Analysis and modelling of hydrodynamics in the three-phase flow system can provide useful information for process design, operation and optimization of the three-phase flow photocatalytic reactor, which requires research on the mixing and flow characteristics of the interphase regions in the reactor. In this study, we modelled the hydrodynamics in an internal air-lift circulating photocatalytic reactor using an Eulerian multi-fluid approach. Localized information on phase holdup, fluid flow patterns and mixing characteristics was obtained. The simulation results revealed that the distribution of solid particle concentration depends on the flow field in the internal air-lift circulating photocatalytic reactor. The distance between the draft tube and wall of the reactor and changes in the superficial gas velocity (Ug) were found to be influential factors in reactor performance. The computational model developed could support optimizing reactor design to improve the hydrodynamics and provide guidance for scale-up.

Modeling offshore steady flow field data using drift-flux and black-oil models

The flow of oil in pipes is, in general, a multiphase flow where water, oil, gas, emulsions and sediments are transported in a co-current flow. Various complex phenomena, including mass transfer between phases, phase slip, friction pressure drop, variable geometry, compression, heat transfer and other thermodynamic effects make the flow modeling quite complex. Mixture models considering simplified empirical correlations derived from experimental observations, such as friction pressure drop and drift-flux models, are becoming increasingly used in the oil industry because of their good accuracy and simplicity. Fluid characterization is complex because it deals with multicomponent systems; therefore, empirical approaches such as black-oil models have been widely used. Modeling oil flows in real systems also requires suitable computer tools to solve equations that often need to be discretized in space and time and solved iteratively. In this paper, a stationary flow model based on a drift-flux formulation and a black-oil fluid model is developed. We present a method to integrate numerically the stationary equations and test the accuracy of a few drift-flux and two-phase multiplier correlations using steady state field data. Specifically a high pressure, three-phase flow system in deep water consisting of an offshore oil well with a 8,000m length, 6in diameter pipeline-riser system located at Tupi oilfield (Santos basin, Brazil) is used as a case study. Results show that the proposed method, as well as the fluid and flow models adopted, is suitable for the analysis of stationary oil flows in real production systems.

Droplet entrainment analysis of three-phase low liquid loading flow

Most of the commonly used multiphase flow models neglect the amount of droplets entrained in stratified wavy flow. However, the experimental data presented in this study show high entrainment values, exceeding 50% in some cases. This shows that neglecting entrainment phenomenon can introduce a major source of discrepancy into multiphase flow modeling predictions. This study improves the entrainment fraction predictions in three-phase stratified flow.The droplet entrainment in three-phase stratified flow in horizontal pipelines is experimentally investigated using a 0.152-m ID facility. The experiments are conducted under low liquid loading conditions, which is very commonly observed in wet gas pipelines. The oil-aqueous-gas flow experiments are initially performed without mono-ethylene glycol (MEG), and then repeated with 50 wt% of MEG in the aqueous phase to analyze the effects of MEG presence on entrainment. MEG is a commonly used inhibitor in oil industry, applied to avoid hydrate formation in offshore systems. Its impacts on multiphase flow droplet entrainment are investigated.The experimental range of this study covers superficial gas velocity (vSg) values from 17 to 23m/s, superficial liquid velocity (vSL) values of 0.01 and 0.02m/s, and inlet liquid stream aqueous phase fraction (APFin) values between 0 to 100%. Similar test matrix is completed for both water and water and MEG solution as the aqueous phase. An isokinetic probe system is used to measure the entrained droplet flux at different vertical positions in the gas phase. Liquid entrainment fraction is then estimated by means of volumetric averaging. The trends of the data with respect to input parameters are investigated.The two and three-phase entrainment fraction data are used for a correlation evaluation study. Performances of ten correlations for two-phase entrainment fraction are compared to the experimental data, and best performing correlations are identified. The correlation of Pan and Hanratty (2002) is modified in an effort to improve the entrainment fraction estimations. The predictions of the modified correlation are compared with the acquired data and datasets from the literature. In addition, a simple empirical correlation is proposed to predict liquid phase entrainment fraction for three-phase flow systems.

Phase field modeling and simulation of three-phase flow on solid surfaces

Phase field models are widely used to describe the two-phase system. The evolution of the phase field variables is usually driven by the gradient flow of a total free energy functional. The generalization of the approach to an N phase (N≥3) system requires some extra consistency conditions on the free energy functional in order for the model to give physically relevant results. A projection approach is proposed for the derivation of a consistent free energy functional for the three-phase Cahn–Hilliard equations. The system is then coupled with the Navier–Stokes equations to describe the three-phase flow on solid surfaces with moving contact line. An energy stable scheme is developed for the three-phase flow system. The discrete energy law of the numerical scheme is proved which ensures the stability of the scheme. We also show some numerical results for the dynamics of triple junctions and four phase contact lines.

Fast linearized forecasts for subsurface flow data assimilation with ensemble Kalman filter

Ensemble methods present a practical framework for parameter estimation, performance prediction, and uncertainty quantification in subsurface flow and transport modeling. In particular, the ensemble Kalman filter (EnKF) has received significant attention for its promising performance in calibrating heterogeneous subsurface flow models. Since an ensemble of model realizations is used to compute the statistical moments needed to perform the EnKF updates, large ensemble sizes are needed to provide accurate updates and uncertainty assessment. However, for realistic problems that involve large-scale models with computationally demanding flow simulation runs, the EnKF implementation is limited to small-sized ensembles. As a result, spurious numerical correlations can develop and lead to inaccurate EnKF updates, which tend to underestimate or even eliminate the ensemble spread. Ad hoc practical remedies, such as localization, local analysis, and covariance inflation schemes, have been developed and applied to reduce the effect of sampling errors due to small ensemble sizes. In this paper, a fast linear approximate forecast method is proposed as an alternative approach to enable the use of large ensemble sizes in operational settings to obtain more improved sample statistics and EnKF updates. The proposed method first clusters a large number of initial geologic model realizations into a small number of groups. A representative member from each group is used to run a full forward flow simulation. The flow predictions for the remaining realizations in each group are approximated by a linearization around the full simulation results of the representative model (centroid) of the respective cluster. The linearization can be performed using either adjoint-based or ensemble-based gradients. Results from several numerical experiments with two-phase and three-phase flow systems in this paper suggest that the proposed method can be applied to improve the EnKF performance in large-scale problems where the number of full simulation is constrained.

Insights into the formation mechanism of hydrate plugging in pipelines

Experiments from three-phase (natural gas+water+diesel oil) flow systems were performed in a flowloop to study the hydrate formation and plugging mechanisms from data on morphology and flow characteristics. The hydrate plugging mechanism was investigated for a range of water cuts (5–80vol%) and the injection of chemical additives (glycol and Inhibex 501). The results from the flowloop experiments demonstrated that water and oil formed a disperse system in which water formed a three-dimensional network, separating oil into a mass of oil droplets before hydrate formation; when hydrate began to form, the water network converted into a hydrate network and formed a very sticky oil-in-hydrate network system; With the hydrate formation, some of the oil was squeezed out of the network and the oil-in-hydrate network system shrank, precipitated from the oil phase, and deposited onto the pipe wall, and finally formed hydrate plugging. The presence of glycol or Inhibex 501 did not change the formation mechanism of hydrate plugging, while it decreased the hydrate formation rate.