Multiphase Fluid Flow Research Articles

An improved lattice Boltzmann model for high gas and liquid density ratio in composite grids

Lattice Boltzmann method is one of the widely used in multiphase fluid flow. However, the two main disadvantages of this method are the instability of numerical calculations due to the large density ratio of two phases and impossibility of the temperature distribution to be fed back into the velocity distribution function when the temperature is simulated. Based on the combination prescribed by Inamuro, the large density ratio two-phase flow model and thermal model makes the density ratio of the model simulation to be increased to 2778:1 by optimizing the interface distribution function of two-phase which improves the accuracy of differential format. The phase transition term is added as source term into the distribution function controlling two phase order parameters to describe the temperature effect on the gas-liquid phase transition. The latent heat generated from the phase change is also added as a source term into the temperature distribution function which simulates the movement of the flow under the common coupling of density, velocity, pressure and temperature. The density and the temperature distribution of single bubble are simulated. Comparison of the simulation results with experimental results indicates a good agreement pointing out the effectiveness of the improved model.

Rapid Laser Manufacturing of Microfluidic Devices from Glass Substrates.

Conventional manufacturing of microfluidic devices from glass substrates is a complex, multi-step process that involves different fabrication techniques and tools. Hence, it is time-consuming and expensive, in particular for the prototyping of microfluidic devices in low quantities. This article describes a laser-based process that enables the rapid manufacturing of enclosed micro-structures by laser micromachining and microwelding of two 1.1-mm-thick borosilicate glass plates. The fabrication process was carried out only with a picosecond laser (Trumpf TruMicro 5×50) that was used for: (a) the generation of microfluidic patterns on glass, (b) the drilling of inlet/outlet ports into the material, and (c) the bonding of two glass plates together in order to enclose the laser-generated microstructures. Using this manufacturing approach, a fully-functional microfluidic device can be fabricated in less than two hours. Initial fluid flow experiments proved that the laser-generated microstructures are completely sealed; thus, they show a potential use in many industrial and scientific areas. This includes geological and petroleum engineering research, where such microfluidic devices can be used to investigate single-phase and multi-phase flow of various fluids (such as brine, oil, and CO2) in porous media.

Effect of Current Density on Metal Droplet Dropping and Solidification in an ESR System

The effects of current density on the multiphase fluid flow and solidification in the electroslag remelting (ESR) system are numerically investigated using the 3D mathematical model. The results show that with the increase of current density, the remelting rate of the consumable electrode increases and the dropping behavior of the molten metal at the electrode tip changes from discontinuous droplets to a continuous stream. Also, the turbulent flow in the slag pool becomes intensive, and both the slag and metal pool temperatures increase, resulting in the formation of a deep U-type metal pool. When the current density increases from 8000 A to 10,000 A, the Joule heat increases from 434.326 kW to 678.635 kW, the remelting rate of the electrode increases from 230 kg/h to 390 kg/h, the maximum temperature in the slag pool increases from 1927 K to 1993 K, and the metal pool depth increases from 115 mm to 182 mm.

Fluid Flow, Dissolution, and Mixing Phenomena in Argon-Stirred Steel Ladles

In the current study, the multiphase fluid flow in argon-stirred steel ladles is simulated using an Eulerian–Lagrangian two-phase approach. The momentum source and the turbulent kinetic energy source due to the motion of the bubble are considered for the liquid phase. Argon bubbles are treated as discrete phase particles, and the interfacial forces between the bubbles and the liquid phase; the dependence of the gas density and the bubble diameter on the temperature and the static pressure; and the bubble size distribution are considered. When the fluid flow reaches the quasi-steady state, the ferroalloy melting and mixing phenomena is also modeled. The melting time and the trajectory length of each ferroalloy particle are recorded using a user-defined function (UDF). Local mixing time is predicted in the entire computational domain by checking the mixing criteria in every cell. The effects of gas flow rate, porous plug location, and separation angle of two porous plugs on the fluid flow and the mixing phenomena are investigated. The results show that the flow intensity increases, and the mixing time decreases with the increasing gas flow rate. The optimal porous plug’s radial position with one porous plug is 0.50R for its best mixing condition. When two porous plugs are adopted, the separation angle of 90 deg is recommended to improve the flow field and mixing phenomena.

Effects of Interphase Forces on Fluid Flow in Gas-Stirred Steel Ladles Using the Eulerian–Lagrangian Multiphase Approach

The multiphase fluid flow in a gas-stirred system for steelmaking ladles is simulated using an Eulerian–Lagrangian approach. The effects of interphase forces and the bubble-induced turbulence on the fluid flow and the bubble behavior are analyzed by comparing with the measured data. It is found that the drag force strongly affects the velocity field and bubble volume fraction in the plume, but hardly influences the bubble plume shape. The lift force is mainly responsible for the spreading of the bubble plume, and the bubble plume becomes wider as the lift coefficient increases. The virtual mass force has a significant effect on the bubble volume fraction and should be considered reasonable. The pressure gradient force is negligible because it hardly affects the bubble plume dynamic. On increasing the bubble-induced turbulence, the bubble plume becomes wider and the liquid velocity and the bubble volume fraction in bubble plume are reduced.

Application of Adaptive Neuro-Fuzzy Inference System and Optimization Algorithms for Predicting Methane Gas Viscosity at High Pressures and High temperatures Conditions

Accurate estimation of methane viscosity is extremely important for petroleum engineers. Methane viscosity as an important property is used to model multiphase fluid flow in porous media. The viscosity of methane is usually presented as a function of pseudoreduced pressure ( $${P}_{\mathrm{pr}})$$ and pseudoreduced temperature ( $${T}_{\mathrm{pr}})$$ and can be obtained using correlations and charts. Nevertheless, the prediction of methane viscosity at high pressure and high pressure (HPHT) by correlations is associated with some level of uncertainties. Moreover, in the available charts, the methane viscosities are not presented at HPHT conditions. Therefore, having an accurate model that can predict the viscosity of methane at HPHT conditions is beneficial. Therefore, in this study, adaptive neuro-fuzzy inference system (ANFIS) as a powerful intelligent tool is used to predict the viscosity of methane at HPHT using literature experimental data. Two hybrid ANFIS-based models are developed. In the first model, particle swarm optimization (PSO) is employed to find the optimum ANFIS model parameters (ANFIS-PSO), while in the second model, the genetic algorithm (GA) optimization is applied (ANFIS-GA). The results show a better prediction of methane viscosity by the ANFIS models compared to those by models and correlations from the literature. Moreover, ANFIS-GA model shows slightly better prediction than the ANFIS-PSO model. In fact, ANFIS-GA model possesses the lowest average absolute relative deviation, the lowest mean squared error, and the highest correlation coefficient. The findings from the present work demonstrate that the proposed ANFIS-GA model can be easily implemented in any reservoir simulation software, and it provides superior accuracy and performance in reservoir simulators.

Dynamics of Viscous Entrapped Saturated Zones in Partially Wetted Porous Media

As a typical multiphase fluid flow process, drainage in porous media is of fundamental interest in nature and industrial applications. During drainage processes in unsaturated soils and porous media in general, saturated clusters, in which a liquid phase fully occupies the pore space between solid grains, affect the relative permeability and effective stress of the system. In this study, we experimentally studied drainage processes in unsaturated granular media as a model porous system. The distribution of saturated clusters is analysed by an optical imaging method under different drainage conditions, in which pore-scale information from Voronoi and Delaunay tessellation was used to characterise the topology of saturated cluster distributions. By employing statistical analyses, the observed spatial and temporal information of multiphase flow and fluid entrapment in porous media are described. The results indicate that the distributions of both the crystallised cell size and pore size are positively correlated to the spatial and temporal distribution of saturated cluster sizes. The saturated cluster size is found to follow a lognormal distribution, in which the generalised Bond number correlates negatively to the scale parameter and positively to the shape parameter. These findings can be used to connect pore-scale behaviour with overall hydro-mechanical characteristics in partially saturated porous media, using both the degree of saturation and generalised Bond number.

Modeling fluid transport in two-dimensional paper networks

Paper-based microfluidic devices offer great potential as a low-cost platform to perform chemical and biochemical tests. Commercially available formats such as dipsticks and lateral-flow test devices are widely popular as they are easy to handle and produce fast and unambiguous results. Although these simple devices lack precise control over the flow to enable integration of complex functionality for multistep processes or the ability to multiplex several tests, intense research in this area is rapidly expanding the possibilities. Modeling and simulation is increasingly more instrumental in gaining insight into the underlying physics driving the processes inside the channels; however, simulation of flow in paper-based microfluidic devices has barely been explored to aid in the optimum design and prototyping of these devices for precise control of the flow. We implement a multiphase fluid flow model through porous media for the simulation of paper imbibition of an incompressible, Newtonian fluid such as when water, urine, or serum is employed. The formulation incorporates mass and momentum conservation equations under Stokes flow conditions and results in two coupled Darcy’s law equations for the pressures and saturations of the wetting and nonwetting phases, further simplified to the Richard’s equation for the saturation of the wetting fluid, which is then solved using a finite element solver. The model tracks the wetting fluid front as it displaces the nonwetting fluid by computing the time-dependent saturation of the wetting fluid. We apply this to the study of liquid transport in two-dimensional paper networks and validate against experimental data concerning the wetting dynamics of paper layouts of varying geometries.

Sequential fully implicit formulation for compositional simulation using natural variables

The Sequential Fully Implicit (SFI) method was proposed [12], in the context of a Multiscale Finite Volume (MSFV) formulation, to simulate coupled immiscible multiphase fluid flow in porous media. Later, Lee et al. [15] extended the SFI formulation to the black-oil model, whereby the gas component is allowed to dissolve in the oil phase. Most recently, the SFI approach was extended to fully compositional isothermal displacements by Moncorgé et al. [21]. SFI schemes solve the fully coupled system in two steps: (1) Construct and solve the pressure equation (flow problem). (2) Solve the coupled species transport equations for the phase saturations and phase compositions. In SFI, each outer iteration involves this two-step sequence. Experience indicates that complex interphase mass transfer behaviors often lead to large numbers of SFI outer iterations compared with the Fully Implicit (FI) method. Here, we demonstrate that the convergence difficulties are directly related to the treatment of the coupling between the flow and transport problems, and we propose a new SFI variant based on a nonlinear overall-volume balance equation. The first step consists of forming and solving a nonlinear pressure equation, which is a weighted sum of all the component mass conservation equations. A Newton-based scheme is used to iterate out all the pressure dependent nonlinearities in both the accumulation and flux terms of the overall-volume balance equation. The resulting pressure field is used to compute the Darcy phase velocities and the total-velocity. The second step of the new SFI scheme entails introducing the overall-mass density as a degree-of-freedom, and solving the full set of component conservation equations cast in the natural-variables form (i.e., saturations and phase compositions). During the second step, the pressure and the total-velocity fields are fixed. The SFI scheme with a nonlinear pressure extends the SFI approach of Jenny et al. [12] to multi-component compositional processes with interphase mass transfer. The proposed compositional SFI approach employs an overall balance for the pressure equation; however, unlike existing volume-balance Sequential Implicit (SI) schemes [1,34,32,27,10,9], which use overall compositions, this SFI formulation is well suited for the natural variables (saturations and phase compositions). We analyze the ‘splitting errors’ associated with the compositional SFI scheme, and we show how to control these errors in order to converge to the same solution as the Fully Implicit (FI) method. We then demonstrate that the compositional SFI has convergence properties that are very comparable to those of the FI approach. This robust sequential-implicit solution scheme allows for designing numerical methods and linear solvers that are optimized for the sub-problems of flow and transport. The SFI scheme with a nonlinear pressure formulation is well suited for multiscale formulations, and it promises to replace the widely used FI approach for compositional reservoir simulation.

Numerical simulations of oil flow inside a gearbox by Smoothed Particle Hydrodynamics (SPH) method

Abstract In this paper, numerical simulations of oil flow inside a gearbox are presented and compared to experimental particle image velocimetry (PIV) results. Instead of a traditional grid-based finite volume method, a mesh-free Smoothed Particle Hydrodynamics (SPH) method is employed. A multi-phase SPH formulation is utilized to resolve the complex multiphase fluid flow. A total of nine simulations are carried out for three oil levels and three Reynolds numbers, to investigate the flow field behavior and to compare with the experimental results. The aeration effect is first considered to qualitatively analyze the quantity and size of bubbles generated due to the rotation of the gears. Furthermore, the velocity field and velocity profile beneath the oil surface are comprehensively analyzed. Our simulation results exhibit physically consistent behavior of the oil flow and good agreement is achieved compared to the experimental results. Flow structures, splashing and recirculation areas are very well captured by the simulation. However, some discrepancies of the velocity field between the numerical and experimental results are also observed, and discussed.

An optimization algorithm for evaluation of kinetic parameters for crude oil combustion

The design of enhanced oil recovery processes that employ in-situ combustion requires high-fidelity simulation models that accurately describe the physics and chemistry of reactive, exothermic multiphase fluid flow. Therefore, a detailed description of oil combustion kinetics is required. The goal of this work is to present and apply a workflow to define and match pseudo-kinetic reaction models based on Arrhenius kinetics. These models are meant to be used at the laboratory scale with high-resolution, fully-resolved simulation models as a tool to generate high density data required by upscaled models at reservoir scale.The workflow starts by performing ramped temperature oxidation (RTO) experiments for a wide range of heating rates. New experimental equipment has allowed us to obtain data for large heating rates (>15°Cmin ) that were not achievable in the past. A subset of the experiments are selected to match the oxygen consumption curves by tuning kinetic parameters of several global reaction models using pattern search optimization. Those models that obtain a match are validated by predicting a second subset of the data that was not considered during the optimization. The workflow is tested using a heavy oil and two satisfactory matches with two different global reaction models are obtained.

Geologic CO2 sequestration monitoring design: A machine learning and uncertainty quantification based approach

Monitoring is a crucial aspect of geologic carbon dioxide (CO2) sequestration risk management. Effective monitoring is critical to ensure CO2 is safely and permanently stored throughout the life-cycle of a geologic CO2 sequestration project. Effective monitoring involves deciding: (i) where is the optimal location to place the monitoring well(s), and (ii) what type of data (pressure, temperature, CO2 saturation, etc.) should be measured taking into consideration the uncertainties at geologic sequestration sites. We have developed a filtering-based data assimilation procedure to design effective monitoring approaches. To reduce the computational cost of the filtering-based data assimilation process, a machine-learning algorithm: Multivariate Adaptive Regression Splines is used to derive computationally efficient reduced order models from results of full-physics numerical simulations of CO2 injection in saline aquifer and subsequent multi-phase fluid flow. We use example scenarios of CO2 leakage through legacy wellbore and demonstrate a monitoring strategy can be selected with the aim of reducing uncertainty in metrics related to CO2 leakage. We demonstrate the proposed framework with two synthetic examples: a simple validation case and a more complicated case including multiple monitoring wells. The examples demonstrate that the proposed approach can be effective in developing monitoring approaches that take into consideration uncertainties.

Modeling on the Fluid Flow and Mixing Phenomena in a RH Steel Degasser with Oval Down‐Leg Snorkel

The RH vacuum refining process is vitally important for the production of ultra‐low‐carbon steels, due to its effective degassing and homogenizing. A combined physical and mathematical modeling approach is performed in the current study to investigate the multiphase fluid flow and mixing phenomena during the RH vacuum refining process. The numerical simulation coupled VOF and DPM is used to obtain the flow pattern and the interface profile in the RH reactor in the water‐air system. Turbulent characteristics are predicted by a modified k‐ϵ model. A water model is used to validate calculated results. Based on the results of RH water modeling, the 2D‐velocity distribution in the section Y = 0 is captured by particle image velocimetry (PIV) system. To improve the refining efficiency and the service life time of the RH reactor, a new designed RH degasser with an optimized down‐leg snorkel is established. The oval down‐leg snorkel with a larger cross‐sectional area will increase the circulation rate of the fluid by 20% and weaken the impact on the ladle wall compared with the traditional one, which has immense potential in future applications to improve the service life of the ladle.

Sequential implicit nonlinear solver for geothermal simulation

Modeling of thermal multiphase fluid flow in subsurface porous media poses significant difficulties for nonlinear solvers. These difficulties are a result of the strong coupling between the mass and energy conservation equations through the thermodynamic relationships. In particular, for geothermal problems, this tight coupling results in an apparent “negative compressibility” for cells (control volumes) that have two fluid phases (liquid and vapor) during the time interval of interest. This behavior is associated with the flow of cold water into a cell that is at saturated conditions. As steam condensation occurs, the reduction in fluid volume due to the phase change is larger than the expansion of the liquid and vapor due to injection. As a result, the cell pressure decreases as condensation proceeds. This pressure decrease leads to an increase in the inflow of cold water until the condensation is complete. During the condensation period, the overall compressibility of the system is negative, and this poses serious convergence problems even when a fully implicit (i.e., backward Euler) time discretization is used. In order to deal with this problem, nonlinear solvers must be modified. In this work, we present a nonlinear solution strategy that overcomes the negative compressibility associated with the condensation front. We first consider a single-cell problem that demonstrates the negative compressibility phenomenon. Then, we describe a solution strategy that overcomes the nonlinear convergence difficulties. We then derive a criterion that can be used as a nonlinear preconditioning strategy to solve multicell problems. The effectiveness of the proposed nonlinear solution scheme is then demonstrated for more complex models. It was found that for one-dimensional problems, this nonlinear solution strategy converges for all timesteps sizes, while the fully coupled strategy only converges for a limited sized timestep. Furthermore, for a two-dimensional heterogeneous problem, the largest Courant–Friedrichs–Lewy (CFL) number for this method is at least an order of magnitude larger than the CFL number that can be used with the fully coupled approach.

On modeling of MPS‐based multiphase fluid flow with low density ratios

SummaryA divergence‐free moving particle semi‐implicit framework has been formulated for modeling of multiple miscible fluids having small density ratios (≤ 1.10) in the presence of free surface. A density‐weighted pressure gradient along with a hybrid free‐surface treatment is specifically adopted to incorporate the effect of marginal density difference through a higher‐order kernel. The hybrid free‐surface treatment reduces error in velocity divergence and resulting spurious velocity fluctuation in the vicinity of free surface for low‐velocity system. Scalar transport equation is resolved to update density associated with the particles at every time step. A total of 9 cases of lock‐exchange flow with different lock positions and density ratios have been utilized to validate the proposed framework. The model performs satisfactorily irrespective of lock positions and low density variations (3%‐9%).

Microfluidic Devices Developed for and Inspired by Thermotaxis and Chemotaxis.

Taxis has been reported in many cells and microorganisms, due to their tendency to migrate toward favorable physical situations and avoid damage and death. Thermotaxis and chemotaxis are two of the major types of taxis that naturally occur on a daily basis. Understanding the details of the thermo- and chemotactic behavioral response of cells and microorganisms is necessary to reveal the body function, diagnosing diseases and developing therapeutic treatments. Considering the length-scale and range of effectiveness of these phenomena, advances in microfluidics have facilitated taxis experiments and enhanced the precision of controlling and capturing microscale samples. Microfabrication of fluidic chips could bridge the gap between in vitro and in situ biological assays, specifically in taxis experiments. Numerous efforts have been made to develop, fabricate and implement novel microchips to conduct taxis experiments and increase the accuracy of the results. The concepts originated from thermo- and chemotaxis, inspired novel ideas applicable to microfluidics as well, more specifically, thermocapillarity and chemocapillarity (or solutocapillarity) for the manipulation of single- and multi-phase fluid flows in microscale and fluidic control elements such as valves, pumps, mixers, traps, etc. This paper starts with a brief biological overview of the concept of thermo- and chemotaxis followed by the most recent developments in microchips used for thermo- and chemotaxis experiments. The last section of this review focuses on the microfluidic devices inspired by the concept of thermo- and chemotaxis. Various microfluidic devices that have either been used for, or inspired by thermo- and chemotaxis are reviewed categorically.

Computations of Homogeneous Multiphase Real Fluid Flows at All Speeds

Computations of all-speed multiphase real fluid flows for aerospace launch vehicles are known to be very demanding, owing to several issues that include robust capturing of two-phase shock/phase discontinuity and proper scaling of numerical flux at steady/unsteady all-speed flows. This paper deals with the development of computational components to overcome difficulties arising from these issues. First, the shock-discontinuity-sensing term used in the two-phase and RoeM schemes is modified because the existing shock-discontinuity-sensing term is not suitable for complex equation of state of real fluids. The accuracy of the two-phase and RoeM schemes for unsteady low-Mach-number flows is then improveed through separate scaling of the velocity- and pressure-difference terms. It is demonstrated that the resulting schemes are capable of robustly and accurately capturing phenomena involving shock and phase discontinuities and interactions between them for numerous two-phase problems. Finally, numerical simulations of cryogenic cavitation and three-dimensional cavitating flows around the Korea Aerospace Research Institute turbopump are presented to confirm accurate and robust behavior of the proposed approaches in computations of multiphase real fluid flows at all speeds.

Non-isothermal simulation of the behavior of unsaturated soils using a novel EFG-based three dimensional model

In this paper, a three-dimensional simulation of fully coupled multiphase fluid flow and heat transfer through deforming porous media is presented in the context of EFG mesh-less method. Spatial discretization of the system of governing equations is performed using EFG and a fully implicit finite difference scheme is employed for temporal discretization. Penalty method is used for imposition of essential boundary conditions. The developed numerical tool is employed to simulate two problems of nuclear waste disposal and CO2 sequestration in deep underground strata. The obtained results demonstrate the capability and robustness of the developed EFG code.

A quick method to fabricate large glass micromodel networks

The study of multi-phase fluid flow in microfluidic devices provides an opportunity for researchers to characterize effective factors and mechanisms in microscale. The application of microtechnology in various fields of science and engineering has always raised different technical problems that require further research and developments. This paper aims to address the associated challenges with micromodel studies that employ the chemical (wet) etching method for making glass micromodels. To overcome these challenges, recent advances in chemical etching are modified and combined to decrease the construction time and costs. The general steps in the chemical etching process are masking, etching, and bonding. First, the common masking step [projecting the designed pattern (regular or irregular) on the acid-resistant layer] in this work is simplified by engraving the mirror plates with a CO2 laser. This new technique skips the required facilities for photoresist layer deposition and UV lithography by using direct laser beam machining of pre-coated soda lime glasses (mirror). Moreover, the variety of mirror products and flexible functionality of laser machines make it possible to create larger size models with any desirable flow pattern. Next, the general composition of solution used in the etching step and the operating conditions of thermal bonding step are modified based on recent investigations in literature to enhance the mechanical strength of the micromodel. Finally, the fabricated model with this procedure is applied in a two-phase flow visualization study to examine the practical features under experimental conditions.

Drag coefficient and strouhal number analysis of a rectangular probe in a two-phase cross flow

In some case of laboratory and industrial applications, various kind of measurement instruments must be placed in a conduit, in which multiphase fluid flows. Vortex shedding for any immersed body in flow field is created with a frequency, which according to flow conditions such as flow rates, geometry of body, etc. may be constant or variable. Failure may happen, if this frequency is close to one of the natural frequencies of the instruments. These flows can play a significant role in long-term reliability and safety of industrial and laboratory systems. In this study, an Eulerian–Eulerian approach is employed to simulate Air-Water two-phase flow around a rectangular probe with different volume fractions (0.01-0.5) and Reynolds numbers (1000-3000). Two-phase flow characteristics around the probe have been analyzed numerically. The results show vortex shedding in all cases with distinct Strouhal number. In addition, results illustrate that shedding is intensified by increasing Reynolds number. In order to validate the results, fraction of inlet volume was set to zero, and drag coefficient and its relation with low Reynolds number (1000-3000) in single phase flow were compared to experimental and numerical results in published article. The results show a complete agreement between the simulation and available data.