Bulletin of the American Physical Society
73rd Annual Meeting of the APS Division of Fluid Dynamics
Volume 65, Number 13
Sunday–Tuesday, November 22–24, 2020; Virtual, CT (Chicago time)
Session X06: Multiphase Flows: Modeling and Theory (10:45am - 11:30am CST)Interactive On Demand
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X06.00001: High-Fidelity Simulation of a Rotary Bell Atomizer with Electrohydrodynamic Effects Venkata Krisshna, Mark Owkes Rotary Bell Atomizers (RBA) are extensively used as paint applicators in the automotive industry. Atomization of paint is achieved by a bell cup rotating at speeds of 40k-60k RPM in the presence of a background electric field. Automotive paint shops amount up to 70\% of the total energy costs [Galitsky et. al., 2008], 50\% of the electricity demand [Leven et. al., 2001] and up to 80\% of the environmental concerns [Geffen et al., 2000] in an automobile manufacturing facility. The atomization process in an RBA affects droplet size and velocity distribution which subsequently control transfer efficiency and surface finish quality. Optimal spray parameters used in industry are often obtained from expensive trial-and-error methods. In this work, three-dimensional near-cup atomization (primary and secondary breakup) are simulated computationally using a high-fidelity volume-of-fluid transport scheme that includes an electrohydrodynamic effects. The influence of fluid properties (viscosity ratio, flow rate and charge density), nozzle rotation rate and bell potential on atomization are investigated by performing a parametric study. This cost-effective method of research aims to identify the ideal spray parameters to achieve maximum transfer efficiency. [Preview Abstract] |
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X06.00002: The thermodynamic principle governing the interface temperature during phase change Tom Zhao, Neelesh Patankar The interface temperature during phase change (for instance, liquid to vapor) has traditionally been underspecified because the heat balance condition is used to determine the amount of mass changing phase. A common approach in boiling is to assume that the interface attains the saturation temperature according to the ambient pressure. This assumption is usually applied even under highly non-equilibrium scenarios where significant temperature jumps and mass transport exist across the interface. In this work, an ab-initio thermodynamic principle is found to fully determine the interface temperature under non-equilibrium scenarios. Physically, the thermodynamic principle not only provides a theoretical limit on the space of possible phase change rates that can occur, but also specifies the corresponding phase change rate. This principle accurately captures experimental and computational values of the interface temperature that deviate by over 50{\%} from the assumed saturation values. It also accounts for temperature jumps (discontinuities) at the interface whose difference can exceed 15 K. We find that this thermodynamic principle is a robust model to complete the phase change problem. [Preview Abstract] |
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X06.00003: Modeling polymer blend demixing: complications and simplifications in the Gibbs energy of mixing function Pierre Walker, Pavan Inguva, Kezheng Zhu, Hon Wa Yew, Andrew Haslam, Omar Matar The Cahn-Hilliard equation, which can be used to model polymer blend morphology at a continuum scale, tracks the decrease of the Gibbs energy of the system through changes in the homogenous free energy, which is given the Gibbs energy of mixing, and the interfacial energy. In most problems, the Gibbs energy of mixing function is typically set as a simple quartic polynomial or in the case of polymer blends, the Flory-Huggins equation. In certain cases, such as for mineral solutions or alloys, more suitable free energy functions have been employed. However, more accurate and complex equations of state (EoS) applicable to polymer blends such as Statistical Associating Fluid Theory (SAFT) based EoS have yet to be explored within a phase-field setting. In this work, we explore how these advanced EoS can be integrated to model binary polymer blends, looking at both thermophysical properties and blend morphology. At the other end of the complexity spectrum, we also investigate the impact of various simplifications to the free energy function and the Cahn-Hilliard equation on the numerical solution. [Preview Abstract] |
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X06.00004: Data-driven analysis and prediction of multi-component polymer precipitation Pavan Inguva, Lachlan Mason, Indranil Pan, Miselle Hengardi, Omar Matar The morphology of polymer blends can greatly impact material performance which consequently impacts the material choice and manufacturing processes. Characterizing the relationship between input parameters such as composition and thermodynamic interaction parameters, while desirable, is challenging due to the complex physics governing polymer blend precipitation which can be computationally expensive to solve numerically. To address this challenge, we present a workflow for integrating machine learning (ML) techniques to analyze and predict the output of physical simulations. We apply this workflow to study ternary polymer blends, however, it can be generalized to more complex systems. A set of ternary polymer blend morphologies is first generated using a modified multi-component Cahn-Hilliard model. The initial composition and material interaction parameters are varied. Subsequently, unsupervised ML is applied to cluster the simulation data, which is in the form of image data, into groups with distinct morphologies. With suitable cluster labels assigned to each data-point, a supervised ML algorithm can be employed to learn the non-linear relationship between the input parameters and the morphology which then enables the generation of predictive maps. [Preview Abstract] |
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X06.00005: Effects of Finite Volume Fraction on the Lift and Drag Forces in a Linear Shear Flow. Georges Akiki, S. Balachandar Eulerian-Lagrangian (EL) and Eulerian-Eulerian (EE) methods are indispensable tools for multiphase flow simulations with large number of particles where fully-resolved simulations are not possible using today’s technology. The accuracy of these methods is directly related to the accuracy of the particle-fluid sub-grid interaction coupling model used. For a uniform flow in non-dilute systems, even at low volume fractions, several studies have shown a significant increase in drag compared to a drag on a single sphere at the same Reynolds number. In this study, we perform fully-resolved Direct Numerical Simulations of random distribution of monodisperse spheres subject to a linear shear flow at a volume fraction of $\phi = 0.2$ and Reynolds number $3.5 \leq Re \leq 9$. The aim of this study is to address three main questions; i) Is the drag in a linear shear flow equal to the drag in a uniform flow at the same volume fraction and Reynolds number? ii) Does the shear-induced lift exhibit an increase due to finite volume fraction similar to the increase in drag? iii) How significant is the lift force variation within the random array of spheres compared to the mean lift? [Preview Abstract] |
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X06.00006: Dimensionless groups and regime maps in atomization by gas jetting on bubbles on a liquid surface Maksim Mezhericher, Howard Stone In our recent work we presented a novel liquid atomization process capable of generating aerosols of submicron-diameter droplets for various liquids, including pure solvents, suspensions and solutions with wide ranges of viscosity and surface tension. The atomization process is based on disintegration by gas micro-jets of thin liquid films formed as bubbles on a liquid surface. In our previous work we demonstrated that the new atomization process is governed by several nondimensional groups including three dimensionless numbers that were not described before in the literature. Here we investigate the interpretation of our results in terms of the dimensionless parameters. We show that the diameters of the droplets are governed by the interplay of process timescales including capillary Rayleigh breakup, liquid viscosity and gas jet pressure, and those timescale ratios can be converted into ratios of specific energies provided by the gas jets and dissipated by the atomized liquid. We also demonstrate that a flow rate of droplets of a given diameter is governed by the ratios of energy rates corresponding to the above timescales. Finally, we develop two regime maps for prediction of the droplet diameters and flow rate of droplets in the new process. [Preview Abstract] |
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X06.00007: Pairwaise Interaction Extended Point-Particle (PIEP) model for Compressible Multiphase problem Smyther Hsiao, Kambiz Salari, S. Balachandar An efficient means to compute multiphase flow problems is to utilize the Euler-Lagrange simulation method. Previously, various developments have been made for the case in the incompressible regime. However, due to the complex nature of compressible multiphase flows, details of the model are re-examined. With a steady compressible inflow, the forces experienced by a particle is expressed as functions of the surface averaged flow properties perturbed by a neighboring particle, such as density, Mach number, pressure gradient, etc. Furthermore, the shock phenomenon is considered by using the experimental drag coefficient. Comparison is made between the modeled force and that from a particle-resolved 2-sphere simulation at Mach number 3. It is observed that around the wake region of an upstream neighboring particle, subsonic communication can occur which slows the down local flow, causing a further reduction in the modeled drag coefficient compared to the simulation. [Preview Abstract] |
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X06.00008: Towards accurate prediction and statistical quantification of two phase regimes through system identification and recurrent neural networks Naseem Ali, Bianca Viggiano, Murat Tutkun, Raul Cal Two different multiphase flow regimes including slug and dispersed flows are considered here to apply system identifications and obtain reduced order models. Unlike the balanced decomposition, system identification extracts a linear state-space model from impulse response data without the use of adjoint information. The system identification model precisely captures the flow dynamics of the flow regimes. The model also provides state-space representation in terms of frequency by defining the transfer function. The system identification results are compared with that of the long-short term memory neural network to predict the state of the flow regimes. [Preview Abstract] |
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X06.00009: Surface tension induced translational and rotational motion of a droplet with viscosity variation Gaojin Li, Donald Koch A droplet releasing oil into a micellar solution can undergo spontaneous translational motion due to Marangoni flows. Recent experiments with two-component oil droplet emulsions show that the oil droplet exhibits transition between ballistic and spiraling motions depending on the relative size of coexisting (low viscosity) isotropic and (higher viscosity) liquid crystalline phases. This transition could be used to engineer programmed active drops to effectively search a desired portion of a fluid domain in applications such as targeted drug delivery or pollutant harvesting. To understand the mechanisms behind this phenomenon, we analyze the translational and rotational instabilities of a two-dimensional drop with two compartments of different viscosity. Using both linear stability analysis and direct numerical simulation, we show that the viscosity variation inside the drop leads to earlier transitions from quiescent state to spontaneous translational motion and coupled translational and rotational motion than predicted for a single-phase drop. [Preview Abstract] |
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X06.00010: Preserving isentropic consistency in multi-fluid systems: basic energy closures and variational evolution equations Eric Heulhard de Montigny, Antoine Llor Multi-fluid modeling is required in systems involving numerous entangled mesoscale physical phenomena (bubbles, particles, surface effects, transport, mass-transfer, chemical reactions, turbulence, etc.). It is generally produced by applying some \emph{fluid conditional averaging} to the basic evolution equations (such as mass, momentum, and energy) and closing the ensuing unknown correlations.\\ However, this procedure does not yield a clear separation between non-dissipative and dissipative correlations, which are critical in understanding multi-fluid behavior and simulation. In particular, many systems follow quasi-isentropic dissipation-free evolution but their simulation appears fragile with respect to numerical errors or approximations as it is basically ``living at the edge of stability'' [Int. J. Multiphase Flow 103324, 2020].\\ Hamilton’s least action principle is a universal approach to constrain the isentropic self-consistency of evolution equations. It is here applied to multiple velocity systems involving added mass, external and internal turbulence, surface tension, and equal pressure constraints. Combined with Gibbs' internal energy evolution equations, it yields non-trivial but efficient expressions suited for robust thermodynamically-consistent simulations. [Preview Abstract] |
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X06.00011: Experiments with Reduced Order Models for 2D turbulent Multiphase Flows Xianyang Chen, Jiacai Lu, Gretar Tryggvason The development of reduced order models for multiphase turbulent flows pose multiple challenges, including a large range of scales, complex evolving interfaces, and the interaction of interface generated vorticity and fluid turbulence. While traditional models usually depend on removing high frequency modes by filtering, in fluid mechanics there is a long tradition of reducing the degrees of freedom by singularization, such as by replacing bubbles and drops by point particles and compact vortices by point vortices. We introduce a formal process called weighted coordinates smoothing to singularize the flow field and apply it to simplify both the interface and the velocity field, for two-dimensional flow. As in other reduced order models for complex flows, it is necessary to account for the effects of processes not fully resolved by adding closure terms and we present our initial attempts to do so, including using artificial neural network to correlate the terms. For the flow field, we compare predictions from an augmented point vortex model with results from a more classical approach where we smooth the flow field and use machine learning to relate the subgrid stresses to the average flow. [Preview Abstract] |
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X06.00012: A computational model for heat and mass transfer across interfaces in two-phase flows using phase field methods Shahab Mirjalili, Suhas S Jain, Ali Mani Two-phase flows involving interfacial heat/mass transfer are widespread in industrial and environmental applications such as chemical reactors, bubbly flows, combustion, boiling, carbon sequestration and ocean-atmosphere exchanges. Thus, it is important to accurately predict the interfacial transfer of heat/mass via numerical simulations. Modeling the interfacial transfer between the two-phases is particularly challenging for phase field (diffuse interface) methods. In the context of these methods, by assuming a micro-structure that is consistent with the interfacial profile, we use perturbation theory and asymptotic analysis of thin films to derive interfacial heat/mass exchange terms that are consistent extensions of the underlying phase field equations. The developed model is conservative and correctly predicts the transient and equilibrium solutions in all limits of diffusivity ratio. Canonical and realistic simulations are presented to demonstrate the consistency, accuracy and convergence of the model. [Preview Abstract] |
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X06.00013: Residual Terms in the Spatially Filtered Fluid Momentum Equation for a Particle--laden Suspension Menglin Ni, Mohammad Mehrabadi, Jesse Capecelatro, Shankar Subramaniam Spatially filtering the disperse two-phase flow equations results in the volume-filtered Euler-Lagrange (VFEL) method that can efficiently simulate large domains, and capture a wide range of scales including mesoscale structures corresponding to particle clustering. However, spatial filtering results in unclosed residual terms in the VFEL equations which need to be modeled. These are traditionally closed using ensemble-averaged models, such as the average drag on a particle in a suspension (Capecelatro and Desjardins (2013)) for the residual filtered interphase momentum exchange term. Here we quantify the unclosed terms in the filtered momentum equation for a particle-laden suspension using particle resolved direct numerical simulation (PR-DNS). Using the indicator function approach we derive the exact interphase momentum exchange term, which differs slightly from the approximate expression given by Capecelatro and Desjardins (2013) for the interphase momentum exchange term that was based on simplifying assumptions of Anderson and Jackson (1967). PR-DNS data from statistically steady flow past a statistically homogeneous particle assembly is filtered to quantify both exact and approximate versions of the interphase momentum exchange term for different filter widths. [Preview Abstract] |
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X06.00014: Investigation of the compressible MRG force model for simulations of detonation-driven particle motion -- comparison against microscale experiments Joshua Garno, Thomas Jackson, S. Balachandar For the case of a modest air shock traversing a spherical particle, the compressible Maxey-Riley-Gatignol (MRG) force model has been shown to capture the rapid momentum exchange due to the fluid-particle interaction. With high-quality data from an explosive multiphase experiment, this work explores the predictive capability of the model in the detonation-driven flow regime. Following a UQ-driven calibration of explosive model parameters, a time-dependent simulation flow field is presented that is in agreement with experimental data. Spatial and temporal variation of flow properties on the scale of the particle are considered in the Fax\'{e}n form of the particle force model, employed in the finite-volume, Euler-Lagrange simulations. Carefully-timed X-ray exposures provide the trajectories of a few tungsten particles accelerated from an initial explosion for comparison with the simulation results for evaluation of the accuracy of the force model. [Preview Abstract] |
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X06.00015: Representing Number Fluctuations in Disperse Multiphase Flow using the Filtered Klimontovich Density Shankar Subramaniam Fluctuations in number of particles, droplets or bubbles are closely related to clustering phenomena and instabilities in disperse multiphase flow that can span a wide range of time and length scales. The number density function (NDF) in gas-solid flow, and its equivalent the droplet distribution function (DDF) in sprays, forms the basis of kinetic theory descriptions of disperse multiphase flow. The NDF (DDF) is the ensemble average of the Klimontovich density (KD) and represents first-order ensemble-averaged quantities such as the ensemble-averaged particle number density and volume fraction. The NDF does not contain information concerning fluctuations in particle number (or volume). Spatial filtering of the KD has the advantage of capturing scale--dependent fluctuations and is a path to rigorously incorporate second--order statistical information characterizing number fluctuations by explicitly modeling it in a one--particle theory. I propose a new Euler-Lagrange formulation involving spatial filtering of the KD, but its promise can be realized only insofar as the accuracy of models for the unclosed terms in its transport equation. PR--DNS can be used to quantify these unclosed terms at the microscale because the formulation is reconcilable across micro, meso and macroscales. [Preview Abstract] |
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