Bulletin of the American Physical Society
77th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 24–26, 2024; Salt Lake City, Utah
Session R21: Computational Methods for Bubbly and Cavitation Flows |
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Chair: Ashish Dhanalakota, University of Illinois at Urbana-Champaign Room: 250 E |
Monday, November 25, 2024 1:50PM - 2:03PM |
R21.00001: A hybrid immersed boundary-lattice Boltzmann method solver for modeling encapsulated microbubbles Morteza Garousi, Michael L Calvisi Encapsulated microbubbles (EMBs) have biomedical applications that include ultrasound imaging and targeted drug delivery. EMBs are modeled as a gas core surrounded by a thin, viscoelastic coating immersed in a viscous liquid, therefore, numerical simulation of their dynamic response to acoustic forcing is a complicated multiphase flow problem that involves fluid-structure interaction. Upon insonation, an EMB can undergo both spherical (volumetric) and nonspherical (shape) oscillations. In this study, we use a multicomponent multiphase lattice Boltzmann method (LBM) to solve for the fluid dynamics of the interior and exterior fluid phases and couple this with the immersed boundary (IB) method to account for the fluid-structure interaction between the fluid phases and the encapsulation. This hybrid IB-LBM solver explicitly solves for the bubble surface shape via tracking Lagrangian markers placed on the interface, and can account for nonspherical deformations. The force exerted on the surrounding fluids by the EMB coating is incorporated into the IB-LBM solver using a viscoelastic constitutive model. Simulations of the EMB response to step and sinusoidal variations in far-field pressure using the IB-LBM solver are validated against the modified Rayleigh-Plesset equation and other results in the scientific literature. The accuracy of the IB-LBM model is analyzed with respect to the stencil choice for the kernel function used for velocity interpolation and force spreading, and also with respect to the choice of time integration scheme for advecting the EMB surface. |
Monday, November 25, 2024 2:03PM - 2:16PM |
R21.00002: Direct numerical simulation of two-way coupled microbubble and flow dynamics beneath surface waves LI-AN HSIEH, WU-TING TSAI We present a direct numerical simulation model that couples the dynamics of microbubbles with the boundary-layer turbulence beneath surface waves. This study extends the algorithm of Tsai and Hung (J. Geophys. Res., 2007), which only simulated the flow. We implement a two-way coupled Eulerian-Lagrangian approach to model microbubbles. This framework tracks microbubbles using the Lagrangian description, influenced by the flow. Concurrently, the flow is solved in the Eulerian frame, accounting for the bubbles' backaction via point-force approximation. The component modeling the motion of the microbubbles is validated by observing the terminal velocity of free-rising bubbles and the convergence of bubble trajectories as the bubbles rise in progressive waves. The impact of bubble forcing is verified through approximate solutions. With the model validated, we conduct simulations to examine the effects of microbubbles on the flow and vice versa. Microbubbles are released into waves to analyze how the waves affect the mean rising velocity of the bubbles. Additionally, simulations of microbubbles in wind-driven turbulence demonstrate the potential for studying interactions between microbubbles and turbulence beneath wind waves. |
Monday, November 25, 2024 2:16PM - 2:29PM |
R21.00003: Neural operator learning for multiscale bubble growth dynamics with correlated fluctuations Minglei Lu, Chensen Lin, Martin R Maxey, George Em Karniadakis, Zhen Li The intricate process of bubble growth dynamics involves a broad spectrum of physical phenomena from microscale mechanics of bubble formation to macroscale interplay between bubbles and surrounding thermo-hydrodynamics. Traditional bubble dynamics models including atomistic approaches and continuum-based methods segment the bubble dynamics into distinct scale-specific models. To bridge the gap between microscale stochastic models and continuum-based models for bubble dynamics, we develop a composite neural operator model to unify the analysis of nonlinear bubble dynamics across microscale and macroscale regimes by integrating a multiphase dissipative particle dynamics (mDPD) model with a continuum-based Rayleigh-Plesset (RP) model through a novel neural network architecture, consisting of an operator network for learning mean-field behavior of bubble growth subject to pressure variations and a long short-term memory network for learning statistical features of correlated fluctuations in microscale dynamics. Training and testing data are generated by conducting mDPD and RP simulations for nonlinear bubble dynamics with initial bubble radii ranging from 0.1 to 1.5 micrometers. Results show that the trained composite neural operator model can accurately predict bubble dynamics across scales, with a 99% accuracy for the time evolution of the bubble radius under varying external pressure while containing correct size-dependent stochastic fluctuations in microscale bubble dynamics. |
Monday, November 25, 2024 2:29PM - 2:42PM |
R21.00004: Bubble-in-Bubble envelope in liquid environments: A new fluidic configuration Balla Mounika Fluidic interactions in two-phase flow refers to the interaction of two phases of fluid (gas, liquid and two immiscible liquids) within a flow system resulting in an exchange of mass, momentum and energy between them which is bound to influence the flow dynamics. Typical two-phase systems involve a bubble and a drop. In this context, three phenomena occur at the interface separating the phases, namely coalescence, spreading and encapsulation. Coalescence is the merging of two single bubbles/drops resulting in the formation of a larger bubble/drop. Spreading is the increase in the surface contact area by spreading of a bubble/drop on a fluid surface. Encapsulation occurs when one phase is entirely surrounded by the other phase resulting in the formation of a distinct boundary. Recently, studies on the new combinations of fluids namely hollow droplet and drop encapsulated in a bubble reported that these fascinated phenomena do occur and require a precise framework in understanding the dynamics. When one bubble of lower surface tension spreads onto the other bubble and entirely covers it, this phenomenon is known as bubble-in-bubble envelope. This possible configuration can be resulted when the surrounding liquid is of self-rewetting in nature and it adds another complexity to the system due to its non-monotonic dependence of surface tension with temperature. This spreading and wetting characteristics helps to understand the controlled bubble interactions, the mechanisms governing the bubble-in-bubble envelopment in a surrounding liquid, thereby analyzing its potential applications in various fields of science. This nature of fluid finds its applications in improving heat transfer rates, thermal energy storage devices using phase change materials, microfluidics and enhanced oil recovery. |
Monday, November 25, 2024 2:42PM - 2:55PM |
R21.00005: Validation of well-posed Euler-Euler models for gas-liquid flows in bubble columns Manjil Ray, Saria Hannan, Martin Obligado, Rodney O. Fox, Alberto Passalacqua Bubble columns are widely used equipment in the chemical and biomanufacturing industries, ensuring the effectiveness of the property transfer by incorporating Computational Fluid Dynamics (CFD) simulations which allows a remarkable level of insight into the details of the flow. However, the accuracy of CFD models hinges on the selection of appropriate model closures, in addition to the adoption of an appropriate spatial discretization of the column geometry. In this work, we present a well-posed formulation of the Euler-Euler two-fluid model, which we use to perform a grid convergence study to provide criteria on the required spatial resolution to achieve a grid-converged numerical solution. We then leverage such a two-fluid model to simulate a pilot-scale bubble column, for which detailed experimental data are available in the literature, which are characterized by narrow bubble size distribution, to predict the bubble volume fraction and the probability distribution (PDF) of the gas velocity. |
Monday, November 25, 2024 2:55PM - 3:08PM |
R21.00006: One-way and two-way coupled simulations of cavitation inception in turbulent shear flows with polydisperse bubbles Hyeoksu Lee, Tim Colonius Natural nuclei in oceans and cavitation tunnels exhibit a broad size distribution, with radii ranging from 10 to 200 μm. The behavior of polydisperse bubbles during cavitation inception in turbulent shear flows is numerically investigated using a fully compressible flow solver. An ensemble phase-averaged multiphase flow model (Zhang & Prosperetti, 1994), along with the Keller-Miksis equation (Keller & Miksis, 1980), is employed to simulate the evolution of a turbulent mixing layer seeded with polydisperse bubbles. A preliminary one-way coupled simulation for Re = 50 (based on shear layer thickness) and Cavitation number, Ca = 1, indicates a preferential expansion of bubbles with equilibrium radii between 100 and 400 μm. Smaller and larger bubbles exhibit suppressed growth, primarily due to surface tension and inertial effects. Additionally, comparisons between one-way and two-way coupled simulations provide deeper insights into the influence of bubble dynamics on the underlying turbulent shear flows. |
Monday, November 25, 2024 3:08PM - 3:21PM |
R21.00007: Towards a hybrid model for cavitation inception Akhil Nekkanti, Tim Colonius Cavitating flows consist of a wide range of resolvable scales as well as micro-scale bubbles that are unresolvable. These micro bubbles serve as cavitation nuclei, and thus play an important role in the resulting dynamics. In this work, a hybrid model is developed that is based on an interface capturing scheme that includes phase change for the resolvable scales, and a stochastic sub-grid bubbles model. In this work, we focus on inter-scale transfer from the sub-grid to resolved scale as this is relevant to cavitation inception. To this end, we recast the gas phase into both resolvable and sub-grid scales, and their respective equations are coupled using source terms. Following Denefle et al. (2015, Comput. Fluids), we propose a source term that depends on the volume fraction of the sub-grid scale and is activated when this volume fraction exceeds a threshold. The hybrid model is implemented in our in-house multi-component flow code, using a five-equation multiphase model. As a proof of concept, the hybrid model is tested by simulating acoustic pulses impinging on an initially sub-grid bubble cluster and comparing the results with fully resolved simulations of the same problem. |
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