Session Q09: Turbulence: Multiphase Flow (3:55pm - 4:40pm CST)

Subgrid-scale Modeling of Bubble Breakup in Large Eddy Simulations of Breaking Waves

Turbulent breaking waves entrain air cavities that break up and coalesce to form polydisperse clouds of bubbles. We have recently provided theoretical and numerical justification that the dominant mechanism for bubble generation is a fragmentation cascade from large to small sizes sustained by turbulent velocity fluctuations. This behavior should be universal across various turbulent bubbly flows because of the size locality inherent in a cascade. Universality simplifies the development of subgrid-scale (SGS) breakup models in two-phase large eddy simulations (LES). We formulate an SGS model based on a breakup cascade in accordance with the LES paradigm, where large bubbles are resolved through a two-phase Eulerian description, while small bubbles are separately modeled and tracked as Lagrangian point particles. This model requires the generation and breakup of Lagrangian particles from underresolved Eulerian bubbles with suitable distributions for breakup rates and child bubble sizes. Model distributions are inferred from earlier breaking-wave simulations. Candidate breakup models are tested using a Monte Carlo simulation that mimics the breakup of Lagrangian particles, and then implemented in a coarse breaking-wave LES with validation against previous finer simulations.   

An analysis of dispersion models in large eddy simulation of turbulent spray jet at low Stokes numbers

In the context of large eddy simulation (LES) of spray jets, many studies have been conducted on dispersion models to accurately reconstruct the gas velocity at the droplet position, which is needed by the momentum forcing term. A proper dispersion model must hold the particles inside their vapor region, preventing excessive evaporation and unrealistic autoignition events in hot environments. Two main approaches are available in the literature: Langevin-type equation model that suffers from excess of induced momentum for low Stokes number, and approximate deconvolution method (ADM) that performs well mostly in the aforementioned regime. Accordingly, a model that combines a Langevin-type equation and ADM is presented and its performance is examined. This study focuses on the sensitivity to the dispersion model of global quantities, such as mean velocity field and mixture fraction, which is lower than that of local quantities, such as particle distribution and preferential segregation. LES results with different dispersion models are compared to DNS results. The analysis will include averages conditioned on the mixture fraction for enstrophy of particle number, droplet diameter, and mass and energy source terms.   

Phenomenology of chaotic flows of dense stabilised emulsions

Stabilized emulsions display a rich phenomenology and are ubiquitous in food and cosmetic products. Multicomponent fluids emulsions can be made via hydrodynamic stirring of two immiscible fluids; this typically produces droplets of the minority phase dispersed into the majority phase. According to the intensity of the stirring, one can observe a chaotic or a fully developed turbulent flow where the size of the dispersed droplets can be characterized by the classical Kolmogorov-Hinze argument. When the emulsion is stabilized, e.g. by the presence of surfactants, the phenomenological picture can drastically change. Here we employ state-of-the-art numerical simulations to study the influence of disjoining pressure, at different volume fractions and stirring intensities, in order to generalise the fundamental Kolmogorov-Hinze phenomenology to stabilised emulsions.   

Spectral Properties of Bubbly Turbulent Flows

Suspension of deformable bubbles are ubiquitous in nature, their presence can dramatically alter the rheological properties of flows. We present a DNS study to investigate the spectral properties of the buoyancy-driven bubbly flows in the presence of large scale driving that generates turbulence. The non-dimensional Galilei ($50<{\rm Ga}<300$) and Reynolds ($50<{\rm Re}<150$) numbers characterize the flow. Consistent with the experiments, we show that the energy spectrum shows a pseudo-turbulence scaling ($E(k) \sim k^{-3}$) for length scales smaller than the bubble diameter and a Kolmogorov scaling ($E(k) \sim k^{-5/3}$) for scales larger than the bubble diameter. We present a scale-by-scale energy budget analysis to unravel the dominant balances in different regimes.   

Experimental investigation on turbulence modulation in a bubble turbulent flow

Gas-Liquid contact methods are quite ubiquitous in industrial operations. The understanding of transport processes across their interface is crucial in determining the efficiencies of processes and designing chemical engineering equipment. A common gas-liquid contact method is \textbf{bubbling gas into the liquid}. The presence of these \textbf{bubbles can modulate the turbulence }of the system. With the controlled addition of bubbles, the quantitative \textbf{estimate of change in turbulent energy budget for a range of Reynolds number} in wall bounded flows are yet to be addressed. In our current work, we study the bubble induced \textbf{pseudo turbulence generation} in a quiescent liquid and \textbf{effect of bubble on turbulence modulation at low Reynolds number }turbulent flow. The experiments are conducted in a \textbf{square duct}, in which \textbf{secondary flows} play an important role. We have used \textbf{Particle Image Velocimetry (PIV)} for prediction of simultaneous dynamics of the phases. An \textbf{image separation technique }has been employed to separate bubble phase from the seeding particle images and further analyzed to obtain simultaneous velocity and velocity statistics of both phases. We observe that the addition of bubbles, drastically change the mean velocity profile of the liquid phase and influence the energy spectra. We have \textbf{predicted the bubble diameter} \textbf{at different air flow} rate in our range of study along with change in \textbf{turbulent kinetic energy as a function of air flow rate}   

Dynamics of droplets in dense emulsions

Emulsions are fascinating systems displaying an extremely rich and fundamental fluid dynamic phenomenology. From dilute to highly concentrated, emulsions can exhibit a variety of small-scale morphology and statistical properties. In particular, stabilized emulsions with high volume fraction for the dispersed phase (i.e. above 65{\%}), can display much of the rich phenomenology and rheological properties typical of soft-glasses. First, by means of state-of-the-art 3d numerical simulations, based on the multi-component Lattice Boltzmann method, we study the dynamics of the emulsification processes induced by a large-scale chaotic stirring. Second, we present and discuss a number of observables that allows us to statistically characterize the dynamics of the emulsion at the microscopic scale, these quantities include: the probability distribution function of the velocity and acceleration of single droplets, the relative and absolute dispersion of droplets. Outlook on connecting the microscopic dynamics with large-scale rheology will be discussed