Bulletin of the American Physical Society
75th Annual Meeting of the Division of Fluid Dynamics
Volume 67, Number 19
Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.
Session T36: Particle-Laden Flows: Clustering and Flow Instabilities |
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Chair: Yuan-Nan Young, New Jersey Inst of Tech Room: 244 |
Monday, November 21, 2022 4:10PM - 4:23PM Author not Attending |
T36.00001: Rayleigh-Taylor and Double-Diffusive Instabilities from Sediment Settling in a Two-Layer Stably-Stratified Hele-Shaw Cell Patrick H Bunton, Eckart Meiburg, David Olsen, Gavin Thomas, Daniel Stump Double Diffusive (DD) and Rayleigh Taylor (RT) Instabilities play critical roles in numerous natural and technological phenomena where they can significantly increase transport rates over Stokes settling. Research over the past decade has demonstrated how sediment settling can initiate these and other fluid instabilities in otherwise initially stable stratifications. Herein, DD and RT instabilities were investigated in a Hele-Shaw cell containing an initially stable stratification of particle-laden fresh water over aqueous dextrose. Particle sizes were chosen such that settling rates were slower than, comparable to, or faster than diffusion rates of dextrose based on the premise that these regimes might prove to be dominated by DD, RT, or contain both simultaneously. Particles used included silicon dioxide nanoparticles with sizes 500 nm, 700 nm, and 1000 nm, soda-lime glass microparticles of nominal sizes 3- 6 microns, and 8 – 12 microns, and nominally 2-micron Cerium Oxide microparticles. Some ability to predict fingering is demonstrated based on a product of a Rayleigh number and a ratio of a particle settling time to a dextrose diffusing time. |
Monday, November 21, 2022 4:23PM - 4:36PM |
T36.00002: Collision, coalescence, and breakup of snowflakes in homogeneous and isotropic turbulence Zhicheng Jiang, James T Warner, Zhongwang Dou Snowflakes, carried by a strong wind, may collide, coalesce, and/or break up in the air. This process will likely result in a new distribution of snowflake size, a critical piece of information when estimating icing hazards in any field instrument or air vehicle, e.g., wind turbine, aircraft wing. To gain an in-depth understanding of how strong wind may impact such snowflake dynamics, we take the first step to experimentally quantify the collision, coalescence, and breakup of snowflakes in a homogeneous and isotropic (HI) turbulent flow condition. An in-house designed, open-wall turbulence chamber was implemented to generate HI turbulence. It is a one-meter diameter, truncated hexahedron shape, with eight fans at each corner pushing airflow towards the center region of the chamber. We characterize turbulence properties and track the trajectory of each snowflake using high-speed particle imaging/tracking velocimetry at different Taylerscale Reynolds numbers. Artificial snowflakes are used to test the feasibility of using this apparatus in studying snowflake dynamics in HI turbulence. |
Monday, November 21, 2022 4:36PM - 4:49PM |
T36.00003: Particle Clustering in Free-Surface Turbulence Yaxing Li, Roumaissa Hassaini, Kelken Chang, Henri S Salmon, Claudio Mucignat, Filippo Coletti The transport of floaters on the surface of turbulent waters has been the object of growing interest, due to its relevance to the global challenge of micro-plastics pollution. Here we investigate the behaviour of densely concentrated particles in free-surface turbulence. Experiments are carried out over the fully-developed turbulent region behind a square mesh grid in an open channel facility. This has a 1-m wide, 6-m long test section, and the flow regime produces negligibly small surface waves. Floating particles are illuminated by pulsed LEDs and tracked by two high-speed cameras. We utilised 2-mm, slightly buoyant spheres that behave as surface flow tracers in the dilute limit. Initially, these particles are dispersed homogeneously, but cluster over the compressible free surface. As their concentration is increased up to covering ~20% of the area, the inter-particle interactions profoundly alter the transport: the particles aggregate and stick to each other, forming large clusters. Varying particle concentration and Reynolds number, we investigate how the underlying turbulence determines the cluster topology, characterized by Voronoi tessellation. Furthermore, we analyse the Lagrangian dispersion and relative velocities in comparison to the dilute case. |
Monday, November 21, 2022 4:49PM - 5:02PM |
T36.00004: Coherence of inertial particle clusters in the core region of a turbulent channel flow Tuhin Bandopadhyay, Laura Villafane The morphology and dynamics of clusters of small inertial particles dispersed in a fully developed turbulent flow are investigated for different Reynolds numbers and particle volume fractions. Experiments are performed in a new vertical channel flow facility for Reynolds numbers based on the channel width between 104 and 2.5*104. Glass-microspheres of 54 microns average diameter yield Stokes numbers based on the Kolmogorov timescale of 13 and 48 for the lowest and highest Reynolds numbers, respectively. Planar illumination high-speed imaging is performed on the central plane, with a streamwise field-of-view length of about 5 times the channel width. Clusters are identified in each snapshot using an in-house density-based clustering algorithm specifically designed to reduce the computational cost of cluster identification while facilitating their individual tracking. Shape tracking through structural skeletonization allows studying the evolution of each cluster along its lifetime. The data-analysis tools were first developed and tested on 3D data from point-particle DNS simulations. The same database is used to evaluate the relationship between 2D and 3D statistics. Different cluster formation and disintegration processes and their lifetimes are studied statistically and correlated to their morphological features. |
Monday, November 21, 2022 5:02PM - 5:15PM Author not Attending |
T36.00005: Physical coupling between inertial clustering and relative velocity in a polydisperse droplet field with background turbulence Shyam Kumar Mutil House, Manikandan Mathur, Satyanarayanan R Chakravarthy Droplet collisions in a turbulent air flow are understood primarily via two different enhancement factors, namely clustering and relative velocity. While these factors are believed to be physically coupled, they have mostly been studied independently, partly owing to challenges in fully accounting for droplet-turbulence interactions in theoretical models and numerical simulations. In this novel experimental study, we measure clustering and relative velocity in a controlled air turbulence facility, to directly demonstrate the physical coupling between these enhancement factors in a polydisperse droplet field. In the non-clustering regime, caustic droplet pairs, comprised of disparate droplet sizes, contribute primarily to an increase in average relative velocity (and hence collisions) with an increase in turbulent intensity. In the clustering regime, while caustic droplet pairs still occur, clustering and relative velocity share an inverse relation, thus contributing to a decrease in droplet collision rates with an increase in turbulent intensity. Turbulent modulation, and the resultant energy redistribution, are found to be the key physical mechanisms, and should be a consideration in droplet collision rate estimates in applications like warm rain initiation. |
Monday, November 21, 2022 5:15PM - 5:28PM |
T36.00006: Clustering characteristics of sub-Kolmogorov size droplets subjected to moderately turbulent co-flows Ali Rostami, Sunny Ri Li, Sina Kheirkhah Interaction of sub-Kolmogorov size droplets with turbulent co-flows is investigated using Interferometric Laser Imaging for Droplet Sizing and Mie scattering techniques along with hotwire anemometry. A swirl atomizer was positioned at the center of a 48 mm diameter nozzle, which provided a turbulent co-flow. The turbulent flow characteristics were varied using perforated plate(s). For test conditions that the co-flow was provided, the mean bulk flow velocity was about 7 m/s. The results show that increasing the background root-mean-square (RMS) velocity fluctuations from 0 to about 1.5 m/s increases the most probable droplet diameter, cluster, and void sizes from about 33 to 43 μm, 660 to 770 μm, and 3.3 to 4.1 mm, respectively. The most probable cluster and void sizes are close to the Taylor and integral length scales, respectively. It was investigated that increasing the RMS velocity fluctuations increases uniformity in the spatial distribution of the droplets. It is inferred that, although increasing the RMS velocity fluctuations increases the most probable droplets size (which may not be desirable for many engineering applications), the enhanced uniformity in the distribution of the droplets is desirable. |
Monday, November 21, 2022 5:28PM - 5:41PM |
T36.00007: Clustering characteristics of heated bidispersed particles Ahmed Saieed, Jean-Pierre Hickey Inertial particles tend to cluster in a turbulent flow due to the centrifugal force exerted by the vortices. While the efficiency of numerous state-of-the-art applications of heated particle-laden flows, such as metal powder combustion in satellite engines and solar collectors, heavy rely on the homogeneous dispersion of particles. Conventionally, the ratio of particle response time to the turbulent timescale (known as Stokes number, St) is used to characterize particle distribution. Here, St = 1 corresponds to maximum particle clustering. Intuitively, it seems reasonable to control particle St for uniform dispersion. Yet, practical applications not only contain a range of particle sizes which correspond to different turbulent timescales, but in a turbulent flow St varies with the evolution of timescales. Furthermore, it was recently reported that heating of bidispersed particles create clouds of high viscosity gas in the flow field. These clouds capture and retain smaller particles, and therefore depict higher clustering even at St<1. However, this study was one-way coupled in momentum, whereas particles can modulate turbulence based on their volume fraction/size. Thus, this research is extended by conducting direct numerical simulations with two-way momentum coupling. Here, a significantly higher decay rate of turbulent kinetic energy is observed which reduced the clustering of smaller particles at later timesteps. On the other hand, the clustering of larger particles was unaffected by the change in momentum coupling. |
Monday, November 21, 2022 5:41PM - 5:54PM |
T36.00008: Self-organization of spherical particles submerged in an oscillating flow Timo van Overveld, Wim-Paul Breugem, Herman Clercx, Matias Duran Matute When a group of spherical particles submerged in a viscous fluid is subjected to oscillations, the particles align themselves in chains perpendicular to the oscillation direction. The driving mechanism of the chain-forming phenomenon is a non-zero residual flow, or steady streaming flow, that remains after averaging over a full oscillation period. We performed experiments using an oscillating box filled with water and stainless steel ball bearings. Our experiments show that the equilibrium particle configurations range from one-particle-thick chains to layered bands, depending on the flow conditions and particle number density. The formation, evolution, and stability of the patterns are characterized by techniques commonly used for colloidal assemblies. |
Monday, November 21, 2022 5:54PM - 6:07PM |
T36.00009: Statistical analysis of DNS data on clustering in homogeneous particle-laden turbulent flow for stochastic model development Jiazhong Zhou, Rohini U Vaideswaran, Max P Herzog, John Wakefield, P.K. Yeung, Jesse Capecelatro, Shankar Subramaniam Recent developments in stochastic Euler-Lagrange (EL) models for particle velocity and acceleration are successful in capturing particle dispersion and particle velocity variance\footnote{Lattanzi, A., Tavanashad, V., Subramaniam, S., Capecelatro, J., 2020. Stochastic models for capturing dispersion in particle-laden flows. Jounral of Fluid Mechanics 903.}. However, existing models do not take account of particle clustering that can significantly affect the fluid particle system. Consequently, advanced stochastic models for particle clustering that capture spatial correlation of particles need to be developed. Murphy\footnote{Murphy, E., 2017. Analysis and modeling of structure formation in granular and fluid-solid flows, Ph.D. thesis, Iowa State University.} established a theoretical framework to represent particle clustering and preferential concentration in terms of two-particle statistics. The key statistical quantities that need to be accurately modeled in this framework include the mean relative velocity $\langle w_{i}|r \rangle$ and the covariance of the relative velocity $\langle w_i w_j |r \rangle$ derived from particle pairs conditional on the pair separation $r$. Accurate prediction of the covariance requires modeling the correlation of particle-pair relative acceleration with particle-pair relative velocity that appears as a source or sink term in the evolution equation for the velocity-acceleration covariance. Point-particle direct numerical simulation (PP-DNS) data are analyzed to extract these statistics that can be used to develop advanced stochastic closure models for preferential concentration and particle clustering. |
Monday, November 21, 2022 6:07PM - 6:20PM |
T36.00010: Aggregation of microplastic and biogenic particles in a homogeneous and isotropic turbulence Mona Rahmani, Akanksha Gupta, Lluis Jofre We investigate the aggregation of microplastic and biogenic particles in a homogeneous and isotropic turbulence using direct numerical simulations and Lagrangian tracking of point particles. The range of particle properties (size and density) and mixture characteristics (turbulence intensity and particle number densities) analyzed correspond to scenarios relevant to the transport of microplastics in marine systems. We examine the spatio-temporal distribution of the disperse and continuous phases, the mechanisms and rates of particle collisions, and the composition of the resulting aggregates. The main findings are that (i) microplastics can be found in a large fraction of aggregates in scenarios with different average diameter of the mixture and number density ratios between microplastic and biogenic particles, (ii) microplastic-containing aggregates will sink to the deeper ocean layers particularly in situations where the biogenic particles are larger than or are of similar size compared to microplastics. By examining the collision mechanisms, a model for the collision rate that reproduces the computational results is proposed. |
Monday, November 21, 2022 6:20PM - 6:33PM |
T36.00011: Scale-dependent divergence of inertial particle velocity in isotropic turbulence Keigo Matsuda, Thibault OUJIA, Kai Schneider, Jacob R West, Suhas S Jain, Kazuki Maeda Clustering of inertial particles in high Reynolds number turbulence is an important fundamental process, e.g., for raindrop formation in atmospheric clouds. The particle concentration has multiscale clusters and voids owing to the multiscale nature of turbulence. Recently, Matsuda et al. (Phys. Rev. Fluids, 2021) showed the cluster/void pronounced structures of inertial particle clustering depend on the scale and the Stokes number. Hence, to get insight into the multiscale dynamics of particle clustering, we analyze the scale dependence of cluster formation/destruction, which is quantified by negative/positive divergence values of particle velocity, respectively. |
Monday, November 21, 2022 6:33PM - 6:46PM |
T36.00012: Clustering of heavy inertial particles in an elliptical vortex Anu Viswanathan Sreekumari Nath, Anubhab Roy In open vortical flows, suspended heavy inertial particles are generally centrifuged out from the regions of high vorticity, making the vortex centre unstable fixed points or sources. The Kirchhoff vortex, an isolated elliptical patch of uniform vorticity that rotates with a self-induced constant angular velocity, is an example of an open vortical flow that contains sinks for heavy inertial particles. In the co-rotating reference frame with the elliptical patch, heavy inertial particles find two sinks and three sources in the flow domain. The locations of sources and sinks depend on the particle inertia/Stokes number (St); their stability characteristics change when the St exceeds a critical value. However, the dynamics of inertial particles can not become chaotic in the Kirchhoff vortex, which is proven by showing time-independent correction to Hamiltonian in the limit of St << 1. We next analyze the transport of heavy inertial particles in a Kida vortex, an elliptical vortex patch in a background shear flow, where evidence of chaotic transport is probed as a function of St and background shear rate. AVSN thanks the Prime Minister's Research Fellows (PMRF) scheme, Ministry of Education, Government of India. The authors also acknowledge the support of the Complex Systems and Dynamics Group at Indian Institute of Technology Madras. |
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