Bulletin of the American Physical Society
72nd Annual Meeting of the APS Division of Fluid Dynamics
Volume 64, Number 13
Saturday–Tuesday, November 23–26, 2019; Seattle, Washington
Session Q28: Particle Laden Flows: Clustering |
Hide Abstracts |
Chair: Sourabh V. Apte, Oregon State University Room: 610 |
Tuesday, November 26, 2019 7:45AM - 7:58AM |
Q28.00001: Pore-Scale Investigation of Clustering of Inertial Particles in Turbulent Flow Through a Porous Medium Sourabh Apte, Thibault Oujia, Xiaoliang He, Benjamin Kadoch, Keigo Matsuda, Kai Schneider Transport and deposition of fine inertial particles in porous media is of interest in several applications such as spillage of contaminants in stream or river beds, water filtration systems, enhanced oil recovery, among others. Specifically, sweep and ejection patterns and turbulence within the porous bed in the sediment-water interface region of stream or rivers may influence the trapping and deposition of fine inertial particles in the bed. In the present work, we use direct numerical simulation to investigate effect of turbulent flow in the confined geometry of a face centered cubic porous unit cell on the transport of fine particles at different Stokes numbers ($St_p = 1, 0.1, 0$) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and collision of particles with pore walls is modeled as perfectly inelastic, damping the particle velocity. The pattern of clustering is investigated using multiscale wavelet analysis and area of Voronoi tessellation cells. The results are compared with preferential concentration in forced isotropic turbulence to investigate the effect of geometric confinement on particle clustering. [Preview Abstract] |
Tuesday, November 26, 2019 7:58AM - 8:11AM |
Q28.00002: Scale-dependent structures of particle clusters in cluster-induced turbulence Jeonglae Kim, Houssem Kasbaoui Recent studies have shown that settling inertial particles dispersed at a sufficiently high mass loading spontaneously cluster and generate turbulent motions in the carrier phase, known as cluster-induced turbulence (CIT). Variance of local volume fraction enhances the fluid-phase production in the Reynolds-averaged context, implying that spatially-local dynamics involving particle--particle and particle--fluid interactions contribute to CIT. This study employs DNS and wavelet multiresolution analysis (WMRA) to characterize and understand the structures of particle clusters at various scales in CIT driven by gravity. Euler--Lagrange simulations of CIT are conducted in two-way coupling at the mass loading 0.5 and particle Reynolds number $\mathrm{Re}_p=\tau_pgd_p/\nu=0.3$. The initially uniformly-distributed particles evolve into a statistically-stationary state of sustained clustering. WMRA is used to extract the clusters of inertial particles in a way similar to the coherent vorticity extraction technique. Following Bassenne et al. (Phys. Rev. Fluids 2017), coherent and incoherent components of volume fraction are obtained per scale, location and direction. Their correlations with particle and turbulence statistics are examined to study the structural characteristics of CIT. [Preview Abstract] |
Tuesday, November 26, 2019 8:11AM - 8:24AM |
Q28.00003: Divergence and convergence of inertial particles in high Reynolds number turbulence Thibault Oujia, Keigo Matsuda, Kai Schneider We analyze data from 3D direct numerical simulations of particle-laden homogeneous isotropic turbulence at high Reynolds number using Voronoi tessellation of the particle positions, considering different Stokes numbers (St). The divergence of the particle velocity can be quantified by determining the volume change rate of the Voronoi cells. We show theoretically that for random particles in random flow the divergence satisfies a PDF of the ratio $X/Y$, where $X$ and $Y$ follow normal and $\Gamma$ distributions, respectively. For inertial particles we find that the PDF of the divergence deviates from the theoretical prediction. Joint PDFs of the divergence and the Voronoi cell volume illustrate that the divergence is most prominent in cluster regions and less pronounced in void regions. Moreover, the mean value of the divergence becomes negative inside the cluster regions for St <=2, corresponding to convergence of inertial particles, while for large St the mean value turns to positive values as the Voronoi cell volume becomes smaller. Finally, we show that the divergence of the inertial particle velocity exhibits no correlation with the second invariant of the fluid velocity gradient tensor, which has some impact for modeling particle laden turbulence. [Preview Abstract] |
Tuesday, November 26, 2019 8:24AM - 8:37AM |
Q28.00004: Inertial particle distribution in high Reynolds number turbulence: wavelet-based scale-dependent statistics Keigo Matsuda, Kai Schneider, Katsunori Yoshimatsu The nonlinear dynamics of inertial particles in high Reynolds number turbulence, and in particular particle clustering, are important fundamental processes in atmospheric science. Here we analyze particle data from three-dimensional direct numerical simulations of particle-laden homogeneous isotropic turbulence at high Reynolds number, up to $Re_\lambda = 531$ and with up to $10^9$ particles. The influence of Reynolds and Stokes numbers on the multiscale clustering structure is investigated. To calculate scale-dependent statistics we apply orthogonal wavelet decomposition to the particle density fields. The intermittency of the density fields is quantified by computing scale-dependent flatness values. Negative values of the scale-dependent skewness allow to assess the spatial scale of void regions. We also show that the number of particles has some impact on high-order statistics, especially at small scales. [Preview Abstract] |
Tuesday, November 26, 2019 8:37AM - 8:50AM |
Q28.00005: Life and death of inertial particle clusters in homogeneous turbulence Yuanqing Liu, Lian Shen, Remi Zamansky, Filippo Coletti Although clustering is a widely observed phenomenon in particle-laden turbulence, our understanding of the formation, evolution, and destruction of particle clusters is still incomplete. Virtually all existing definitions of a cluster rely on the spatial coherence of the particle concentration field, neglecting its temporal persistence. The latter is in fact essential to the ability of the particles to interact with each other, and to modify the carrier fluid flow. Here we leverage simulations of homogeneous isotropic turbulence laden with small heavy particles, and develop a Lagrangian framework to follow them before, during, and after their time as part of a coherent cluster. We define a criterion to establish whether a cluster survives over successive time steps, and use it to characterize its lifetime. Moreover, we investigate the recurring features of the turbulence associated to the formation and destruction of a cluster. The impact of the lifetime definition on the results is also discussed. [Preview Abstract] |
Tuesday, November 26, 2019 8:50AM - 9:03AM |
Q28.00006: Clustering of gas-solids flows in a vertical duct Aaron M. Lattanzi, Sarah Beetham, Kee Onn Fong, Filippo Colletti, Jesse Capecelatro In this work, numerical simulations of moderately dense gas-solids flows in the fully-developed region of a vertical duct are performed. The simulations are performed within a volume-filtered Eulerian-Lagrangian (EL) framework and compared to novel experimental measurements. The high mass loading considered here leads to significant two-way coupling and the spontaneous generation of densely-packed clusters that fall along the duct walls. Two-phase flow statistics are extracted from the simulations and compared against detailed experimental measurements obtained from high-speed imaging and particle-tracking velocimetry. Additionally, a model for the pseudo-turbulent Reynolds stress (PTRS) was implemented within the EL framework to account for sub-grid particle-induced velocity fluctuations. Simulations with the PTRS closure allow the effect of a pseudo-turbulence model on clustered flows to be rigorously assessed for the first time. [Preview Abstract] |
Tuesday, November 26, 2019 9:03AM - 9:16AM |
Q28.00007: Highly concentrated falling inertial particles in a vertical duct/riser Kee Onn Fong, Filippo Coletti Highly concentrated particle-laden turbulent flows, such as flows found in fluidized beds and falling-particle receivers, form complex and poorly understood interactions owing to the strong feedback of the dispersed phase on the fluid and possible inter-particle collisions. We present experimental observations on the velocity response and topological distribution of highly concentrated, falling inertial particles in a vertical rectangular duct. The working fluid is air laden with size-selected glass particles. The experiment is conducted in two different configurations of free-falling particles, and particles suspended by flowing air, enabling particle volume fractions as high as 3E-2. Two different resolutions are employed - a full-scale view to capture large-scale motions of the particles and cluster formation using particle image velocimetry; and a zoomed-in view to resolve the individual motions of particles using particle tracking velocimetry. The findings are discussed in the context of collective effect of particles, the influence of clusters on the mean statistics, and the partitioning of particle velocities into spatially correlated and random uncorrelated motions. [Preview Abstract] |
Tuesday, November 26, 2019 9:16AM - 9:29AM |
Q28.00008: Reynolds number dependence of heavy particle preferential concentration Xiangjun Wang, Minping Wan The preferential concentration of particles is a classical problem in particle-laden turbulence. The dependence of particle clustering on Reynolds number is still an open question. Here, the Reynolds number dependence of heavy inertial particles in homogeneous isotropic turbulence has been investigated. According to the analysis of Voronoi tessellation, the preferential concentration of small heavy particles is studied with the increase of Taylor Reynolds number from 52 to 139, with the number density of particles fixed. There are two factors that determine the extent of particle clustering. The first one is the strength of vortices in turbulence; the other is the persistent time that characteristic vortices drive particles to preferentially accumulate during one turnover time. Obviously, a larger strength of vortices and a longer persistent time contribute to a more intensive preferential concentration of particles. It is uncovered that the strength of vortices increases as Reynolds number increases, whereas the persistent time decreases with Reynolds number. Consequently, the influence of the latter defeats that of the former in present investigation. Therefore, the degree of preferential concentration decreases with Reynolds number. [Preview Abstract] |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2020 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
1 Research Road, Ridge, NY 11961-2701
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700