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Clustering of inertial particles in turbulent flow through a porous unit cell

Published online by Cambridge University Press:  22 February 2022

Sourabh V. Apte Open the ORCID record for Sourabh V. Apte [Opens in a new window] ,
Thibault Oujia Open the ORCID record for Thibault Oujia [Opens in a new window] ,
Keigo Matsuda Open the ORCID record for Keigo Matsuda [Opens in a new window] ,
Benjamin Kadoch Open the ORCID record for Benjamin Kadoch [Opens in a new window] ,
Xiaoliang He Open the ORCID record for Xiaoliang He [Opens in a new window]  and
Kai Schneider Open the ORCID record for Kai Schneider [Opens in a new window]
Sourabh V. Apte*
Affiliation:
School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, OR 97330, USA
Thibault Oujia
Affiliation:
Aix–Marseille Université, I2M–CNRS, Marseille, France
Keigo Matsuda
Affiliation:
Research Institute for Value-Added-Information Generation (VAiG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 236-0001, Japan
Benjamin Kadoch
Affiliation:
Aix–Marseille Université, IUSTI–CNRS, Marseille, France
Xiaoliang He
Affiliation:
Pacific Northwest National Laboratory, Richland, WA 99352, USA
Kai Schneider
Affiliation:
Aix–Marseille Université, I2M–CNRS, Marseille, France
*
†Email address for correspondence: Sourabh.Apte@oregonstate.edu
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Abstract

Direct numerical simulation is used to investigate effects of turbulent flow in the confined geometry of a face-centred cubic porous unit cell on the transport, clustering and deposition of fine particles at different Stokes numbers ($St = 0.01, 0.1, 0.5, 1, 2$) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and the collision of particles with pore walls is modelled as perfectly elastic with specular reflection. Tools for studying inertial particle dynamics and clustering developed for homogeneous flows are adapted to take into account the embedded, curved geometry of the pore walls. The pattern and dynamics of clustering are investigated using the volume change of Voronoi tesselation in time to analyse the divergence and convergence of the particles. Similar to the case of homogeneous, isotropic turbulence, the cluster formation is present at large volumes, while cluster destruction is prominent at small volumes and these effects are amplified with the Stokes number. However, unlike homogeneous, isotropic turbulence, the formation of a large number of very small volumes was observed at all Stokes numbers and attributed to the collision of particles with the pore wall. Multiscale wavelet analysis of the particle number density indicates that the peak of the energy density spectrum, representative of enhanced particle clustering, shifts towards larger scales with an increase in the Stokes number. Scale-dependent skewness and flatness quantify the intermittent void and cluster distribution, with cluster formation observed at small scales for all Stokes numbers, and void regions at large scales for large Stokes numbers.

JFM classification

Multiphase and Particle-laden Flows: Particle/fluid flow Multiphase and Particle-laden Flows: Multiphase flow Turbulent Flows: Turbulence simulation
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 937 , 25 April 2022 , A9
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Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

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