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Clustering of fast gyrotactic particles in low-Reynolds-number flow

Systems of particles in turbulent flows exhibit clustering where particles form patches in certain regions of space. Previous studies have shown that motile particles accumulate inside the vortices and in downwelling regions, while light and heavy non-motile particles accumulate inside and outside t...

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Autores principales: Almerol, Jenny Lynn Ongue, Liponhay, Marissa Pastor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989315/
https://www.ncbi.nlm.nih.gov/pubmed/35390073
http://dx.doi.org/10.1371/journal.pone.0266611
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author Almerol, Jenny Lynn Ongue
Liponhay, Marissa Pastor
author_facet Almerol, Jenny Lynn Ongue
Liponhay, Marissa Pastor
author_sort Almerol, Jenny Lynn Ongue
collection PubMed
description Systems of particles in turbulent flows exhibit clustering where particles form patches in certain regions of space. Previous studies have shown that motile particles accumulate inside the vortices and in downwelling regions, while light and heavy non-motile particles accumulate inside and outside the vortices, respectively. While strong clustering is generated in regions of high vorticity, clustering of motile particles is still observed in fluid flows where vortices are short-lived. In this study, we investigate the clustering of fast swimming particles in a low-Reynolds-number turbulent flow and characterize the probability distributions of particle speed and acceleration and their influence on particle clustering. We simulate gyrotactic swimming particles in a cubic system with homogeneous and isotropic turbulent flow. Here, the swimming velocity explored is relatively faster than what has been explored in other reports. The fluid flow is produced by conducting a direct numerical simulation of the Navier-Stokes equation. In contrast with the previous results, our results show that swimming particles can accumulate outside the vortices, and clustering is dictated by the swimming number and is invariant with the stability number. We have also found that highly clustered particles are sufficiently characterized by their acceleration, where the increase in the acceleration frequency distribution of the most clustered particles suggests a direct influence of acceleration on clustering. Furthermore, the acceleration of the most clustered particles resides in acceleration values where a cross-over in the acceleration PDFs are observed, an indicator that particle acceleration generates clustering. Our findings on motile particles clustering can be applied to understanding the behavior of faster natural or artificial swimmers.
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spelling pubmed-89893152022-04-08 Clustering of fast gyrotactic particles in low-Reynolds-number flow Almerol, Jenny Lynn Ongue Liponhay, Marissa Pastor PLoS One Research Article Systems of particles in turbulent flows exhibit clustering where particles form patches in certain regions of space. Previous studies have shown that motile particles accumulate inside the vortices and in downwelling regions, while light and heavy non-motile particles accumulate inside and outside the vortices, respectively. While strong clustering is generated in regions of high vorticity, clustering of motile particles is still observed in fluid flows where vortices are short-lived. In this study, we investigate the clustering of fast swimming particles in a low-Reynolds-number turbulent flow and characterize the probability distributions of particle speed and acceleration and their influence on particle clustering. We simulate gyrotactic swimming particles in a cubic system with homogeneous and isotropic turbulent flow. Here, the swimming velocity explored is relatively faster than what has been explored in other reports. The fluid flow is produced by conducting a direct numerical simulation of the Navier-Stokes equation. In contrast with the previous results, our results show that swimming particles can accumulate outside the vortices, and clustering is dictated by the swimming number and is invariant with the stability number. We have also found that highly clustered particles are sufficiently characterized by their acceleration, where the increase in the acceleration frequency distribution of the most clustered particles suggests a direct influence of acceleration on clustering. Furthermore, the acceleration of the most clustered particles resides in acceleration values where a cross-over in the acceleration PDFs are observed, an indicator that particle acceleration generates clustering. Our findings on motile particles clustering can be applied to understanding the behavior of faster natural or artificial swimmers. Public Library of Science 2022-04-07 /pmc/articles/PMC8989315/ /pubmed/35390073 http://dx.doi.org/10.1371/journal.pone.0266611 Text en © 2022 Almerol, Liponhay https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Almerol, Jenny Lynn Ongue
Liponhay, Marissa Pastor
Clustering of fast gyrotactic particles in low-Reynolds-number flow
title Clustering of fast gyrotactic particles in low-Reynolds-number flow
title_full Clustering of fast gyrotactic particles in low-Reynolds-number flow
title_fullStr Clustering of fast gyrotactic particles in low-Reynolds-number flow
title_full_unstemmed Clustering of fast gyrotactic particles in low-Reynolds-number flow
title_short Clustering of fast gyrotactic particles in low-Reynolds-number flow
title_sort clustering of fast gyrotactic particles in low-reynolds-number flow
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989315/
https://www.ncbi.nlm.nih.gov/pubmed/35390073
http://dx.doi.org/10.1371/journal.pone.0266611
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