Efficient point-based simulation of four-way coupled particles in turbulence at high number density Article Swipe
YOU?
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· 2024
· Open Access
·
· DOI: https://doi.org/10.1103/physreve.110.015301
In many natural and industrial applications, turbulent flows encompass some form of dispersed particles. Although this type of multiphase turbulent flow is omnipresent, its numerical modeling has proven to be a remarkably challenging problem. Models that fully resolve the particle phase are computationally very expensive, strongly limiting the number of particles that can be considered in practice. This warrants the need for efficient reduced order modeling of the complex system of particles in turbulence that can handle high number densities of particles. Here we present an efficient method for point-based simulation of particles in turbulence that are four-way coupled. In contrast with traditional one-way coupled simulations, where only the effect of the fluid phase on the particle phase is modeled, this method additionally captures the back-reaction of the particle phase on the fluid phase, as well as the interactions between particles themselves. We focus on the most challenging case of very light particles or bubbles, which show strong clustering in the high-vorticity regions of the fluid. This strong clustering poses numerical difficulties which are systematically treated in our work. Our method is valid in the limit of small particles with respect to the Kolmogorov scales of the flow and is able to handle very large number densities of particles. This methods paves the way for comprehensive studies of the collective effect of small particles in fluid turbulence for a multitude of applications.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1103/physreve.110.015301
- http://link.aps.org/pdf/10.1103/PhysRevE.110.015301
- OA Status
- bronze
- Cited By
- 2
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394906348
Raw OpenAlex JSON
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https://openalex.org/W4394906348Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1103/physreve.110.015301Digital Object Identifier
- Title
-
Efficient point-based simulation of four-way coupled particles in turbulence at high number densityWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-07-01Full publication date if available
- Authors
-
Xander M. de Wit, Rudie Kunnen, H. J. H. Clercx, Federico ToschiList of authors in order
- Landing page
-
https://doi.org/10.1103/physreve.110.015301Publisher landing page
- PDF URL
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https://link.aps.org/pdf/10.1103/PhysRevE.110.015301Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://link.aps.org/pdf/10.1103/PhysRevE.110.015301Direct OA link when available
- Concepts
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Turbulence, Point (geometry), Statistical physics, Physics, Computer science, Mechanics, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2Per-year citation counts (last 5 years)
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37Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.densities | 79, 206 |
| abstract_inverted_index.dispersed | 12 |
| abstract_inverted_index.efficient | 62, 86 |
| abstract_inverted_index.encompass | 8 |
| abstract_inverted_index.multitude | 229 |
| abstract_inverted_index.numerical | 24, 170 |
| abstract_inverted_index.particles | 50, 71, 92, 140, 152, 188, 223 |
| abstract_inverted_index.practice. | 56 |
| abstract_inverted_index.turbulent | 6, 19 |
| abstract_inverted_index.Kolmogorov | 193 |
| abstract_inverted_index.clustering | 158, 168 |
| abstract_inverted_index.collective | 219 |
| abstract_inverted_index.considered | 54 |
| abstract_inverted_index.expensive, | 44 |
| abstract_inverted_index.industrial | 4 |
| abstract_inverted_index.multiphase | 18 |
| abstract_inverted_index.particles. | 13, 81, 208 |
| abstract_inverted_index.remarkably | 31 |
| abstract_inverted_index.simulation | 90 |
| abstract_inverted_index.turbulence | 73, 94, 226 |
| abstract_inverted_index.challenging | 32, 147 |
| abstract_inverted_index.point-based | 89 |
| abstract_inverted_index.themselves. | 141 |
| abstract_inverted_index.traditional | 102 |
| abstract_inverted_index.additionally | 122 |
| abstract_inverted_index.difficulties | 171 |
| abstract_inverted_index.interactions | 138 |
| abstract_inverted_index.omnipresent, | 22 |
| abstract_inverted_index.simulations, | 105 |
| abstract_inverted_index.applications, | 5 |
| abstract_inverted_index.applications. | 231 |
| abstract_inverted_index.back-reaction | 125 |
| abstract_inverted_index.comprehensive | 215 |
| abstract_inverted_index.high-vorticity | 161 |
| abstract_inverted_index.systematically | 174 |
| abstract_inverted_index.computationally | 42 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.71103871 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |