Improvements in Turbulent Jet Particle Dispersion Modeling and Its Validation with DNS

Particle dispersion models (PDMs) are essential to capture the influence of unresolved turbulent eddies on particle transport in computational fluid dynamics (CFD) simulations. However, the validation of these models remains challenging, especially when relying on experimental data or CFD simulations that are based on turbulence models. In this work, we use time-averaged data obtained in a direct numerical simulation (DNS) instead of relying on turbulence models to model particle dispersion. In addition, a new particle dispersion model is presented, referred to as the limited particle–eddy interaction time (LPI) model. For a detailed and systematic evaluation of the new LPI model, we compare its performance with that of other commonly used models, such as the mean particle–eddy interaction time (MPI) model implemented in OpenFOAM® and the randomized particle–eddy interaction time (RPI) model from the literature. The MPI model shows good agreement with the DNS for the largest particles tested (Stokes number, St = 0.2) but exhibits erratic and unphysical trajectories for smaller particles (St ≤ 0.05). To mitigate this erratic behavior, we have adjusted the eddy interaction time in the new LPI model.

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Publication Details

Journal
Atmosphere
Published
2025-05-23
DOI
https://doi.org/10.3390/atmos16060637
Citations
1
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
0.80

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article

Improvements in Turbulent Jet Particle Dispersion Modeling and Its Validation with DNS

Claus Wagner, Daniel Schmeling, Florian Webner, Ege Batmaz
1 citations
Atmosphere
Wind and Air Flow Studies
0.80
article

Improvements in Turbulent Jet Particle Dispersion Modeling and Its Validation with DNS

Claus Wagner, Daniel Schmeling, Florian Webner, Ege Batmaz
article en
1 citations

Abstract

Particle dispersion models (PDMs) are essential to capture the influence of unresolved turbulent eddies on particle transport in computational fluid dynamics (CFD) simulations. However, the validation of these models remains challenging, especially when relying on experimental data or CFD simulations that are based on turbulence models. In this work, we use time-averaged data obtained in a direct numerical simulation (DNS) instead of relying on turbulence models to model particle dispersion. In addition, a new particle dispersion model is presented, referred to as the limited particle–eddy interaction time (LPI) model. For a detailed and systematic evaluation of the new LPI model, we compare its performance with that of other commonly used models, such as the mean particle–eddy interaction time (MPI) model implemented in OpenFOAM® and the randomized particle–eddy interaction time (RPI) model from the literature. The MPI model shows good agreement with the DNS for the largest particles tested (Stokes number, St = 0.2) but exhibits erratic and unphysical trajectories for smaller particles (St ≤ 0.05). To mitigate this erratic behavior, we have adjusted the eddy interaction time in the new LPI model.

AtmosphereVol. 16(6)
Technische Universität Ilmenau (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Helmholtz-Gemeinschaft, Deutsches Zentrum für Luft- und Raumfahrt
Openalex Percentile: Top 29%
Wind and Air Flow Studies
0.80
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