QES-Plume v1.0: a Lagrangian dispersion model
<p>Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predic...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-10-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/5729/2023/gmd-16-5729-2023.pdf |
| _version_ | 1797658783689736192 |
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| author | F. Margairaz B. Singh J. A. Gibbs L. Atwood E. R. Pardyjak R. Stoll |
| author_facet | F. Margairaz B. Singh J. A. Gibbs L. Atwood E. R. Pardyjak R. Stoll |
| author_sort | F. Margairaz |
| collection | DOAJ |
| description | <p>Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below <span class="inline-formula">6</span> % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with <span class="inline-formula">99</span> % of matched zeros and <span class="inline-formula">59</span> % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.</p> |
| first_indexed | 2024-03-11T18:05:16Z |
| format | Article |
| id | doaj.art-8bc795c883ac49a38af805d39db6e6a5 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-03-11T18:05:16Z |
| publishDate | 2023-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-8bc795c883ac49a38af805d39db6e6a52023-10-17T08:45:06ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032023-10-01165729575410.5194/gmd-16-5729-2023QES-Plume v1.0: a Lagrangian dispersion modelF. Margairaz0B. Singh1J. A. Gibbs2L. Atwood3E. R. Pardyjak4R. Stoll5Department of Mechanical Engineering, University of Utah, 1495 E 100 S, Salt Lake City, UT, USAPacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA, USANOAA/OAR National Severe Storms Laboratory, Norman, OK, USADepartment of Mechanical Engineering, University of Utah, 1495 E 100 S, Salt Lake City, UT, USADepartment of Mechanical Engineering, University of Utah, 1495 E 100 S, Salt Lake City, UT, USADepartment of Mechanical Engineering, University of Utah, 1495 E 100 S, Salt Lake City, UT, USA<p>Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below <span class="inline-formula">6</span> % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with <span class="inline-formula">99</span> % of matched zeros and <span class="inline-formula">59</span> % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.</p>https://gmd.copernicus.org/articles/16/5729/2023/gmd-16-5729-2023.pdf |
| spellingShingle | F. Margairaz B. Singh J. A. Gibbs L. Atwood E. R. Pardyjak R. Stoll QES-Plume v1.0: a Lagrangian dispersion model Geoscientific Model Development |
| title | QES-Plume v1.0: a Lagrangian dispersion model |
| title_full | QES-Plume v1.0: a Lagrangian dispersion model |
| title_fullStr | QES-Plume v1.0: a Lagrangian dispersion model |
| title_full_unstemmed | QES-Plume v1.0: a Lagrangian dispersion model |
| title_short | QES-Plume v1.0: a Lagrangian dispersion model |
| title_sort | qes plume v1 0 a lagrangian dispersion model |
| url | https://gmd.copernicus.org/articles/16/5729/2023/gmd-16-5729-2023.pdf |
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