Accounting for wind-direction fluctuations in Reynolds-averaged simulation of near-range atmospheric dispersion

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Accounting for wind-direction fluctuations in Reynolds-averaged simulation of near-range atmospheric dispersion. / Vervecken, Lieven; Camps, Johan; Meyers, Johan.

In: Atmospheric Environment, Vol. 72, 01.03.2013, p. 142-150.

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@article{ddc9330872bd4086a3b0ba83917aca01,
title = "Accounting for wind-direction fluctuations in Reynolds-averaged simulation of near-range atmospheric dispersion",
abstract = "When using the mean wind direction in Reynolds-averaged Navier-Stokes (RANS) simulations of atmospheric dispersion, it is well documented that peak concentration levels are often overestimated, and lateral spreading underestimated. A number of studies report that if the variability of wind directions observed in experiments is included in the boundary conditions, peak levels improve, but lateral spreading is overestimated. In the current work, we argue that fluctuations in wind directions observed in experiments are partly accounted for by the modeled turbulence in RANS simulations; and hence, the effective variability that should be used as a boundary condition to the simulations, needs to be lower than experimentally measured. A simple approach is proposed that reduces the variability based on turbulence levels predicted in the RANS turbulence model. We test the approach by performing a series of dispersion simulations of the well-documented Prairie Grass experiments, and demonstrate that simulations improve significantly.",
keywords = "dispersion, atmospheric boundary layer, wind fluctuations, project prairie grass",
author = "Lieven Vervecken and Johan Camps and Johan Meyers",
note = "Score = 10",
year = "2013",
month = "3",
day = "1",
doi = "10.1016/j.atmosenv.2013.03.005",
language = "English",
volume = "72",
pages = "142--150",
journal = "Atmospheric Environment",
issn = "1352-2310",
publisher = "Elsevier",

}

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TY - JOUR

T1 - Accounting for wind-direction fluctuations in Reynolds-averaged simulation of near-range atmospheric dispersion

AU - Vervecken, Lieven

AU - Camps, Johan

AU - Meyers, Johan

N1 - Score = 10

PY - 2013/3/1

Y1 - 2013/3/1

N2 - When using the mean wind direction in Reynolds-averaged Navier-Stokes (RANS) simulations of atmospheric dispersion, it is well documented that peak concentration levels are often overestimated, and lateral spreading underestimated. A number of studies report that if the variability of wind directions observed in experiments is included in the boundary conditions, peak levels improve, but lateral spreading is overestimated. In the current work, we argue that fluctuations in wind directions observed in experiments are partly accounted for by the modeled turbulence in RANS simulations; and hence, the effective variability that should be used as a boundary condition to the simulations, needs to be lower than experimentally measured. A simple approach is proposed that reduces the variability based on turbulence levels predicted in the RANS turbulence model. We test the approach by performing a series of dispersion simulations of the well-documented Prairie Grass experiments, and demonstrate that simulations improve significantly.

AB - When using the mean wind direction in Reynolds-averaged Navier-Stokes (RANS) simulations of atmospheric dispersion, it is well documented that peak concentration levels are often overestimated, and lateral spreading underestimated. A number of studies report that if the variability of wind directions observed in experiments is included in the boundary conditions, peak levels improve, but lateral spreading is overestimated. In the current work, we argue that fluctuations in wind directions observed in experiments are partly accounted for by the modeled turbulence in RANS simulations; and hence, the effective variability that should be used as a boundary condition to the simulations, needs to be lower than experimentally measured. A simple approach is proposed that reduces the variability based on turbulence levels predicted in the RANS turbulence model. We test the approach by performing a series of dispersion simulations of the well-documented Prairie Grass experiments, and demonstrate that simulations improve significantly.

KW - dispersion

KW - atmospheric boundary layer

KW - wind fluctuations

KW - project prairie grass

UR - http://ecm.sckcen.be/OTCS/llisapi.dll/open/ezp_128077

UR - http://knowledgecentre.sckcen.be/so2/bibref/10111

U2 - 10.1016/j.atmosenv.2013.03.005

DO - 10.1016/j.atmosenv.2013.03.005

M3 - Article

VL - 72

SP - 142

EP - 150

JO - Atmospheric Environment

JF - Atmospheric Environment

SN - 1352-2310

ER -

ID: 236461