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

被引:13
作者
Vervecken, Lieven [1 ,2 ]
Camps, Johan [1 ]
Meyers, Johan [2 ]
机构
[1] Belgian Nucl Res Ctr, SCK CEN, BE-2400 Mol, Belgium
[2] Katholieke Univ Leuven, Dept Mech Engn, BE-3000 Louvain, Belgium
关键词
Dispersion; Atmospheric boundary layer; Wind fluctuations; Project Prairie Grass; PRAIRIE GRASS; POLLUTANT DISPERSION; MODEL; CFD;
D O I
10.1016/j.atmosenv.2013.03.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
When using the mean wind direction in Reynolds-averaged Navier-Stokes (RAMS) 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. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:142 / 150
页数:9
相关论文
共 34 条
[11]   FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations [J].
Hanna, SR ;
Hansen, OR ;
Dharmavaram, S .
ATMOSPHERIC ENVIRONMENT, 2004, 38 (28) :4675-4687
[12]   Detailed simulations of atmospheric flow and dispersion in downtown Manhattan: An application of five computational fluid dynamics models [J].
Hanna, Steven R. ;
Brown, Michael J. ;
Camell, Fernando E. ;
Chan, Stevens T. ;
Coirier, William J. ;
Hansen, Olav R. ;
Huber, Alan H. ;
Kim, Sura ;
Reynolds, R. Michael .
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2006, 87 (12) :1713-+
[13]   On the use of the k-ε model in commercial CFD software to model the neutral atmospheric boundary layer [J].
Hargreaves, D. M. ;
Wright, N. G. .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2007, 95 (05) :355-369
[14]   UCD 2001: an improved model to simulate pollutant dispersion from roadways [J].
Held, T ;
Chang, DPY ;
Niemeier, DA .
ATMOSPHERIC ENVIRONMENT, 2003, 37 (38) :5325-5336
[15]  
Huber A., 2004, P 13 JOINT C APPL AI
[16]   Comparative Study of Gaussian Dispersion Formulas within the Polyphemus Platform: Evaluation with Prairie Grass and Kincaid Experiments [J].
Korsakissok, Irene ;
Mallet, Vivien .
JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2009, 48 (12) :2459-2473
[17]   Verification of CFD pollution dispersion modelling based on experimental data [J].
Labovsky, J. ;
Jelemensky, L'. .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2011, 24 (02) :166-177
[18]  
Laumbach RJ, 2010, AM FAM PHYSICIAN, V81, P175
[19]   Selected results of a model validation exercise [J].
Piringer, M. ;
Baumann-Stanzer, K. .
ADVANCES IN SCIENCE AND RESEARCH, 2009, 3 :13-16
[20]  
Pope S.B., 2000, Turbulent flows, DOI DOI 10.1017/CBO9780511840531