DOI: 10.1016/j.atmosenv.2017.04.019
Scopus记录号: 2-s2.0-85019056652
论文题名: Quantifying inflow uncertainties in RANS simulations of urban pollutant dispersion
作者: García-Sánchez C ; , Van Tendeloo G ; , Gorlé C
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 161 起始页码: 263
结束页码: 273
语种: 英语
英文关键词: Dispersion
; Joint Urban 2003
; Reynolds-Averaged Navier-Stokes
; Uncertainty quantification
; Urban flow
Scopus关键词: Air pollution
; Chaotic systems
; Dispersion (waves)
; Kinetic energy
; Kinetics
; Navier Stokes equations
; Pollution
; Population statistics
; Probability distributions
; Sensitivity analysis
; Turbulence
; Inflow boundary conditions
; Joint Urban 2003
; Reynolds - Averaged Navier-Stokes
; Reynolds-averaged navier-stokes simulations
; Turbulence kinetic energy
; Uncertainty quantifications
; Urban flow
; Variance-based sensitivity analysis
; Uncertainty analysis
; boundary condition
; dispersion
; energy dissipation
; kinetic energy
; Navier-Stokes equations
; pollutant property
; Reynolds number
; sensitivity analysis
; tracer
; turbulence
; uncertainty analysis
; urban pollution
; algorithm
; Article
; atmospheric dispersion
; calculation
; comparative study
; kinetics
; methodology
; Oklahoma
; priority journal
; reynolds averaged navier stokes
; sensitivity analysis
; simulation
; urban area
; Oklahoma [United States]
; United States
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Numerical simulations of flow and pollutant dispersion in urban environments have the potential to support design and policy decisions that could reduce the population's exposure to air pollution. Reynolds-averaged Navier-Stokes simulations are a common modeling technique for urban flow and dispersion, but several sources of uncertainty in the simulations can affect the accuracy of the results. The present study proposes a method to quantify the uncertainty related to variability in the inflow boundary conditions. The method is applied to predict flow and pollutant dispersion in downtown Oklahoma City and the results are compared to field measurements available from the Joint Urban 2003 measurement campaign. Three uncertain parameters that define the inflow profiles for velocity, turbulence kinetic energy and turbulence dissipation are defined: the velocity magnitude and direction, and the terrain roughness length. The uncertain parameter space is defined based on the available measurement data, and a non-intrusive propagation approach that employs 729 simulations is used to quantify the uncertainty in the simulation output. A variance based sensitivity analysis is performed to identify the most influential uncertain parameters, and it is shown that the predicted tracer concentrations are influenced by all three uncertain variables. Subsequently, we specify different probability distributions for the uncertain inflow variables based on the available measurement data and calculate the corresponding means and 95% confidence intervals for comparison with the field measurements at 35 locations in downtown Oklahoma City. © 2017 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82731
Appears in Collections: 气候变化事实与影响
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作者单位: EMAT, Department of Physics, University of Antwerp, Groenenborgerlaan 171, Antwerp, Belgium; Von Karman Institute for Fluid Dynamics, Waterloosesteenweg 72, Sint-Genesius-Rode, Belgium; Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA, United States
Recommended Citation:
García-Sánchez C,, Van Tendeloo G,, Gorlé C. Quantifying inflow uncertainties in RANS simulations of urban pollutant dispersion[J]. Atmospheric Environment,2017-01-01,161