A Computational Fluid Dynamics Approach for Urban Area Transport and Dispersion Modeling

Coirier, William J.; Fricker, D.; Furmanczyk, M.; Kim, S.

doi:10.1007/s10652-005-0299-4

Cited by 43 publications

(19 citation statements)

References 32 publications

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“…Three-dimensional RANS CFD simulations are also numerous [36][37][38][39][40], comparing with either full scale or reduced scale experimental data for both complex and simplified urban geometries, covering both flow and concentration fields. Wang and McNamara study [40] is of particular interest, since the authors used among others the Reynolds-stress model (RSM) of the CFX commercial code and found that the RSM model was sensitive to grid density and may lead to convergence difficulties.…”

Section: Previous Studiesmentioning

confidence: 99%

Evaluation of Reynolds stress, k-ε and RNG k-ε turbulence models in street canyon flows using various experimental datasets

2012

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In this study the Reynolds-averaged Navier-Stokes computational fluid dynamics methodology is used, which has proved to be a powerful tool for the simulations of the airflow and pollutant dispersion in the atmospheric environment. The interest is focused on the urban areas and more specifically on the street canyons, several types of which are examined in order to evaluate the performance of various turbulence models, including a Reynolds-stress model and variations of the k-ε model. The results of the two-dimensional simulations are compared with measurements from a diversity of independent street canyon experimental datasets, covering a wide range of aspect ratios, free stream velocities and roughnesses. This way more general and reliable conclusions can be reached about the applicability, accuracy and ease of use of each turbulence model. In this work, the renormalization group k-ε presented better results in most cases examined, while the Reynolds-stress model did not stand up for the expectations and also exhibited convergence problems.

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Section: Previous Studiesmentioning

confidence: 99%

Evaluation of Reynolds stress, k-ε and RNG k-ε turbulence models in street canyon flows using various experimental datasets

2012

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“…There are essentially two different approaches for the numerical modelling of dispersion through an urban area using CFD; namely, the Reynolds-averaged Navier-Stokes (RANS) and largeeddy simulation (LES) approaches. The application of CFD to turbulent dispersion in the urban environment using either RANS or LES includes Liu and Barth (2002), Baik et al (2003), Kim and Baik (2004), Camelli et al (2005), Coirier et al (2005), Hsieh et al (2007), and Milliez and Carissimo (2007). A hybrid approach, which uses a RANS-predicted gridded field of (building-resolving) wind statistics in an urban area as input to a three-dimensional Lagrangian stochastic trajectory model for the prediction of urban dispersion, is described by Wilson (2007).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Model for Concentration Fluctuations in Compact-Source Plumes in an Urban Environment

Yee

Wang²,

Lien

2009

Boundary-Layer Meteorol

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A comprehensive model for the prediction of concentration fluctuations in plumes dispersing in the complex and highly disturbed wind flows in an urban environment is formulated. The mean flow and turbulence fields in the urban area are obtained using a Reynolds-averaged Navier-Stokes (RANS) flow model, while the standard k-turbulence model (k is the turbulence kinetic energy and is the viscous dissipation rate) is used to close the model. The RANS model provides a specification of the velocity statistics of the highly disturbed wind flow in the urban area, required for the solution of the transport equations for the mean concentrationc and concentration variance c 2 (both of which are formulated in the Eulerian framework). A physically-based formulation for the scalar dissipation time scale t d , required for the closure of the transport equation for c 2 , is presented. This formulation relates t d to an inner time scale corresponding to "internal" concentration fluctuation associated with relative dispersion, rather than an outer time scale associated with the entire portion of the fluctuation spectrum. The two lowest-order moments of concentration (c and c 2 ) are used to determine the parameters of a pre-chosen functional form for the concentration probability density function (clipped-gamma distribution). Results of detailed comparisons between a water-channel experiment of flow and dispersion in an idealized obstacle array and the model predictions for mean flow, turbulence kinetic energy, mean concentration, concentration variance, and concentration probability density function are presented.

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“…Dispersion models that use first principle physics are available today thanks to the sustained increase of computational capability. The use of CFD models has been noted for its ability to represent and characterized the flow patterns in complex urban environments [24][25][26]. The accuracy of these models has been tested and proven to be accurate in the past decades for a broad range of engineering applications [6] and for predicting atmospheric dispersion patterns [26][27][28].…”

Section: Computational Fluid Dynamics and Transport And Dispersion Momentioning

confidence: 99%

Generating seamless surfaces for transport and dispersion modeling in GIS

et al. 2011

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A standard use of triangulation in GIS is to model terrain surface using TIN. In many simulation models of physical phenomena, triangulation is often used to depict the entire spatial domain, which may include buildings, landmarks and other surface objects in addition to the terrain surface. Creating a seamless surface of complex building structures together with the terrain is challenging and existing approaches are laborious, time-consuming and error-prone. We propose an efficient and robust procedure using computational geometry techniques to derive triangulated building surfaces from 2D polygon data with a height attribute. We also propose a new method to merge the resultant building surfaces with the triangulated terrain surface to produce a seamless surface for the entire study area. Using Oklahoma City data, we demonstrate the proposed method. The resultant surface is used as the input data for a simulated transport and dispersion event in Oklahoma City. The proposed method can produce the seamless surface data to be used for various types of physical models in a fraction of the time required by previous methods.

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A Computational Fluid Dynamics Approach for Urban Area Transport and Dispersion Modeling

Cited by 43 publications

References 32 publications

Evaluation of Reynolds stress, k-ε and RNG k-ε turbulence models in street canyon flows using various experimental datasets

Evaluation of Reynolds stress, k-ε and RNG k-ε turbulence models in street canyon flows using various experimental datasets

Probabilistic Model for Concentration Fluctuations in Compact-Source Plumes in an Urban Environment

Generating seamless surfaces for transport and dispersion modeling in GIS

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