Investigation of Re -independence of turbulent flow and pollutant dispersion in urban street canyon using numerical wind tunnel (NWT) models

Cui, Peng-Yi; Li, Zhuo; Tao, Wen‐Quan

doi:10.1016/j.ijheatmasstransfer.2014.07.096

Cited by 50 publications

(26 citation statements)

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“…Re D increase, the discrepancies in the velocity distributions get smaller and smaller for this two models. Our previous work illustrated that the critical Re number was independent on the three high-Reynolds-number models (standard, RNG and realizable k-ε models) [37]. In this study, we can expect that the predicted critical Re number is independent on the turbulence model adopted, at least in the range of standard k-ε model and the low Re k-ε model (details will be given later).…”

Section: Validations For Nwt Modelmentioning

confidence: 63%

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Numerical investigations on Re-independence for the turbulent flow and pollutant dispersion under the urban boundary layer with some experimental validations

Cui

Tao

2017

International Journal of Heat and Mass Transfer

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This paper numerically studied the Re-independence of turbulent flow and pollutant dispersion around five scaled building models. The RANS-based CFD model, hereafter called numerical wind tunnel (NWT) model, was validated by wind-tunnel experiments and applied to investigate the flow-structure independence on building Reynolds number (Re H ) and roughness Reynolds number (Re r ). The ratio of relative change (RRC) was used to evaluate the Re-independence with 5% selected as the threshold. The results show that the critical Re H (Re H, crit ) is strongly affected by the building structure, particularly the building height. However, the value of the critical Re r (Re r , crit ) in the pedestrian level plane changes very little with the different building models, which is suggested to be 25 in terms of the RRC criterion. Distributions of dimensionless velocity and concentration in the pedestrian level planes validated this suggested value. For the RANS turbulence models tested in this paper (high Reynolds number model and low Reynolds number model) the predicted value of Re r , crit is independent on the model. This work improves © 2016. This manuscript version is made available under the Elsevier user license http://www.elsevier.com/open-access/userlicense/1.0/ the understanding of Re-independence in the investigation of the flow and pollutant dispersion by using wind-tunnel experiment.There has been particular concern on flow-structure investigations in urban areas over the last few decades which arises from the increased levels of air pollutants such as PM10 and PM2.5 in urban atmosphere in China [1-3]. The heavy fog haze and photochemical smog emerge out of the various interactions and deteriorate air quality seriously, affecting people's health, especially in large cities [4-7]. Many previous studies on the air pollutant dispersion within urban regions started from the investigations of the air flow characteristics because the flow structure determines the pollutant distribution [8-10].Traditional methods to investigate flow characteristics include the field measurements [11,12] and laboratory modeling in wind tunnels or water channels [13][14][15]. However, there are many limitations and difficulties to measure flow field under real atmospheric boundary-layer conditions due to the uncertainty of the climate conditions and other measurement inconveniences [16] while these physical conditions can be artificially controlled by laboratory modeling. Snyder pointed out that for modeling a conventional fluid flow and pollution dispersion the most important criteria are Reynolds number and Schmidt number [17,18].It is well-known that for the flow similarity, Reynolds number should be the same in the wind-tunnel experiments [19,20]. Nevertheless, it's rather difficult to implement this criterion using the models with a small scale ratio ranging from 1:100 to 1:1000. Fortunately, when the Reynolds number is larger than a critical value the flow structure over a rough surface would be almost independent on the Reynolds n...

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Section: Validations For Nwt Modelmentioning

confidence: 63%

“…We proposed the following quantity (RRC) given in Eq. 11 for judging whether the flow can be regarded into the Re-independence regime [37] (11)…”

Section: The Physical Quantity For Determining Re R Critmentioning

confidence: 99%

Numerical investigations on Re-independence for the turbulent flow and pollutant dispersion under the urban boundary layer with some experimental validations

Cui

Tao

2017

International Journal of Heat and Mass Transfer

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“…This means that the flow conditions considered in the present paper are not similar to the common atmospheric boundary layer flow scenario. To simulate a full scale canyon condition, the scalability of experimental results should be proven by a Re-independence test of results [72]. A further scalability issue is due to the particle aerodynamics itself.…”

Section: A N U S C R I P Tmentioning

confidence: 99%

A simplified benchmark of ultrafine particle dispersion in idealized urban street canyons: A wind tunnel study

Stabile

Arpino

Buonanno

et al. 2015

Building and Environment

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“…A tracer gas was emitted by a line source placed at the bottom of one street canyon and the concentrations of pollutant were measured at several locations on the walls and roofs of buildings on either side of the street containing the source (Fig. 1), and it is presented in dimensionless form Due to increasing computer power, numerous studies using CFD techniques have been performed using RANS models and lately LES, DES and DNS approaches, simulating explicitly detailed fl ow, pollutant dispersion patterns in street canyons related to various parameters such as street geometries, building roof shapes, thermal effects and trees planting (Sini, Anquetin & Mestayer, 1996;Rafailidis, 1997;Theodoridis & Moussiopoulos, 2000;Xiaomin, Zhen & Jiasong, 2005;Xie, Huang & Wang, 2005;Nazridoust & Ahmadi, 2006;Huang, Hu & Zeng, 2009;Yassin, 2011;Salim, Buccolieri, Chan & Di Sabatino, 2011;Gallagher, Gill & McNabola, 2012;Tong & Leung, 2012;Moonen, Gromke & Dorer, 2013;Takano & Moonen, 2013;Allegrini, Dorer & Carmeliet, 2014;Cui, Li & Tao, 2014;Liu & Wong, 2014;Madalozzo, Braun, Awruch & Morsch, 2014;Ng & Chau, 2014;Efthimiou, Berbekar, Harms, Bartzis & Lietl, 2015). Some of these CFD studies have been performed to investigate in detail the effects of building confi guration on fl ows and pollutant dispersion.…”

Section: Introductionmentioning

confidence: 99%

A numerical analysis of pollutant dispersion in street canyon: influence of the turbulent Schmidt number

Abed

Bouarbi

Bouzit

et al. 2017

Przegląd Naukowy Inżynieria I Kształtowanie Środowiska

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Realizing the growing importance and availability of motor vehicles, we observe that the main source of pollution in the street canyons comes from the dispersion of automobile engine exhaust gas. It represents a substantial effect on the micro-climate conditions in urban areas. Seven idealized-2D building configurations are investigated by numerical simulations. The turbulent Schmidt number is introduced in the pollutant transport equation in order the take into account the proportion between the rate of momentum turbulent transport and the mass turbulent transport by diffusion. In the present paper, we attempt to approach the experimental test results by adjusting the values of turbulent Schmidt number to its corresponding application. It was with interest that we established this link for achieving our objectives, since the numerical results agree well with the experimental ones. The CFD code ANSYS CFX, the k, e and the RNGk-e models of turbulence have been adopted for the resolutions. From the simulation results, the turbulent Schmidt number is a range of 0.1 to 1.3 that has some effect on the prediction of pollutant dispersion in the street canyons. In the case of a flat roof canyon configuration (case: runa000), appropriate turbulent Schmidt number of 0.6 is estimated using the k-epsilon model and of 0.5 using the RNG k-e model.

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Investigation of Re -independence of turbulent flow and pollutant dispersion in urban street canyon using numerical wind tunnel (NWT) models

Cited by 50 publications

References 38 publications

Numerical investigations on Re-independence for the turbulent flow and pollutant dispersion under the urban boundary layer with some experimental validations

Numerical investigations on Re-independence for the turbulent flow and pollutant dispersion under the urban boundary layer with some experimental validations

A simplified benchmark of ultrafine particle dispersion in idealized urban street canyons: A wind tunnel study

A numerical analysis of pollutant dispersion in street canyon: influence of the turbulent Schmidt number

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