350 research outputs found

    Large-Eddy Simulation of Flow and Pollutant Transport in Urban Street Canyons with Ground Heating

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    Our study employed large-eddy simulation (LES) based on a one-equation subgrid-scale model to investigate the flow field and pollutant dispersion characteristics inside urban street canyons. Unstable thermal stratification was produced by heating the ground of the street canyon. Using the Boussinesq approximation, thermal buoyancy forces were taken into account in both the Navier–Stokes equations and the transport equation for subgrid-scale turbulent kinetic energy (TKE). The LESs were validated against experimental data obtained in wind-tunnel studies before the model was applied to study the detailed turbulence, temperature, and pollutant dispersion characteristics in the street canyon of aspect ratio 1. The effects of different Richardson numbers (Ri) were investigated. The ground heating significantly enhanced mean flow, turbulence, and pollutant flux inside the street canyon, but weakened the shear at the roof level. The mean flow was observed to be no longer isolated from the free stream and fresh air could be entrained into the street canyon at the roof-level leeward corner. Weighed against higher temperature, the ground heating facilitated pollutant removal from the street canyon.Singapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Monitorin

    Defining the roughness sublayer and its turbulent statistics

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    The roughness sublayer in a turbulent openchannel flow over a very rough wall is investigated experimentally both within the canopy and above using particle image velocimetry by gaining complete optical access with new methodologies without disturbing the flow. This enabled reliable estimates of the double-averaged mean and turbulence profiles to be obtained by minimizing and quantifying the usual errors introduced by limited temporal and spatial sampling. It is shown, for example, that poor spatial sampling can lead to erroneous vertical profiles in the roughness sublayer. Then, in order to better define and determine the roughness sublayer height, a methodology based on the measured spatial dispersion is proposed which takes into account temporal sampling errors. The results reveal values well below the usual more ad hoc estimates for all statistics. Finally, the doubleaveraged mean and turbulence statistics in the roughness sublayer are discussed
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