Validation of Simplified Urban-Canopy Aerodynamic Parametrizations Using a Numerical Simulation of an Actual Downtown Area

Ramirez, Nicolas; Afshari, Afshin; Norford, Leslie K.

doi:10.1007/s10546-018-0345-7

Cited by 15 publications

(3 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Perhaps the most widely used model, developed by Macdonald et al (1998), uses frontal plan area, average building height, and building drag coefficient to parametrize roughness. Successful attempts have been made to apply roughness models in cities by , Ramirez et al (2018), andHuq &Rahman (2018). However, to the author's knowledge, there is no study that successfully applied a roughness parameterization model to get accurate results in the drone flight environment.…”

Section: Using Cfd To Predict Wind Fieldsmentioning

confidence: 99%

“…To account for the roughness of the buildings removed from the model, the method for estimating surface roughness of obstacle arrays developed by Macdonald et al (1998) was employed and is defined by Equation 3-1. This model was previously utilized by Coceal & Belcher (2004), Buccolieri & Sabatino (2011), Dallman et al (2013), , Ramirez et al (2018), andHuq &Rahman (2018) to parameterize roughness.…”

Section: Model Roughness Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Towards Safe Drone Transportation in Toronto

Gianfelice

2024

Preprint

View full text Add to dashboard Cite

<p>This thesis focuses on the development of an application capable of predicting wind velocities at any location in Toronto that can be used to improve drone flight safety. First, computational fluid dynamics (CFD) was used to study the effect of downtown building geometry on the wind field. Wind speeds and bearings from CFD were extracted, compared to local weather station measurements, and were within 12% and 8% root mean square error (RMSE), respectively. Next, a simplified CFD model was developed to efficientlymodelToronto’ssuburbanzones. This model utilized a roughness parameterization to implicitly model small buildings. When compared to weather station data,the wind speeds and bearings from this model were within 8% and 2% RMSE, respectively. In combination, these chapters outline a methodology for accurately obtaining real time, historical, forecast, and statistical wind velocities in the drone flight environment which can be used to improve flight safety and efficiency. </p>

show abstract

Section: Using Cfd To Predict Wind Fieldsmentioning

confidence: 99%

Section: Model Roughness Parametersmentioning

confidence: 99%

Towards Safe Drone Transportation in Toronto

Gianfelice

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Based on the range of a um in the literature, Macdonald (2000) suggests a um = 9.6λ f , which would correspond to about 3 to 4 for the datasets used in this study. Ramirez et al (2018) report values < 2. Note that this profile does not generally satisfy the no-slip condition, but a shallow reflection layer at the bottom (see Sect.…”

Section: Mean Wind Speedmentioning

confidence: 99%

Including the Urban Canopy Layer in a Lagrangian Particle Dispersion Model

Stöckl

Rotach

Kljun

2022

Boundary-Layer Meteorol

View full text Add to dashboard Cite

In this study we introduce a novel extension of an existing Lagrangian particle dispersion model for application over urban areas by explicitly taking into account the urban canopy layer. As commonly done, the original model uses the zero-plane displacement as a lower boundary condition, while the extension reaches to the ground. To achieve this, spatially-averaged parametrizations of flow and turbulence characteristics are created by fitting functions to observational and numerical data. The extended model is verified with respect to basic model assumptions (well-mixed condition) and its behaviour is investigated for unstable/neutral/stable atmospheric stabilities. A sensitivity study shows that the newly introduced model parameters characterizing the canopy turbulence impact the model output less than previously existing model parameters. Comparing concentration predictions to the Basel Urban Boundary Layer Experiment—where concentrations were measured near roof level—shows that the modified model performs slightly better than the original model. More importantly, the extended model can also be used to explicitly treat surface sources (traffic) and assess concentrations within the urban canopy and near the surface (pedestrian level). The small improvement with respect to roof level concentrations suggests that the parametrized canopy profiles for flow and turbulence characteristics realistically represent the dispersion environment on average.

show abstract

Turbulent flows over real heterogeneous urban surfaces: Wind tunnel experiments and Reynolds-averaged Navier-Stokes simulations

Cheng

et al. 2021

Build. Simul.

View full text Add to dashboard Cite

Validation of Simplified Urban-Canopy Aerodynamic Parametrizations Using a Numerical Simulation of an Actual Downtown Area

Cited by 15 publications

References 86 publications

Towards Safe Drone Transportation in Toronto

Towards Safe Drone Transportation in Toronto

Including the Urban Canopy Layer in a Lagrangian Particle Dispersion Model

Turbulent flows over real heterogeneous urban surfaces: Wind tunnel experiments and Reynolds-averaged Navier-Stokes simulations

Contact Info

Product

Resources

About