Run-Time and Statistical Pedestrian Level Wind Map for Downtown Toronto

Abstract

Rapid population growth and urbanization have led to the development of high-density and high-rise structures around the world. Tall structures in proximity can negatively affect pedestrian comfort by directing strong winds to the ground near the structure. Pedestrian level wind (PLW) may affect local businesses/services, pedestrian comfort and in extreme cases jeopardizes pedestrian safety. The downtown portion of the City of Toronto (∼10 km2) was chosen as the study region due to the recent development of many high-rise structures. The region was split into 10 zones and Computational Fluid Dynamics (CFD) was utilized to study the wind effects of the local building geometry and arrangements. Wind velocities were extracted from Computational Fluid Dynamics and coupled with historical meteorological data from Billy Bishop Airport. The coupled velocities from CFD were found to be within 20 and 5% RMSE, respectively, of the recorded data at the wind station for 85% of the sampled data. Wind velocities were then extracted at various elevations and coupled with meteorological weather data to generate real-time, historical, and statistical visualization of local wind fields. This study enables the prediction of real-time, historical, and statistical wind speeds, bearings at various elevations. Visualization of the flow field provides important insights for pedestrians, architects, engineers, and city planners regarding local wind speeds and identify problematic areas.

Towards Safe Drone Transportation in Toronto

“…-For the first model of downtown Toronto, the average root mean square error was found to be 12% for wind speeds and 8% for wind bearing. This is an improvement from previous models developed by Chen et al (2021) who had a root mean square error of 20% for wind speeds and 15% for wind bearing. It is important to note that field measurements were made in an area with complex aerodynamics and on the top of a building with some obstructions at the northwest corner.…”

“…To predict wind fields around buildings, computational fluid dynamics (CFD) has been used as a primary tool to solve the Reynolds Averaged Navier-Stokes (RANS) equations. CFD studies have been done in urban environments most recently by Blocken et al (2012), Mirzaei et al (2013), Tominaga et al (2013); Elshaer et al (2017), andChen et al (2021). In many cases those study results have been compared to experimental data from wind tunnel tests and metrological stations and have proven to be sufficiently reliable.…”

“…For example, CFD-based studies have been conducted to study the wind flow near street level byHu et al (2005),Mochida & Lun, (2008),Blocken et al (2012), Cui et al (2019), and Weerasuriya et al (2020. Most recently,Chen et al (2021) used CFD to examine the real-time pedestrian level winds in downtown Toronto. The study extracted wind velocities around the pedestrian level and coupled them with meteorological weather data to generate realtime, historical, and statistical visualizations of local wind fields within the downtown core.In many cases those CFD simulations have been compared to experimental data from wind tunnel tests, metrological station measurements, and UAV measurements, although the latter two are far less common.…”

“…Hu et al (2005),Mochida & Lun, (2008),Blocken et al (2012),Cui et al (2019),Weerasuriya et al (2020), andChen et al (2021). In many cases those study results have been compared to experimental data from wind tunnel tests, metrological station measurements, and UAV measurements, although the latter two are far less common.…”

Design of PID and ADRC based adaptively anti-disturbance quadrotor hovering controller

“…The pedestrian and long-term wind are usually caused by macroatmospheric activity at the regional level. It is affected by thermodynamic flow caused by thermal effects such as thermal effects related with day and night changes [7] and heat island effects [1]. Due to the complexity and chaos of urban wind fields, we only conduct qualitative analysis here.…”