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http://dx.doi.org/10.12989/was.2020.30.3.231

Numerical characterization of downburst wind field at WindEEE dome  

Ibrahim, Ibrahim (Department of Civil and Environmental Engineering, Western University)
Aboshosha, Haitham (Department of Civil Engineering, Ryerson University)
El Damatty, Ashraf (Department of Civil and Environmental Engineering, Western University)
Publication Information
Wind and Structures / v.30, no.3, 2020 , pp. 231-243 More about this Journal
Abstract
Downbursts are acknowledged for being a major loading hazard for horizontally-extending structures like transmission line systems. With these structures being inherently flexible, it is important to characterize the turbulence associated with the wind flow of downburst events being essential to quantify dynamic excitations on structures. Accordingly, the current study numerically characterizes the downburst wind field of open terrain simulated at the Wind Engineering, Energy and Environment (WindEEE) dome testing facility at The University of Western Ontario in Canada through a high-resolution large eddy simulation (LES). The study validates the numerical simulation considering both the mean and the turbulent components of the flow. It then provides a detailed visual description of the flow at WindEEE through the capabilities enabled by LES to identify the key factors affecting the flow. The study also presents the spatial distribution of turbulence intensities and length scales computed from the numerical model and compares them with previous values reported in the literature. The comparison shows the ability of the downburst simulated at WindEEE to reproduce turbulence characteristics similar to those reported from field measurements. The study also indicates that downburst turbulence is well-correlated circumferentially which imposes high correlated loads on horizontally-distributed structures such as transmission lines.
Keywords
downburst; WindEEE; Large Eddy Simulation (LES); turbulence; length scales; high intensity wind;
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Times Cited By KSCI : 4  (Citation Analysis)
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