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Computational Fluid Dynamics-Aided Simulation of Twisted Wind Flows in Boundary Layer Wind Tunnel.

Authors :
Yi, Zijing
Wang, Lingjun
Li, Xiao
Zhang, Zhigang
Zhou, Xu
Yan, Bowen
Source :
Applied Sciences (2076-3417); Feb2024, Vol. 14 Issue 3, p988, 23p
Publication Year :
2024

Abstract

The twisted wind flow (TWF), referring to the phenomenon of wind direction varying with height, is a common feature of atmospheric boundary layer (ABL) winds, noticeably affecting the wind-resistant structural design and the wind environment assessment. The TWF can be effectively simulated by a guide vane system in wind tunnel tests, but the proper design and configuration of the guide vanes pose a major challenge as practical experience in using such devices is still limited in the literature. To address this issue, this study aims to propose an approach to determining the optimal wind tunnel setup for TWF simulations using a numerical wind tunnel, which is a replica of its physical counterpart, using computational fluid dynamics (CFD) techniques. By analyzing the mechanisms behind guide vanes for generating TWF based on CFD results, it was found that the design must take into account three key parameters, namely, (1) the distance from the vane system to the side wall, (2) the distance from the vane system to the model test region, and (3) the separation between the vanes. Following the optimal setup obtained from the numerical wind tunnel, TWF profiles matching both the power-law and Ekman spiral models, which, respectively, reflect the ABL and wind twist characteristics, were successfully generated in the actual wind tunnel. The findings of this study provide useful information for wind tunnel tests as well as for wind-resistant structural designs and wind environment assessment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
3
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
175372230
Full Text :
https://doi.org/10.3390/app14030988