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CFD simulation study on wind load of perforated traffic sign board.


ABSTRACT: Traffic sign boards are often blown away by strong winds, seriously endangering the safety of vehicles and pedestrians. To increase their resistance to strong winds, sign boards are perforated. Using computational fluid dynamics simulations, the wind load resistance of traffic signs with holes was optimised. By comparing the solutions to different turbulence models with empirical results, it was found that the simulation results of the re-normalisation group (RNG) model have the smallest error. Therefore, the RNG model is used to simulate the wind load of traffic sign boards with different perforation diameters and different hole spacings under different wind speeds. By analysing the wind pressure distribution on the surface of the perforated traffic sign board, the perforation scheme for different regions of the sign board under different wind loads was obtained. The results show that reasonable perforation diameters and hole spacings can reduce the wind load and improve the wind load resistance of sign boards. This study provides decision-makers with useful information for installing traffic signs in areas affected with strong winds, thereby improving the wind resistance of traffic signs and ensuring traffic safety.

SUBMITTER: Xu J 

PROVIDER: S-EPMC7580890 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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CFD simulation study on wind load of perforated traffic sign board.

Xu Jinqiang J   Xu Hai H   Zeng Chenghong C   Xie Chengguang C   Guo Jiangang J  

PloS one 20201022 10


Traffic sign boards are often blown away by strong winds, seriously endangering the safety of vehicles and pedestrians. To increase their resistance to strong winds, sign boards are perforated. Using computational fluid dynamics simulations, the wind load resistance of traffic signs with holes was optimised. By comparing the solutions to different turbulence models with empirical results, it was found that the simulation results of the re-normalisation group (RNG) model have the smallest error.  ...[more]

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