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Wind and Structures
  Volume 36, Number 2, February 2023 , pages 121-131
DOI: https://doi.org/10.12989/was.2023.36.2.121
 


Fatigue wind load spectrum construction based on integration of turbulent wind model and measured data for long-span metal roof
Liman Yang, Cong Ye, Xu Yang, Xueyao Yang and Jian-ge Kou

 
Abstract
    Aiming at the problem that fatigue characteristics of metal roof rely on local physical tests and lacks the cyclic load sequence matching with regional climate, this paper proposed a method of constructing the fatigue load spectrum based on integration of wind load model, measured data of long-span metal roof and climate statistical data. According to the turbulence characteristics of wind, the wind load model is established from the aspects of turbulence intensity, power spectral density and wind pressure coefficient. Considering the influence of roof configuration on wind pressure distribution, the parameters are modified through fusing the measured data with least squares method to approximate the actual wind pressure load of the roof system. Furthermore, with regards to the wind climate characteristics of building location, Weibull model is adopted to analyze the regional meteorological data to obtain the probability density distribution of wind velocity used for calculating wind load, so as to establish the cyclic wind load sequence with the attributes of regional climate and building configuration. Finally, taking a workshop's metal roof as an example, the wind load spectrum is constructed according to this method, and the fatigue simulation and residual life prediction are implemented based on the experimental data. The forecasting result is lightly higher than the design standards, consistent with general principles of its conservative safety design scale, which shows that the presented method is validated for the fatigue characteristics study and health assessment of metal roof.
 
Key Words
    fatigue load spectrum; life prediction; metal roof; regional climate characteristic; wind load modelling
 
Address
Liman Yang, Cong Ye, Xu Yang, Xueyao Yang and Jian-ge Kou:School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
 

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