Prediction of long-term extreme response due to non-Gaussian wind on a HSR cable-stayed bridge by a hybrid approach

Zhiwei Xu, Gonglian Dai, Y. Frank Chen, Huiming Rao

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The effect of non-Gaussian inflows on structural long-term extreme buffeting responses has been little investigated. In this study, the sensitivity of long-term extreme value distribution (EVD) of a high-speed railway cable-stayed bridge to the non-Gaussian intensity is studied first. The turbulence skewness and kurtosis are then taken as the environmental variables to investigate their single and combined effects on bridge's long-term EVDs based on a proposed hybrid approach that combines the machine learning algorithm and virtual process method. The 2.5-year measured turbulence wind and 40-year annual extreme wind speed recorded near the bridge site are utilized to describe the probability distributions of the skewness and kurtosis of turbulence wind and 10-min mean wind speed. The research results reveal that: (1) the long-term EVD of torsional angle is more sensitive to non-Gaussian turbulence wind than vertical and lateral extreme responses; (2) the single effect of turbulence skewness is detrimental but limited, and the combined effect of skewness and kurtosis of turbulence u (w) is also weak within the considered MRIs (1–100 years). Lastly, the virtual process method is shown to be applicable to predict structural long-term EVDs; and it is efficient without losing significant prediction accuracy.

Original languageEnglish (US)
Article number105217
JournalJournal of Wind Engineering and Industrial Aerodynamics
StatePublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Renewable Energy, Sustainability and the Environment
  • Mechanical Engineering


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