Probabilistic wind spectrum model based on correlation of wind parameters in mountainous areas: Focusing on von Karman spectrum

Accurate evaluation of wind field characteristics in complex mountainous areas has essential reference signifi-cance for the wind-resistant design of bridges. This paper systematically considers the nonstationary charac-teristics of the wind field, the randomness, and the correlation of average and turbulent wind parameters (TWPs) via the field measurement data. Combined with the C-Vine Copula and inverse reliability method, the joint probability model (JPM) and environmental contour model of wind speed, turbulence intensity, and turbulence integral length are constructed, respectively. Finally, the probabilistic turbulence wind spectrum models are obtained. The results show that the nonstationary characteristics are prominent, and the disturbance by the wind speed threshold is slight; Furthermore, wind speed, turbulence intensity, and turbulence integral length have a strong nonlinear correlation with wind direction preference. Ignoring the influence of wind direction can incorrectly estimate the correlation characteristics between wind parameters (WPs). In addition, the environ-mental contour model derived from the joint probability model (JPM) of wind parameters (WPs) is far smaller than the extreme combination under a given probability without considering the correlation. It is concluded that the wind spectrum constructed in this paper can provide an essential reference for evaluating uncertainty in the design stage of long-span bridges.

Automated summary

This paper systematically considers the nonstationary characteristics, randomness, and correlation of wind field parameters through field measurement data. Joint probability model and environmental contour model are constructed, and probabilistic turbulence wind spectrum models are obtained. The results show that the wind field has prominent nonstationary characteristics and the wind speed threshold has little effect on the disturbance. Furthermore, ignoring wind direction can lead to incorrect estimation of correlation characteristics between wind parameters. The wind spectrum constructed in this paper provides an essential reference for evaluating uncertainty in the design stage of long-span bridges.