A Hilbert-wavelet-based nonstationarity index for multi-level quantification of extreme winds. Issue 215 (August 2021)

• Record Type: Journal Article
• Authors: Wang, Haifeng; Wu, Teng
• Is Part Of: Journal of wind engineering and industrial aerodynamics. Issue 215(2021)
• Publication Date: 2021-08
• Subjects: Degree of nonstationarity -- Multi-level quantification -- Hilbert-wavelet-based -- Aerodynamics -- Structural dynamics; Wind-pressure -- Periodicals; Buildings -- Aerodynamics -- Periodicals; Pression du vent -- Périodiques; Constructions -- Aérodynamique -- Périodiques; Buildings -- Aerodynamics; Wind-pressure; Periodicals
• DOI: 10.1016/j.jweia.2021.104682
• Languages: English
• ISSNs: 0167-6105

Abstract

Abstract: Extreme wind events (e.g., thunderstorm downbursts) often present strong nonstationarities in terms of time-varying mean, amplitude modulation and frequency modulation. The stationary-wind assumption adopted in the traditional analysis framework for wind-induced structural responses may lead to severely biased estimates in nonstationary scenarios. Accordingly, advanced methodologies have recently emerged to investigate nonstationary wind effects on structures. Since the consideration of nonstationary winds and associated structural aerodynamics and dynamics usually involves more time and effort in comparison of stationary case, it is important to first measure the degree of nonstationarity of wind signals for selecting an appropriate analysis framework (stationary or nonstationary). In this study, a Hilbert-wavelet-based nonstationarity index is developed to quantify the nonstationarity of extreme winds. The joint utilization of Hilbert transform and wavelet packet decomposition provides a sharp time-frequency representation of the analyzed signal, and hence lays a solid foundation for the nonstationarity quantification. To highlight that the same wind nonstationarity may present different contributions to dynamic responses of various structures, the structural aerodynamics and dynamics are integrated into the proposed nonstationarity index to form a multi-level quantification framework. Furthermore, the obtained Hilbert-wavelet-based multi-level nonstationarity index of a nonstationary wind signal is first summarized over the time and frequency domains and then normalized by the corresponding nonstationarity index of an impulse signal (treated as the most nonstationary signal) for convenient application and easy interpretation of the quantification results. The effectiveness of the proposed index for multi-level quantification of nonstationarity is well demonstrated with its applications to synthesized signals as well as field-measured downburst winds. Highlights: A Hilbert-wavelet-based nonstationarity index is developed to quantify wind nonstationarity. Structural aerodynamics and dynamics are integrated into the nonstationarity index. Effectiveness of the index for multi-level quantification of nonstationarity is well demonstrated.