Peak factor estimation method of non‐Gaussian wind pressures on long‐span tri‐centered cylindrical roof structures. (30th November 2022)

• Record Type: Journal Article
• Authors: Wu, Yanru; Wen, Zhang; Wu, Xiaohong; Lv, Hang; Sun, Qing
• Is Part Of: Structural design of tall and special buildings. Volume 32:Number 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-30
• Subjects: long‐span tri‐centered cylindrical roof structure -- non‐Gaussian features -- peak factor -- peak factor estimation method -- wind pressure spectrum model -- wind tunnel test; Tall buildings -- Design and construction -- Periodicals; Structural design -- Periodicals; 690.1
• DOI: 10.1002/tal.1994
• Languages: English
• ISSNs: 1541-7794

Abstract

Summary: Claddings are susceptible to damage due to underestimation of extreme wind‐induced surface pressures. Commonly accepted methods for estimating the peak factor (an input used to determine cladding design loads) involve complex calculation‐intensive procedures. This research develops a four‐parameter unified auto‐spectral model of wind pressure to simplify peak factor estimation of wind‐induced surface pressure via analysis of wind tunnel wind load data on tri‐centered cylindrical roofs. Values of the model parameters were identified via statistical analysis of wind tunnel wind pressure measurement on two long‐span tri‐centered cylindrical roof structures with different curvatures. The study identified roof regions with non‐Gaussian features by inspecting probabilistic density functions of the standardized wind‐induced roof pressures and the third‐ and fourth‐order statistical moments of wind pressure time histories. The paper ultimately proposed and evaluated a simplified method for estimating the peak factors in the non‐Gaussian regions, the Three‐parameter Hermite Model, derived through the moment‐based Hermite Model, the Revised Hermite Model, and the parameter simplification accomplished in this study. The results show that the auto‐spectral model of wind‐induced roof pressures can accurately estimate the zero‐ and second‐order spectral moments, which reflects the wind pressure fluctuating characteristics and geometric features of spectral curves. Compared with the peak factors of the moment‐based Hermite Model and the Revised Hermite Model, the peak factor errors estimated by the Three‐parameter Hermite Model are all less than 10%. These results suggest that the Three‐parameter Hermite Model simplifies the calculation with acceptable accuracy.