This paper investigates the statistics of the pressure coefficients and their peak factors in hyperbolic paraboloid roofs that are commonly used in tensile structures. The experimental peak factor statistics, estimated using pressure coefficient time histories experimentally measured in wind tunnel tests, were compared with the corresponding peak factor statistics estimated through the use of six analytical models available in the literature, namely the Davenport, classical Hermite, revised Hermite, modified Hermite, Translated-Peak-Process (TPP), and Liu's models. The basic assumption of the TPP model, i.e., that the pressure coefficient local peaks follow a Weibull distribution, was validated and was used to estimate analytically the peak factors’ quantiles. Different time history durations and different error measures were also considered. The non-Gaussian properties of the pressure coefficient processes were characterized at different roof locations for different wind angles of attack. It was found that: (1) the region of non-Gaussianity is significantly affected by the wind angle; (2) as expected, the Davenport model underestimates the peak factor mean and standard deviation in regions of high non-Gaussianity; (3) the modified Hermite model provides the best estimates overall of the peak factor mean; and (4) the TPP model provides the best estimates overall of the peak factor standard deviation. In addition, the modified root mean squared error was found to provide the most reliable assessment of the analytical models’ accuracy among the different error measures considered in this study. © 2018 Elsevier Ltd

Peak factor statistics of wind effects for hyperbolic paraboloid roofs

Rizzo F.;Sepe V.
2018

Abstract

This paper investigates the statistics of the pressure coefficients and their peak factors in hyperbolic paraboloid roofs that are commonly used in tensile structures. The experimental peak factor statistics, estimated using pressure coefficient time histories experimentally measured in wind tunnel tests, were compared with the corresponding peak factor statistics estimated through the use of six analytical models available in the literature, namely the Davenport, classical Hermite, revised Hermite, modified Hermite, Translated-Peak-Process (TPP), and Liu's models. The basic assumption of the TPP model, i.e., that the pressure coefficient local peaks follow a Weibull distribution, was validated and was used to estimate analytically the peak factors’ quantiles. Different time history durations and different error measures were also considered. The non-Gaussian properties of the pressure coefficient processes were characterized at different roof locations for different wind angles of attack. It was found that: (1) the region of non-Gaussianity is significantly affected by the wind angle; (2) as expected, the Davenport model underestimates the peak factor mean and standard deviation in regions of high non-Gaussianity; (3) the modified Hermite model provides the best estimates overall of the peak factor mean; and (4) the TPP model provides the best estimates overall of the peak factor standard deviation. In addition, the modified root mean squared error was found to provide the most reliable assessment of the analytical models’ accuracy among the different error measures considered in this study. © 2018 Elsevier Ltd
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/696865
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