This paper and a companion paper present a complete study (analysis, modeling, and numerical simulation) of the wind pressure field on prismatic tall buildings, taking into account its non-Gaussian nature. In this paper, the analysis of the data obtained by wind tunnel experimental tests is used to provide a systematic characterization of the stochastic pressure field. First, the experimental work is briefly described; then the wind pressure statistical moments up to the second order (mean, standard deviation, and spectral densities) are obtained. Comparisons with results reported in the literature are used to validate the reliability of the experimental measurements. Histograms of the experimental data in the separated flow regions (vortex shedding and wake) are used to identify the non-Gaussian nature of the pressure fluctuations. Maps of higher-order statistical moments (skewness and kurtosis coefficients) at the four faces of the model are proposed to obtain an easy tool to localize regions with non-Gaussian features and give a measurement of the non-Gaussianity. The influence of the incoming flow direction on the parameters of interest is also considered.
Non-Gaussian Wind Pressure on Prismatic Buildings I: Stochastic Field
GIOFFRE', Massimiliano;GUSELLA, Vittorio;
2001
Abstract
This paper and a companion paper present a complete study (analysis, modeling, and numerical simulation) of the wind pressure field on prismatic tall buildings, taking into account its non-Gaussian nature. In this paper, the analysis of the data obtained by wind tunnel experimental tests is used to provide a systematic characterization of the stochastic pressure field. First, the experimental work is briefly described; then the wind pressure statistical moments up to the second order (mean, standard deviation, and spectral densities) are obtained. Comparisons with results reported in the literature are used to validate the reliability of the experimental measurements. Histograms of the experimental data in the separated flow regions (vortex shedding and wake) are used to identify the non-Gaussian nature of the pressure fluctuations. Maps of higher-order statistical moments (skewness and kurtosis coefficients) at the four faces of the model are proposed to obtain an easy tool to localize regions with non-Gaussian features and give a measurement of the non-Gaussianity. The influence of the incoming flow direction on the parameters of interest is also considered.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.