The present study is the logical successor to a preceding paper where the nature of wind pressures on a tall building was investigated by wind tunnel experimental tests. The statistical analysis showed that the pressure time series recorded in separated flow regions have significant non-Gaussian features. The results of this experimental work are used here to develop a suitable procedure to simulate the wind pressure time series on prismatic buildings. This procedure is based on translation processes. It is shown that the proposed method is very attractive for simulation based on experimental data because the translation processes are completely characterized by marginal distributions and covariance functions, which can be easily estimated. The obtained results show that a very high accuracy is achieved. The efficiency of the proposed procedure is related to the exact calculation of the covariance function and the complete utilization of the information given by the marginal distribution. Moreover, time-consuming procedures are avoided.
Non-Gaussian wind pressure on prismatic buildings. II: Numerical simulation
GIOFFRE', Massimiliano;GUSELLA, Vittorio;
2001
Abstract
The present study is the logical successor to a preceding paper where the nature of wind pressures on a tall building was investigated by wind tunnel experimental tests. The statistical analysis showed that the pressure time series recorded in separated flow regions have significant non-Gaussian features. The results of this experimental work are used here to develop a suitable procedure to simulate the wind pressure time series on prismatic buildings. This procedure is based on translation processes. It is shown that the proposed method is very attractive for simulation based on experimental data because the translation processes are completely characterized by marginal distributions and covariance functions, which can be easily estimated. The obtained results show that a very high accuracy is achieved. The efficiency of the proposed procedure is related to the exact calculation of the covariance function and the complete utilization of the information given by the marginal distribution. Moreover, time-consuming procedures are avoided.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.