Simulation methodology for stochastic wind pressure field composed of gaussian and non-gaussian regions
LUO Jun-jie1,2, SU Cheng1,2, HAN Da-jian1,2
1. School of Civil Engineering and Transportation, 2. State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China
Abstract：Simulation of stochastic fluctuating wind pressure field acting on roofs should meet with the requirements of statistical and spectral characteristics. The zero memory nonlinearity (ZMNL) transformation method is presented to generate the stochastic wind pressure time histories in this paper. A detailed procedure is provided, and two crucial problems are addressed. Firstly, the standard covariance function for transforming multivariate non-Gaussian stochastic process vector into the corresponding Gaussian one is derived for simulating the stochastic wind pressure process samples following the lognormal distribution and the Weibull distribution. Secondly, a new method is proposed to cope with the negative definite matrices of spectral density function associated with certain frequencies while generating the Gaussian stochastic process vector. After that, an illustrated example is given. It is shown that the proposed method can generate stochastic wind pressure field samples with specified statistical and spectral natures of the data obtained by wind tunnel experiment.
2012, Vol. 31 
