A simulation methodology of the stationary non-Gaussian stochastic wind pressure field

• A framework is presented to simulate a stochastic wind pressure field on structures.
• Transformation functions are derived for two general types of scaled covariance function.
• Reasons for non-negative definiteness of the Gaussian PSDF matrices are investigated.
• A method to modify entries in the factorized PSDF matrices is proposed.
• The generated stochastic sample can satisfy the requirements of data from the wind tunnel testing.

A simulation methodology is presented to simulate a stationary stochastic wind pressure field consisting of Gaussian and non-Gaussian regions based on the zero memory nonlinearity translation method and the spectral representation method. The transformation functions between the non-Gaussian and Gaussian scaled covariance functions are derived for the stochastic process following the lognormal or the Weibull distribution. A scheme is then proposed to cope with the negative definite matrices of the power spectral density function while the underlying Gaussian stochastic processes are generated. Finally, a numerical example is given to illustrate that the samples generated by the proposed method can represent the statistical and spectral properties as well as the spatial correlation of the wind pressure processes obtained from wind tunnel testing.