Simulation and Peak Value Estimation of Non-Gaussian Wind Pressures Based on Johnson Transformation Model

Abstract

The simulation and peak value estimation of non-Gaussian wind pressures are important to the structural and cladding design of the building. Due to its straightforwardness and accuracy, the moment-based Hermite polynomial model (HPM) has been widely used. However, its effective region for monotonicity is limited, resulting in its unsuitability for non-Gaussian processes whose skewness and kurtosis are out of the effective region. On the other hand, the Johnson transformation model (JTM) has attracted attention due to its larger effective region compared with that of the HPM. Nevertheless, the systematic study of its application to the simulation and peak value estimation of non-Gaussian wind pressures is less addressed. Specifically, its comparison with the HPM is not well discussed. In this study, a set of closed-form formulas to determine the relationship between correlation coefficients of the non-Gaussian process and those of the underlying Gaussian process was derived, and they facilitate a JTM-based simulation method for the non-Gaussian process. Analytical expressions for the non-Gaussian peak factor were developed. Furthermore, the JTM was systematically compared with the HPM in terms of the translation function, which helps to understand the ensuing performance evaluation on these two models in the simulation and peak value estimation based on the very long wind pressure data. Results showed that the JTM-based peak value estimation method performs well for wind pressures with weak to mild non-Gaussianity, even those beyond the effective region of the HPM, although it may provide slightly worse estimation for strong softening processes compared with the HPM.