Simulation of stationary non-Gaussian multivariate wind pressures based on moment-based piecewise Johnson transformation model

Fast and accurate simulation of non-Gaussian wind pressures are desired sometimes in the wind-resistant design of buildings under stationary winds. Recently, attracted by its wide application range, the moment-based Johnson transformation model (JTM) has been successfully applied by some authors of this paper. However, the simulation accuracy and efficiency of the moment-based JTM still need to be improved. Inspired by the successful application of the proposed newly defined statistical moments to the moment-based Hermite polynomial model (HPM), this paper applies these moments to the JTM named moment-based piecewise JTM (PJTM) and proposes a novel PJTM-based simulation method. In this method, a set of close-form formulas to estimate the parameters of PJTM are firstly proposed. Secondly, the analytical formula to determine the correlation distortion relationship by PJTM is further developed. Finally, the performance of the proposed method is verified by the very long non-Gaussian wind pressure data from a wind tunnel test. Results shown the proposed method by PJTM can not only present higher simulation efficiency but also better simulation accuracy compared with JTM and can present higher simulation efficiency compared with moment-based piecewise HPM.

Automated summary

This paper proposes a novel PJTM-based simulation method by applying the newly defined statistical moments to the moment-based JTM. The method improves the simulation accuracy and efficiency by utilizing a set of close-form formulas to estimate the parameters of PJTM and developing an analytical formula to determine the correlation distortion relationship. Experimental results show that the proposed PJTM method outperforms both JTM and moment-based piecewise HPM in terms of simulation efficiency and accuracy.