Wind and Structures

Techno-Press (테크노프레스)
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Linear prediction and z-transform based CDF-mapping simulation algorithm of multivariate non-Gaussian fluctuating wind pressure

  • Jiang, Lei (School of civil engineering and architecture, Jiangsu University of science and technology) ;
  • Li, Chunxiang (Department of Civil Engineering, School of Mechanism and Engineering Science, Shanghai University) ;
  • Li, Jinhua (Department of Civil Engineering, East China Jiaotong University)
  • Received : 2020.06.07
  • Accepted : 2020.12.18
  • Published : 2020.12.25
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Abstract

Methods for stochastic simulation of non-Gaussian wind pressure have increasingly addressed the efficiency and accuracy contents to offer an accurate description of the extreme value estimation of the long-span and high-rise structures. This paper presents a linear prediction and z-transform (LPZ) based Cumulative distribution function (CDF) mapping algorithm for the simulation of multivariate non-Gaussian fluctuating wind pressure. The new algorithm generates realizations of non-Gaussian with prescribed marginal probability distribution function (PDF) and prescribed spectral density function (PSD). The inverse linear prediction and z-transform function (ILPZ) is deduced. LPZ is improved and applied to non-Gaussian wind pressure simulation for the first time. The new algorithm is demonstrated to be efficient, flexible, and more accurate in comparison with the FFT-based method and Hermite polynomial model method in two examples for transverse softening and longitudinal hardening non-Gaussian wind pressures.

Keywords

Acknowledgement

This work was supported by the National Natural Science Foundation of China (No.51378304 and No. 51778354 and No.11962006). Also, the authors wish to thank Professor Zhi-hong Zhang for the precious wind pressure data for the flexible structure.

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