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Wind and Structures
  Volume 31, Number 6, December 2020, pages 549-560
DOI: http://dx.doi.org/10.12989/was.2020.31.6.549
 


Linear prediction and z-transform based CDF-mapping simulation algorithm of multivariate non-Gaussian fluctuating wind pressure
Lei Jiang, Chunxiang Li and Jinhua Li

 
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.
 
Key Words
    Non-Gaussian wind pressure; LPZ spectral analysis; CDF-mapping; Multivariate simulation
 
Address
Lei Jiang:School of civil engineering and architecture, Jiangsu University of science and technology, Zhenjiang 212005, China/ Department of Civil Engineering, School of Mechanism and Engineering Science,
Shanghai University, 333 Nanchen Road, Shanghai 200444, China
Chunxiang Li: Department of Civil Engineering, School of Mechanism and Engineering Science,
Shanghai University, 333 Nanchen Road, Shanghai 200444, China
Jinhua Li: 3Department of Civil Engineering, East China Jiaotong University, Nanchang 330013, China
 

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