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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  

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)
Publication Information
Wind and Structures / v.31, no.6, 2020 , pp. 549-560 More about this Journal
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
Non-Gaussian wind pressure; LPZ spectral analysis; CDF-mapping; Multivariate simulation;
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Times Cited By KSCI : 10  (Citation Analysis)
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