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Wind and Structures Volume 31, Number 6, December 2020 , pages 549-560 DOI: https://doi.org/10.12989/was.2020.31.6.549 |
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Linear prediction and z-transform based CDF-mapping simulation algorithm of multivariate non-Gaussian fluctuating wind pressure |
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Lei Jiang, Chunxiang Li and Jinhua Li
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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 nonGaussian 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:1School 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:Department of Civil Engineering, East China Jiaotong University, Nanchang 330013, China | ||