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高斯/非高斯混合随机风压场的模拟方法
引用本文:罗俊杰,苏成,韩大建.高斯/非高斯混合随机风压场的模拟方法[J].振动与冲击,2012,31(10):111-117.
作者姓名:罗俊杰  苏成  韩大建
作者单位:1华南理工大学土木与交通学院土木工程系,2.亚热带建筑科学国家重点实验室,广州 510640
基金项目:国家自然科学基金项目(51078150);华南理工大学亚热带建筑科学国家重点实验室开放基金项目(2010KB30)
摘    要:针对作用于屋盖结构随机风压场样本的统计特性要求,基于零记忆非线性转化法的理论,给出了随机风压场的具体模拟过程。其中,解决了两个关键问题:(1)推导了服从对数正态分布和韦布尔分布的多点非高斯随机过程向量的标准化协方差,与相应高斯随机过程向量的标准化协方差的函数转化关系;(2)提出了分解谱密度函数修正法,解决利用谐波合成法模拟多点高斯随机过程向量时,功率谱密度函数矩阵在某些频率点出现负定的问题。经过具体算例表明,所提出的方法能生成合乎风洞实验数据统计特性要求的随机风压场样本。

关 键 词:随机风压场    非高斯随机过程向量    零记忆非线性转化法    谐波合成法  
收稿时间:2011-7-4
修稿时间:2011-10-19

Simulation methodology for stochastic wind pressure field composed of gaussian and non-gaussian regions
LUO Jun-jie,SU Cheng,HAN Da-jian.Simulation methodology for stochastic wind pressure field composed of gaussian and non-gaussian regions[J].Journal of Vibration and Shock,2012,31(10):111-117.
Authors:LUO Jun-jie  SU Cheng  HAN Da-jian
Affiliation:1. School of Civil Engineering and Transportation, 2. State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China
Abstract:Simulation of stochastic fluctuating wind pressure field acting on roofs should meet the requirements of identity in statistical and spectral characteristics.The zero memory nonlinearity(ZMNL) transformation method was presented to generate the time histories of stochastic wind pressure.A detailed simulation procedure was provided,and two crucial problems were addressed.First,the standard covariance function for transforming multivariate non-Gaussian stochastic process vector into the corresponding Gaussian one was derived for simulating the stochastic wind pressure process following the lognormal distribution and the Weibull distribution.Second,a new method was proposed to cope with the problem of negative definite matrices of spectral density function appearing at certain frequencies while generating the Gaussian stochastic process vector.An illustrating example was given.It is shown that the proposed method can generate stochastic wind pressure field samples with the same specified statistical and spectral natures of the data obtained by wind tunnel experiment.
Keywords:stochastic wind pressure field  non-Gaussian stochastic process vector  zero memory nonlinearity transformation method  wave superposition method
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