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基于自回归模型的桥梁脉动风场模拟 被引量:4

Simulation of bridge fluctuating wind field based on Auto-Regressive model
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摘要 为了客观量化桥梁结构上各点处的脉动风速时程从而为准确计算风荷载效应提供前提保证,在考虑结构节点间的风速时程相关性的基础上,采用线性滤波技术亦即白噪声滤波法中的自回归模型(AR)模拟了某斜拉桥主梁上个别代表点处在任意200 s时长内的风速随机时程.该模型通过线性滤波器将白噪声随机序列输出为符合一定谱特征的平稳随机过程.分别采用Kaimal谱和Panofsky谱作为水平向风和竖向风的风速谱.结果表明:AR模型可以有效模拟脉动风速时程,合成的随机风速时程能够客观反映各代表点风速的时间相关性和空间相关性,其功率谱和目标功率谱也吻合较好. Objective quantification of fluctuating wind speed time series around the body of bridge structure offers guarantee for the accurate calculation of wind effect of the structure. Base on the correlativity of nodal wind speed time history, the Auto-Regressive(AR) model of the white noise filtration method was used to simulate the time history of fluctuating wind within any 200 seconds at representative points on the main beam of a cable-stayed bridge. Through the linear filter, a white noise random series with zero mean were transferred to be a stationary random process with specified spectral characteristics. Herein, the spectrum of Kaimal and the spectrum of Panofsky were used to simulate the horizontal and vertical wind spectrum respectively. The results of numerical wind speed time series show that AR model is efficient in simulating nodal wind speed time series which has time and space correlativity. The simulated power spectrum density is consistent with the target power spectrum density and correlation function is reasonable.
出处 《武汉工程大学学报》 CAS 2015年第3期25-28,共4页 Journal of Wuhan Institute of Technology
关键词 桥梁 脉动风场 自回归法 目标功率谱 相关函数 bridge stochastic wind field simulation Auto-Regressive model target power spectrum density correlation function
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