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基于实测的脉动风随机幅值谱模型
引用本文:淡丹辉,王向杰,闫兴非,夏烨.基于实测的脉动风随机幅值谱模型[J].同济大学学报(自然科学版),2018,46(4):0452-0457.
作者姓名:淡丹辉  王向杰  闫兴非  夏烨
作者单位:同济大学土木工程学院;上海城市建设设计研究总院
基金项目:2014年国家高技术研究发展计划(863)(编号:2014AA110402),中央高校基本科研业务费专项自尽和国家气象局气象行业科研专项经费(201306102),上海城市建设设计研究总院“桥梁安全运行大数据采集技术及结构监测系统研究”
摘    要:风荷载建模问题是结构抗风设计和安全评估的关键,已有规范给出的脉动风功率谱密度函数很难全面反应原始随机过程的概率信息,为此,根据量纲分析给出脉动风幅值谱的一般化表达形式,并结合某桥的实测风速数据的谱估计,给出Davenport形式的随机幅值谱模型,并采用PSO(partical swarm optimization)算法估计该模型的参数,最后给出该模型的3种具体使用方式.与实测风幅值谱的统计特性进行对比,表明提出的随机脉动风幅值谱模型能真实描述当地风场概率统计特性,可以提高该桥所在地区风荷载的建模精度.

关 键 词:脉动风  幅值谱  Davenport随机幅值谱模型  PSO(particle  swarm  optimization)算法  概率统计特性
收稿时间:2017/4/11 0:00:00
修稿时间:2018/3/7 0:00:00

Modeling of Fluctuating Wind Velocity Amplitude Spectrum Based on Onsite Monitoring Data
DAN Danhui,WANG Xiangjie,YAN Xingfei and XIA Ye.Modeling of Fluctuating Wind Velocity Amplitude Spectrum Based on Onsite Monitoring Data[J].Journal of Tongji University(Natural Science),2018,46(4):0452-0457.
Authors:DAN Danhui  WANG Xiangjie  YAN Xingfei and XIA Ye
Institution:College of Civil Engineering, Tongji University, Shanghai 200092, China,College of Civil Engineering, Tongji University, Shanghai 200092, China,Shanghai Urban Construction Design Research Institute, Shanghai 200125, China and College of Civil Engineering, Tongji University, Shanghai 200092, China
Abstract:The modeling of wind load is essential for the anti wind design and safety assessment of structures. The fluctuating wind power spectra in given specifications were not capable of fully expressing the probability information of the fluctuating wind velocity, which was seen as stochastic process. The general empirical expression of fluctuating wind amplitude spectrum was introduced by dimensional analysis and its specific Davenport form was proposed according to field measured wind velocity data. The parameters of Davenport empirical fluctuating wind amplitude spectrum were estimated by using the PSO(partical swarm optimization) algorithm and three specific applications of this model were put forward when different known conditions are met. Compared with the measured data, the stochastic Davenport empirical amplitude spectrum model proposed in this paper could accurately describe the statistical properties of the local wind field, thus improve the modeling accuracy of the filed wind load.
Keywords:
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