高层建筑风振分析中的模态组合问题  被引量:4

Mode combinations in wind-induced vibration analysis of tall buildings

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作  者:汤昱薇 谢霁明[1] 

机构地区:[1]浙江大学建筑工程学院,杭州310058

出  处:《振动与冲击》2017年第15期16-21,35,共7页Journal of Vibration and Shock

基  金:国家自然科学基金面上项目(51578505)

摘  要:大多数超高层建筑具有两个侧移振动固有频率非常接近的特点,使得风振响应分析中不能忽略其模态相关性。但目前普遍采用的SRSS(Square Root Squares)与CQC(Complete Quadratic Combination)模态组合方法存在理论上的不足,在实际工程应用中不能正确把握风致结构响应特点,对结构的抗风优化设计带来一定的困惑甚至误导。理论分析与数值计算证实了这两种方法的缺陷。SRSS方法完全忽略了模态相关性。CQC方法虽然在一定程度上考虑了模态相关性,但未能反映模态相关性中的相位关系,导致过于保守的计算结果。根据随机振动的基本理论,可建立基于风荷载互谱密度函数的模态组合新方法(称为"CS模态组合法")。这一方法能够完整考虑相邻模态之间的幅值相关性与相位相关性,原理清晰,计算简单,具有实际可操作性。与时域模拟结果的比较验证了这一新方法的可靠性与精确性。Most super-tall buildings have a feature of their first two sway modes ? natural frequencies being very close to each other,so in their wind-induced vibration analysis their mode correlations cannot be ignored. However, the current adopted mode combination methods of SRSS and CQC have shortcomings in theory and can? t handle correctly the features of wind-induced structural responses in actual applications to bring structural anti-wind optimization design a certain confusion even misleading. Here,the shortcomings of these two methods were verified through theoretical analysis and numerical computation. SRSS method fully neglected mode correlations. Although CQC method considered mode correlations to a certain extent,it couldn ? t reflect the phase relation in mode correlations to cause too conservative computation results. Based on the fundamental principles of random vibration, a new method of mode combinations named the CS method based on cross spectral density function was proposed here. It was shown that the new method can fully consider amplitude correlations and phase correlations between adjacent modes; its principle is clear, and it is easy to calculate. The reliability and correctness of this method were verified through comparing its results with those of simulation in time domain.

关 键 词:高层建筑抗风设计 结构风效应 模态相关性 模态组合法 CQC法 基于互谱密度函数的CS(Cross Spectrum)法 

分 类 号:TH212[机械工程—机械制造及自动化] TH213.3

 

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