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首页> 外文期刊>Journal of structural engineering >Evolutionary Spectra-Based Time-Varying Coherence Function and Application in Structural Response Analysis to Downburst Winds
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Evolutionary Spectra-Based Time-Varying Coherence Function and Application in Structural Response Analysis to Downburst Winds

机译:基于演化谱的时变相干函数及其在下暴风结构响应分析中的应用

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Priestley's oscillatory process theory is widely employed to model nonstationary excitation. However, the underlying coherence function of this theory can only be time invariant. To take into account the time-varying coherence function, the Sigma-oscillatory process theory and Wold-Cramer decomposition model have been introduced in literature. Due to its straightforwardness, the Wold-Cramer decomposition model is used in this study. Based on the Wold-Cramer decomposition model of nonstationary wind excitation, the alongwind response analysis framework of tall buildings to nonstationary winds is presented. The time-varying coherence function models of two downburst events are developed using the measured downburst data. The influence of time-varying coherence of nonstationary winds on the alongwind tall building response is investigated. Numerical examples show that the time-varying coherence function may lead to larger structural response compared with the corresponding time-invariant coherence function model. Considering the large variation of nonstationary downburst winds, the observation drawn from this study should be further evaluated using more measurement wind data. It can be expected that the time-varying coherence function may play an important role in better modeling the nonstationary winds and their load effects on structures.
机译:Priestley的振荡过程理论被广泛用于对非平稳激发进行建模。但是,该理论的基本相干函数只能是时间不变的。为了考虑时变相干函数,文献中引入了Sigma振荡过程理论和Wold-Cramer分解模型。由于其直接性,本研究使用了Wold-Cramer分解模型。基于非平稳风激励的Wold-Cramer分解模型,提出了高层建筑对非平稳风的顺风响应分析框架。利用测得的暴发数据建立了两个暴发事件的时变相干函数模型。研究了非平稳风的时变相干对顺风高层建筑物响应的影响。数值算例表明,时变相干函数与相应的时不变相干函数模型相比,可能导致更大的结构响应。考虑到非平稳下行突发风的变化较大,应使用更多的测量风数据进一步评估本研究得出的观测结果。可以预期,时变相干函数可能在更好地模拟非平稳风及其对结构的载荷影响中起重要作用。

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