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A numerical comparison of random vibration theory and time histories based methods for equivalent-linear site response analyses
International Journal of Geo-Engineering ( IF 2.6 ) Pub Date : 2017-11-06 , DOI: 10.1186/s40703-017-0059-6
Margarita A. Chi-Miranda , Luis A. Montejo

Dynamic site response is usually implemented using an equivalent-linear approach through analyses based on time-histories or random vibration theory (RVT). In the RVT approach the input motion is characterized in the frequency domain by means of Fourier Amplitude Spectra (FAS) or power spectral densities so that the need for selecting/developing multiple suitable time-histories is avoided. Nevertheless, past studies have found that RVT may produce results that differ significantly from empirically determined site amplification functions and from the time history approach. This work is aimed to further understand the potential differences in the results from RVT and time-histories based approaches by performing a comprehensive numerical evaluation that takes into account the effect of the input intensity level, input spectral shape, site conditions, and the methodology used to produce the input FAS. The results obtained corroborate that RVT over-predictions occur mainly at the site fundamental frequencies and are larger for relatively soft soil deposits with significant impedance contrast at the soil/rock interface. However, in the soft site evaluated the magnitude of the over-prediction was rather insensitive to the increase in the inelastic demand, conversely, the over-prediction in the stiffer site increased as the site softened due to the rising inelastic demand.

中文翻译:

基于随机振动理论和时程的等效线性场地响应分析方法的数值比较

动态站点响应通常是通过基于时间历史或随机振动理论(RVT)的分析,使用等效线性方法来实现的。在RVT方法中,输入运动通过傅立叶振幅谱(FAS)或功率谱密度在频域中进行表征,从而避免了选择/建立多个合适的时间历史的需求。然而,过去的研究发现,RVT产生的结果可能与根据经验确定的位点扩增功能和时程分析方法明显不同。这项工作旨在通过进行全面的数值评估,进一步考虑RVT和基于时间历史的方法的结果之间的潜在差异,该评估考虑了输入强度水平,输入光谱形状,站点条件,以及用于产生输入FAS的方法。所获得的结果证实,RVT的高估主要发生在现场的基频上,对于相对较软的土壤沉积物,其在土壤/岩石界面处具有明显的阻抗对比,其预测值更大。但是,在评估的软站点中,过度预测的幅度对于无弹性需求的增长相当不敏感,相反,在较硬的站点中,由于无弹性需求的增加,随着站点变软,对过度预测的预测也有所增加。
更新日期:2017-11-06
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