Empirical Approaches for Non-linear Site Response: Results for the ESG6-Blind Test

Julie REGNIER, Pierre-Yves Bard,David Castro-Cruz, Boumédienne Derras,Etienne Bertrand

Research Square (Research Square)(2022)

引用 0|浏览2
暂无评分
摘要
Abstract We use two different purely empirical approaches to estimate the non-linear transfer function between a reference rock and a sedimentary site from recordings of weak ground motions and site-condition proxies. The modulus of the linear transfer function is first computed from weak motions and then modulated with a correction to consider non-linear soil behavior. Afterward, a time delay between the rock and site stations is considered using the weak motions delays and a minimum-phase assumption is used to derive a complex transfer function, which then allows to recover the prediction of acceleration time series a(t) at the sedimentary site. We apply these two approaches to the material provided for step 3 of the blind prediction exercise organized by the ESG6 Conference. The predictions were compared to the recordings that were provided after the blind test and to the overall predictions performed in the benchmark. Both methods underestimate the non-linear effects on the site response. For the foreshock, it contributes to improve the prediction compared to the other predictions. However, the prediction is less accurate for the mainshock. The prediction is also based on the average linear transfer function which, in case of large variability between weak motion transfer functions, may underestimate at some frequencies the amplification. Both of these purely empirical methods provide an honorable prediction of the Fourier spectra and acceleration time histories of the two target events, as the methods required only recordings of weak motions at the target and a referent sites and very simple description of the soil profile. The use of moderate motions to constrain the frequency shift prediction for the second method and the consideration of an alternative phase modification are possible ways to improvement.
更多
查看译文
关键词
response,non-linear
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要