Development of a quantitative strong motion prediction technique based on simple site effect evaluation methods with sufficient accuracy

开发基于简单场地效应评估方法且具有足够精度的定量强运动预测技术

基本信息

批准号：
11450211
负责人：
KAWASE Hiroshi
金额：
$ 4.16万
依托单位：
Kyushu University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2001
项目状态：
已结题

项目摘要

The purpose of the project is to propose a quantitative strong motion prediction technique based on simple site effect evaluation methods with sufficient accuracy in order to use these predicted strong motions as inputs to structures for aseismic design. The strong motion prediction technique based on a physical modeling of source, path, and site effects may have wide applicability so that it is suitable for a scenario type evaluation of strong ground motions. However, it requires many physical parameters, especially information on local site conditions, in order to produce quantitative synthetics. In this project we propose various methods that yield quantitative site effects.To this end we use strong motion data observed by K-NET in Kyushu and separate source, path, and site effects to generate statistical Green' s functions. Combining them with ordinary wave summation technique we show that we can successfully reproduce observed strong motions during the Hyogo-ken Nanbu earthquake, the Kagoshima-ken Hokuseibu earthquake, and the Tottori-ken Seibu earthquake. Then we use site amplification factors to invert S-wave velocity structures underneath by Genetic Algorithm. At the same time we obtain horizontal-to-Vertical spectral ratios (HVRs) for P-wave part, S-wave part, and Coda part and compare them with observed site amplification factors, theoretical S-wave amplification factors, and theoretical HVRs for Rayleigh wave. We found that observed HVRs show quite good correlation with observed site amplification factors. Based on these information we propose a highly accurate technique for strong ground motions that can be sued for aseismic design of structures.

该项目的目的是基于简单的站点效应评估方法提出一种定量的强运动预测技术，以便将这些预测的强动作作为对无性震动设计结构的输入。基于源，路径和站点效应的物理建模的强运动预测技术可能具有广泛的适用性，因此它适用于场景类型的强大地面运动评估。但是，它需要许多物理参数，尤其是有关本地现场条件的信息，以产生定量合成剂。在这个项目中，我们提出了各种产生定量位点效应的方法。为此，我们使用K-NET在Kyushu中观察到的强运动数据以及单独的来源，路径和位点效应来生成统计Green的功能。将它们与普通的波求和技术相结合，我们表明，我们可以在hyogo-ken nanbu地震，kagoshima-ken-ken-ken hokuseibu地震和托托托 - 肯尼·塞布（Tottori-ken Seibu）地震中成功再现观察到的强烈动作。然后，我们使用位点放大因子将遗传算法下面的S波速度结构倒转。同时，我们获得了P波部分，S波部分和CODA部分的水平与垂直光谱比（HVR），并将它们与观察到的位点放大因子，理论S波放大因子和理论HVR进行比较，用于瑞利波。我们发现观察到的HVR与观察到的位点扩增因子相关。基于这些信息，我们提出了一种高度准确的技术，以实现强大的地面运动，该技术可用于结构的无向设计。