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System reliability analysis for seismic site classification based on sequential Gaussian co-simulation: A case study in Shiraz, Iran

机译:基于顺序高斯共模的地震位点分类系统可靠性分析 - 以西拉,伊朗为例

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摘要

Seismic site classification plays a significant role in the estimation of site response and is carried out using average shear wave velocity through the top 30 m (V-S30) soil layers. Meanwhile, at some sites with a number of boreholes, identification of the V-S30 acquired from different boreholes does not lead to the classification of the site into one single category, and this makes the seismic classification of the site troublesome. This paper proposes a practical approach for obtaining the reliability index of the seismic site classification when not all Vs30 calculated from the boreholes converge to that of a unique seismic class. For this purpose, the geostatistical method is combined with the system reliability approach. A real site with three boreholes, two of which fall into the 'D' and the third into the 'C' category based on the National Earthquake Hazards Reduction Program (NEHRP), is considered. The site is divided into 66 hypothetical soil columns. The shear wave velocity (Vs) is estimated in depths of each column using the Sequential Gaussian Co-Simulation (SGCS) method based on sampled data determined nearby. Ten thousand realizations of Vs with spatial distributions are generated via the SGCS method and are validated with the original data. In order for reliability analysis of the proposed classification approach, the reliability indices of the components are merged based on their corresponding correlation through the Sequential Compounding Method (SCM). The proposed method is proven to be consistent, fast, and the results are shown to be reliable.
机译:地震位点分类在现场响应的估计中起着重要作用,并且使用平均剪切波速度通过前30M(V-S30)土层进行。同时,在一些具有多个钻孔的某些网站上,从不同钻孔获取的V-S30的鉴定不会导致现场的分类成一个单一类别,这使得现场的地震分类进行了麻烦。本文提出了一种实用的方法,用于获得抗震位点分类的可靠性指数,当不是从钻孔计算的所有VS30都会收敛到独特的地震级别时。为此目的,地质统计方法与系统可靠性方法相结合。考虑了一个具有三个钻孔的真实景点,其中两个是基于国家地震危害减少计划(NEHRP)的“D”和第三个进入“C”类别的第三个网站。该网站分为66个假想的土壤柱。使用基于附近确定的采样数据的顺序高斯共模(SGC)方法,每个列的深度估计剪切波速度(VS)。通过SGCS方法生成一万与空间分布的VS实现,并通过原始数据验证。为了实现所提出的分类方法的可靠性分析,基于顺序复合方法(SCM)的相应相关性来合并组件的可靠性指标。拟议的方法被证明是一致的,快速的,结果显示可靠。

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