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Single-Station Sigma for the Iranian Strong Motion Stations

机译:用于伊朗强大运动站的单站Sigma

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AbstractIn development of ground motion prediction equations (GMPEs), the residuals are assumed to have a log-normal distribution with a zero mean and a standard deviation, designated as sigma. Sigma has significant effect on evaluation of seismic hazard for designing important infrastructures such as nuclear power plants and dams. Both aleatory and epistemic uncertainties are involved in the sigma parameter. However, ground-motion observations over long time periods are not available at specific sites and the GMPEs have been derived using observed data from multiple sites for a small number of well-recorded earthquakes. Therefore, sigma is dominantly related to the statistics of the spatial variability of ground motion instead of temporal variability at a single point (ergodic assumption). The main purpose of this study is to reduce the variability of the residuals so as to handle it as epistemic uncertainty. In this regard, it is tried to partially apply the non-ergodic assumption by removing repeatable site effects from total variability of six GMPEs driven from the local, Europe–Middle East and worldwide data. For this purpose, we used 1837 acceleration time histories from 374 shallow earthquakes with moment magnitudes ranging fromMw4.0 to 7.3 recorded at 370 stations with at least two recordings per station. According to estimated single-station sigma for the Iranian strong motion stations, the ratio of event-corrected single-station standard deviation (Φss) to within-event standard deviation (Φ) is about 0.75. In other words, removing the ergodic assumption on site response resulted in 25% reduction of the within-event standard deviation that reduced the total standard deviation by about 15%.]]>
机译:CDATA [<标题>抽象 <帕拉ID =“PAR1”>在研发地面运动预测方程式(GMPE)中,假设残差具有零平均值和标准的日志正态分布偏差,指定为sigma。西格玛对设计核电站和水坝等重要基础设施的地震危害进行了重大影响。杀菌和认知的不确定性都参与了Sigma参数。然而,在特定网站上没有长时间的地面运动观察不可用,并且使用来自多个站点的观察到的数据来导出GMPE以获得少量纪录的地震。因此,Sigma与地面运动的空间变异性的统计学主导地统计,而不是单点(ergodic假设)而不是时间变异性。本研究的主要目的是降低残留物的可变性,以便将其处理为认知不确定性。在这方面,试图通过从来自当地,欧洲中东和全球数据的六种GMPES的总可变性中除去可重复的现场效应来部分适用非遍历假设。为此目的,我们使用了来自374个浅地震的加速时间历史,随着瞬间=“斜体”> M <下标> W 4.0至7.3,至少在370站中记录每个仓库的两个录音。根据估计的单站Sigma用于伊朗强运动站,事件校正的单站标准偏差的比率(<重点类型=“斜体”>φ <下标> SS ) -Event标准偏差(<重点类型=“斜体”>φ)约为0.75。换句话说,去除现场响应的ergodic假设导致在事后标准偏差减少25%,降低了总标准偏差约15%。]>

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