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首页> 外文期刊>Seismological Research Letters >Sigma: Issues, Insights, and Challenges
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Sigma: Issues, Insights, and Challenges

机译：Sigma：问题，见解和挑战

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The prediction of ground-motion levels at a site is one of the key elements of seismic hazard assessment. This prediction is commonly achieved using equations derived through regression analysis on selected sets of instrumentally recorded strong-motion data, hereafter referred to as empirical ground-motion prediction equations (GMPE). Reviews and compilations of equations published to date have been presented by, among others, Campbell (1985), Joyner and Boore (1988), and Douglas (2003, 2004, 2006). These equations relate a predicted variable (Zpred) characterizing the level of shaking, most commonly the logarithm of a peak ground-motion parameter (e.g., PGA, PGV) or response spectral ordinate (SA, PSA, PSV, SD), to a set of explanatory variables {Xk}=X1, X2,... describing the earthquake source, wave propagation path, and site conditions: nnn (1) nThe explanatory variables {Xk} usually include the earthquake magnitude, M; a factor describing the style-of-faulting of the causative event; a measure of the source-to-site distance, R; and a parameter characterizing the site class. Recent equations sometimes also include additional terms to characterize the location of the site with respect to the rupture plane (hanging-wall factor), to distinguish between ground motions from surface-faulting events and buried ruptures, or to include the effects of sediment depth in the case of deep alluvial basins. Other factors that are known to influence the motion (and many others that are not yet known) are not included in the equation because the information is not readily available or not predictable in advance. For instance, anisotropy effects resulting from the dynamic propagation of rupture (including directivity effects) are currently not included in predictions, although back-analyses of ground motions from past earthquakes have shown that such effects may have a strong influence on the spatial distribution of ground motions.
机译：预测场地的地面运动水平是地震灾害评估的关键要素之一。通常使用通过对选定的仪器记录的强运动数据集进行回归分析得出的方程式实现此预测，此后称为经验地面运动预测方程式（GMPE）。迄今为止发表的方程式的评论和汇编由坎贝尔（1985），乔伊纳和布尔（1988）和道格拉斯（2003、2004、2006）提出。这些方程将一个预测变量（Zpred）关联到一组，该预测变量表征了抖动的水平，最常见的是峰值地面运动参数（例如PGA，PGV）或响应光谱纵坐标（SA，PSA，PSV，SD）的对数解释变量{Xk} = X1，X2，...描述地震源，波传播路径和场地条件：nnn（1）n解释变量{Xk}通常包括地震震级M；描述导致事件的错误样式的因素；源到站点距离R的度量；以及表征网站类别的参数。最近的方程式有时还包括附加项，以表征该位置相对于破裂面的位置（悬挂壁因子），区分地面破坏事件与地表破裂事件与地下破裂之间的差异，或包括沉积物深度对地震破坏的影响。深冲积盆地的情况。已知影响运动的其他因素（以及许多其他未知因素）不包含在公式中，因为信息不容易获得或无法预先预测。例如，尽管过去地震对地震动的反分析表明，这种影响可能对地面的空间分布有很大的影响，但目前尚不包括由破裂的动态传播引起的各向异性效应（包括方向性效应）。动作。

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