Spatial Correlations in CyberShake Physics‐Based Ground‐Motion Simulations

Spatial Correlations in CyberShake Physics‐Based Ground‐Motion Simulations
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基于 Cyber​​Shake 物理的地面运动模拟中的空间相关性

DOI:
10.1785/0120190065
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发表时间:
2019
影响因子:
3
通讯作者:
J. Baker
J. Baker
中科院分区:
地球科学3区
文献类型:
--
作者:
Yilin Chen;J. Baker

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在研究分布式基础设施在地震中的性能时,强地面运动的空间变化具有显著的影响。目前,对未来地震的空间地面运动变化的预测模型是利用密集记录的地震的地面运动观测来校准的。尽管这一校准过程很有用,但它需要对相关性的平稳性和各向同性做出强有力的假设。本文报告了在CyberShake平台上使用基于物理的模拟进行类似的空间变异估计的结果。这个平台包含了来自南加州各地数十万次破裂实现的模拟地面运动,提供了一个合成地面运动目录,比我们希望从记录中获得的要丰富得多。这种丰富性允许显著放宽平稳性和各向同性假设,并提供了关于震源和路径异质性对地面运动幅度空间相关性的作用的新见解。结果表明,地质条件、震源效应和路径效应对空间相关性有显著影响。此外,这项工作作为地面运动模拟验证的一个新维度,因为估计的相关性可以与过去地震的结果进行比较。
When studying the performance of distributed infrastructure in earthquakes, spatial variations in strong ground motion have a significant impact. Currently, prediction models for spatial ground‐motion variations in future earthquakes are calibrated using ground‐motion observations from densely recorded earthquakes. Although useful, that calibration process requires strong assumptions about stationarity and isotropy of correlations. This article reports results from conducting analogous spatial variation estimation using physics‐based simulations from the CyberShake platform. This platform contains simulated ground motions from hundreds of thousands of rupture realizations, at locations throughout southern California, providing a synthetic ground‐motion catalog that is much richer than we could ever hope to achieve from recordings. That richness allows significant relaxation of stationarity and isotropy assumptions, and provides new insights regarding the role of source and path heterogeneity on the spatial correlation of ground‐motion amplitudes. The results suggest that geological conditions, source effects, and path effects have significant impacts on spatial correlations. In addition, this work serves as a new dimension of ground‐motion simulation validation, because the estimated correlations can be compared to results from past earthquakes.
SCEC 统一社区速度模型软件框架
DOI: 10.1785/0220170082
发表时间: 2017
影响因子: 3.3
作者:
Small, Patrick;Gill, David;Maechling, Philip J.;Taborda, Ricardo;Callaghan, Scott;Jordan, Thomas H.;Olsen, Kim B.;Ely, Geoffrey P.;Goulet, Christine
通讯作者: Goulet, Christine