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针对最大可信地震灾害的确定性全情景分析。

Deterministic full-scenario analysis for maximum credible earthquake hazards.

作者信息

Wang Xiang-Chao, Wang Jin-Ting, Zhang Chu-Han

机构信息

Department of Hydraulic Engineering, Tsinghua University, 100084, Beijing, China.

出版信息

Nat Commun. 2023 Oct 19;14(1):6600. doi: 10.1038/s41467-023-42410-3.

DOI:10.1038/s41467-023-42410-3
PMID:37852956
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10584816/
Abstract

Great earthquakes are one of the major threats to modern society due to their great destructive power and unpredictability. The maximum credible earthquake (MCE) for a specific fault, i.e., the largest magnitude earthquake that may occur there, has numerous potential scenarios with different source processes, making the future seismic hazard highly uncertain. We propose a full-scenario analysis method to evaluate the MCE hazards with deterministic broadband simulations of numerous scenarios. The full-scenario analysis is achieved by considering all uncertainties of potential future earthquakes with sufficient scenarios. Here we show an application of this method in the seismic hazard analysis for the Xiluodu dam in China by simulating 22,000,000 MCE scenarios in 0-10 Hz. The proposed method can provide arbitrary intensity measures, ground-motion time series, and spatial ground-motion fields for all hazard levels, which enables more realistic and accurate MCE hazard evaluations, and thus has great application potential in earthquake engineering.

摘要

由于大地震具有巨大的破坏力和不可预测性,它们是现代社会面临的主要威胁之一。特定断层的最大可信地震(MCE),即可能在那里发生的最大震级地震,有许多不同震源过程的潜在情况,使得未来地震灾害具有高度不确定性。我们提出一种全场景分析方法,通过对众多场景进行确定性宽带模拟来评估MCE灾害。全场景分析是通过考虑潜在未来地震的所有不确定性并设置足够多的场景来实现的。在此,我们通过在0 - 10赫兹范围内模拟2200万个MCE场景,展示了该方法在中国溪洛渡大坝地震灾害分析中的应用。所提出的方法可以为所有灾害水平提供任意强度指标、地面运动时间序列和空间地面运动场,这使得MCE灾害评估更加现实和准确,因此在地震工程中具有巨大的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/57e8dad8dd23/41467_2023_42410_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/ee9727e5155c/41467_2023_42410_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/70bfe4a83683/41467_2023_42410_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/88255bf99b03/41467_2023_42410_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/7ce78d30507e/41467_2023_42410_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/46234f77ed30/41467_2023_42410_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/9e972c86e6db/41467_2023_42410_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/57e8dad8dd23/41467_2023_42410_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/ee9727e5155c/41467_2023_42410_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/70bfe4a83683/41467_2023_42410_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/88255bf99b03/41467_2023_42410_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/7ce78d30507e/41467_2023_42410_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/46234f77ed30/41467_2023_42410_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/9e972c86e6db/41467_2023_42410_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9a/10584816/57e8dad8dd23/41467_2023_42410_Fig7_HTML.jpg

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本文引用的文献

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