GSTDTAP  > 地球科学
DOI10.1038/s41561-018-0272-8
Similarity of fast and slow earthquakes illuminated by machine learning
Hulbert, Claudia1; Rouet-Leduc, Bertrand1; Johnson, Paul A.1; Ren, Christopher X.1; Riviere, Jacques2; Bolton, David C.3; Marone, Chris3
2019
发表期刊NATURE GEOSCIENCE
ISSN1752-0894
EISSN1752-0908
出版年2019
卷号12期号:1页码:69-+
文章类型Article
语种英语
国家USA
英文摘要

Tectonic faults fail in a spectrum of modes, ranging from earthquakes to slow slip events. The physics of fast earthquakes are well described by stick-slip friction and elastodynamic rupture; however, slow earthquakes are poorly understood. Key questions remain about how ruptures propagate quasi-dynamically, whether they obey different scaling laws from ordinary earthquakes and whether a single fault can host multiple slip modes. We report on laboratory earthquakes and show that both slow and fast slip modes are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Using machine learning, we find that acoustic emissions generated during shear of quartz fault gouge under normal stress of 1-10 MPa predict the timing and duration of laboratory earthquakes. Laboratory slow earthquakes reach peak slip velocities of the order of 1 x 10(-4) m s(-1) and do not radiate high-frequency elastic energy, consistent with tectonic slow slip. Acoustic signals generated in the early stages of impending fast laboratory earthquakes are systematically larger than those for slow slip events. Here, we show that a broad range of stick-slip and creep-slip modes of failure can be predicted and share common mechanisms, which suggests that catastrophic earthquake failure may be preceded by an organized, potentially forecastable, set of processes.


领域地球科学 ; 气候变化
收录类别SCI-E
WOS记录号WOS:000454010200013
WOS关键词STICK-SLIP ; FRICTION ; SPECTRUM ; VELOCITY ; FAILURE
WOS类目Geosciences, Multidisciplinary
WOS研究方向Geology
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/34962
专题地球科学
气候变化
作者单位1.Los Alamos Natl Lab, Geophys Grp, Los Alamos, NM 87545 USA;
2.Penn State Univ, Dept Engn Sci & Mech, 227 Hammond Bldg, University Pk, PA 16802 USA;
3.Penn State Univ, Dept Geosci, University Pk, PA 16802 USA
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GB/T 7714
Hulbert, Claudia,Rouet-Leduc, Bertrand,Johnson, Paul A.,et al. Similarity of fast and slow earthquakes illuminated by machine learning[J]. NATURE GEOSCIENCE,2019,12(1):69-+.
APA Hulbert, Claudia.,Rouet-Leduc, Bertrand.,Johnson, Paul A..,Ren, Christopher X..,Riviere, Jacques.,...&Marone, Chris.(2019).Similarity of fast and slow earthquakes illuminated by machine learning.NATURE GEOSCIENCE,12(1),69-+.
MLA Hulbert, Claudia,et al."Similarity of fast and slow earthquakes illuminated by machine learning".NATURE GEOSCIENCE 12.1(2019):69-+.
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