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DOI | 10.1038/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
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ISSN | 1752-0894 |
EISSN | 1752-0908 |
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 |
推荐引用方式 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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