Machine learning bridges microslips and slip avalanches of sheared granular gouges
文献类型：期刊论文
| 作者 | Ma, Gang4,5; Mei, Jiangzhou4,5; Gao, Ke3; Zhao, Jidong2; Zhou, Wei4,5; Wang, Di1,4,5 |
| 刊名 | EARTH AND PLANETARY SCIENCE LETTERS
 |
| 出版日期 | 2022-02-01 |
| 卷号 | 579页码:11 |
| 关键词 | granular fault gouge stick slip microslip stress drop spatial correlation |
| ISSN号 | 0012-821X |
| DOI | 10.1016/j.epsl.2022.117366 |
| 英文摘要 | Understanding the origin of stress drop of fault gouges may offer deeper insights into many geophysical processes such as earthquakes. Microslips of sheared granular gouges were found to be precursors of large slip events, but the documented relation between microslips and macroscopic stress drops remains largely qualitative. This study aims to quantitatively connect microslips to macroscopic stress fluctuations, including both stress recharges and stress drops. We examine the stick-slip behavior of a slowly sheared granular system using discrete element method simulations. The microslips are found to demonstrate significantly different statistical and spatial characteristics between the stick and slip stages. We further investigate the correlation between the macroscopic stress fluctuations and the features extracted from microslips based on a machine learning (ML) approach. The data-driven model that incorporates the information of the spatial distribution of microslips can robustly predict the magnitude of stress fluctuation. A further feature importance analysis confirms that the spatial patterns of microslips manifest key information governing the macroscopic stress fluctuations. The generalization of ML across granular gouges with different characteristics indicates the proposed model can be applicable to a broad range of granular materials. Our findings in this study may shed lights on the mechanisms governing earthquake nucleation, microslips, friction fluctuations, and their connection during the stick slip dynamics of earthquake cycles.(C) 2022 Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[51825905] ; National Natural Science Foundation of China[U1865204] ; National Natural Science Foundation of China[51779194] ; Science project of China Huaneng Group Co. Ltd[HNKJ18-H26] |
| WOS研究方向 | Geochemistry & Geophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000781933800011 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/36281]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Mei, Jiangzhou |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 2.Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China 3.Southern Univ Sci & Technol, Dept Earth & Space Sci, Shenzhen 518055, Guangdong, Peoples R China 4.Wuhan Univ, Minist Educ, Key Lab Rock Mech Hydraul Struct Engn, Wuhan 430072, Peoples R China 5.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ma, Gang,Mei, Jiangzhou,Gao, Ke,et al. Machine learning bridges microslips and slip avalanches of sheared granular gouges[J]. EARTH AND PLANETARY SCIENCE LETTERS,2022,579:11. |
| APA | Ma, Gang,Mei, Jiangzhou,Gao, Ke,Zhao, Jidong,Zhou, Wei,&Wang, Di.(2022).Machine learning bridges microslips and slip avalanches of sheared granular gouges.EARTH AND PLANETARY SCIENCE LETTERS,579,11. |
| MLA | Ma, Gang,et al."Machine learning bridges microslips and slip avalanches of sheared granular gouges".EARTH AND PLANETARY SCIENCE LETTERS 579(2022):11. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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