Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach
文献类型：期刊论文
| 作者 | Yang, Wen-Ke1,3; Hu, Bing-Li1,3; Luo, Yan-Wen2; Song, Zhu-Man3; Zhang, Guang-Ping3 |
| 刊名 | INTERNATIONAL JOURNAL OF FATIGUE
 |
| 出版日期 | 2023-07-01 |
| 卷号 | 172页码:11 |
| 关键词 | Size effect Small specimen Fatigue life Machine learning |
| ISSN号 | 0142-1123 |
| DOI | 10.1016/j.ijfatigue.2023.107671 |
| 通讯作者 | Zhang, Guang-Ping(gpzhang@imr.ac.cn) |
| 英文摘要 | In this paper, both experimental and machine learning results show that the fatigue life of A588 steel specimens with different gauge lengths and widths varies more greatly compared with that of the specimens with different thicknesses as the gauge dimensions are reduced from 15 mm to 1.5 mm. The optimal machine learning algorithm is derived to predict the fatigue life of specimens with a thickness of 1 mm, and the predicted results are verified by the fatigue experiments. |
| 资助项目 | National Key R & D Program of China[2022YFB4601001] ; National Natural Science Foundation of China (NSFC)[52171128] ; Fundamental Research Project of Shenyang National Laboratory for Materials Science[L2019R18] |
| WOS研究方向 | Engineering ; Materials Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000981658400001 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Key R & D Program of China ; National Natural Science Foundation of China (NSFC) ; Fundamental Research Project of Shenyang National Laboratory for Materials Science |
| 源URL | [http://ir.imr.ac.cn/handle/321006/177707]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Zhang, Guang-Ping |
| 作者单位 | 1.Univ Sci & Technol China, Sch Mat Sci & Engn, 72 Wenhua Rd, Shenyang 110016, Peoples R China 2.Northeastern Univ, Sch Mat Sci & Engn, Key Lab Anisotropy & Texture Mat, Minist Educ, 3-11 Wenhua Rd, Shenyang 110819, Peoples R China 3.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, 72 Wenhua Rd, Shenyang 110016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Wen-Ke,Hu, Bing-Li,Luo, Yan-Wen,et al. Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach[J]. INTERNATIONAL JOURNAL OF FATIGUE,2023,172:11. |
| APA | Yang, Wen-Ke,Hu, Bing-Li,Luo, Yan-Wen,Song, Zhu-Man,&Zhang, Guang-Ping.(2023).Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach.INTERNATIONAL JOURNAL OF FATIGUE,172,11. |
| MLA | Yang, Wen-Ke,et al."Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach".INTERNATIONAL JOURNAL OF FATIGUE 172(2023):11. |
入库方式： OAI收割
来源：金属研究所
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