| Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach | |
| Yang, Wen-Ke1,2; Hu, Bing-Li1,2; Luo, Yan-Wen3; Song, Zhu-Man1; Zhang, Guang-Ping1 | |
| Corresponding Author | Zhang, Guang-Ping(gpzhang@imr.ac.cn) |
| 2023-07-01 | |
| Source Publication | INTERNATIONAL JOURNAL OF FATIGUE
 |
| ISSN | 0142-1123 |
| Volume | 172Pages:11 |
| Abstract | 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. |
| Keyword | Size effect Small specimen Fatigue life Machine learning |
| Funding Organization | National Key R & D Program of China ; National Natural Science Foundation of China (NSFC) ; Fundamental Research Project of Shenyang National Laboratory for Materials Science |
| DOI | 10.1016/j.ijfatigue.2023.107671 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 Research Area | Engineering ; Materials Science |
| WOS Subject | Engineering, Mechanical ; Materials Science, Multidisciplinary |
| WOS ID | WOS:000981658400001 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/177708 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Zhang, Guang-Ping |
| Affiliation | 1.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, 72 Wenhua Rd, Shenyang 110016, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, 72 Wenhua Rd, Shenyang 110016, Peoples R China 3.Northeastern Univ, Sch Mat Sci & Engn, Key Lab Anisotropy & Texture Mat, Minist Educ, 3-11 Wenhua Rd, Shenyang 110819, Peoples R China |
| Recommended Citation 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. |
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