Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach

doi:10.1016/j.ijfatigue.2023.107671

IMR OpenIR

	Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach
	Yang, Wen-Ke 1,2; Hu, Bing-Li 1,2; Luo, Yan-Wen 3; Song, Zhu-Man 1; Zhang, Guang-Ping 1
通讯作者	Zhang, Guang-Ping(gpzhang@imr.ac.cn)
	2023-07-01
发表期刊	INTERNATIONAL JOURNAL OF FATIGUE
ISSN	0142-1123
卷号	172 页码:11
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.
关键词	Size effect Small specimen Fatigue life Machine learning
资助者	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
收录类别	SCI
语种	英语
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
WOS类目	Engineering, Mechanical ; Materials Science, Multidisciplinary
WOS记录号	WOS:000981658400001
出版者	ELSEVIER SCI LTD
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/177708
专题	中国科学院金属研究所
通讯作者	Zhang, Guang-Ping
作者单位	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
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.