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Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning approach
Luo, Y. W.1; Zhang, B.1; Feng, X.1; Song, Z. M.2; Qi, X. B.3; Li, C. P.3; Chen, G. F.3; Zhang, G. P.2
Corresponding AuthorZhang, B.(zhangb@atm.neu.edu.cn) ; Zhang, G. P.(gpzhang@imr.ac.cn)
2021-01-20
Source PublicationMATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
ISSN0921-5093
Volume802Pages:11
AbstractFatigue life scattering and prediction of Inconel 718 fabricated by selective laser melting were investigated using miniature specimen tests combined with statistical method and machine learning algorithms. The relationship between pore features and fatigue life of the selective laser melting-fabricated specimens was analyzed statistically. The results show that the increase in the size and/or the number of the pores in the specimens, and/or the decrease in the distance from a pore center to the specimen surface degraded the fatigue life. The machine learning and statistical analysis results reveal that the fatigue life are most closely related to the location of the pores compared with the size and the number of pores in the specimens. The finding may provide a potential way to get high-throughput statistical data helping in evaluating defect-dominated scattering and prediction of fatigue life of additive manufactured metallic parts using miniature specimen testing assisted by the machine learning approach.
KeywordSelective laser melting Pore feature Fatigue life Statistical analysis Machine learning
Funding OrganizationNational Natural Science Foundation of China (NSFC) ; project of 'Manufacturing the swirl nozzles of the high pressure turbine by selective laser melting' ; Fundamental Research Project of Shenyang National Laboratory for Materials Science
DOI10.1016/j.msea.2020.140693
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[51771207] ; National Natural Science Foundation of China (NSFC)[51671050] ; National Natural Science Foundation of China (NSFC)[51971060] ; project of 'Manufacturing the swirl nozzles of the high pressure turbine by selective laser melting' ; Fundamental Research Project of Shenyang National Laboratory for Materials Science[L2019R18]
WOS Research AreaScience & Technology - Other Topics ; Materials Science ; Metallurgy & Metallurgical Engineering
WOS SubjectNanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS IDWOS:000613412700003
PublisherELSEVIER SCIENCE SA
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/159127
Collection中国科学院金属研究所
Corresponding AuthorZhang, B.; Zhang, G. P.
Affiliation1.Northeastern Univ, Sch Mat Sci & Engn, Minist Educ, Key Lab Anisotropy & Texture Mat, 3-11 Wenhua Rd, Shenyang 110819, Peoples R China
2.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, 72 Wenhua Rd, Shenyang 110016, Peoples R China
3.Corp Technol Siemens Ltd China, Mat & Mfg Qualificat Grp, Beijing 100102, Peoples R China
Recommended Citation
GB/T 7714
Luo, Y. W.,Zhang, B.,Feng, X.,et al. Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning approach[J]. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING,2021,802:11.
APA Luo, Y. W..,Zhang, B..,Feng, X..,Song, Z. M..,Qi, X. B..,...&Zhang, G. P..(2021).Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning approach.MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING,802,11.
MLA Luo, Y. W.,et al."Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning approach".MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 802(2021):11.
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