| 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 Author | Zhang, B.(zhangb@atm.neu.edu.cn) ; Zhang, G. P.(gpzhang@imr.ac.cn) |
| 2021-01-20 | |
| Source Publication | MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
 |
| ISSN | 0921-5093 |
| Volume | 802Pages:11 |
| Abstract | Fatigue 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. |
| Keyword | Selective laser melting Pore feature Fatigue life Statistical analysis Machine learning |
| Funding Organization | National 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 |
| DOI | 10.1016/j.msea.2020.140693 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National 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 Area | Science & Technology - Other Topics ; Materials Science ; Metallurgy & Metallurgical Engineering |
| WOS Subject | Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering |
| WOS ID | WOS:000613412700003 |
| Publisher | ELSEVIER SCIENCE SA |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/159127 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Zhang, B.; Zhang, G. P. |
| Affiliation | 1.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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