Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens
文献类型：期刊论文
| 作者 | Wan, H. Y.2,3; Chen, G. F.1; Li, C. P.1; Qi, X. B.1,4; Zhang, G. P.2 |
| 刊名 | JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
 |
| 出版日期 | 2019-06-01 |
| 卷号 | 35期号:6页码:1137-1146 |
| 关键词 | Additive manufacturing Miniature specimen Fatigue Size effect Location-specific Data analysis |
| ISSN号 | 1005-0302 |
| DOI | 10.1016/j.jmst.2018.12.011 |
| 通讯作者 | Zhang, G. P.(gpzhang@imr.ac.cn) |
| 英文摘要 | This overview firstly introduces the state-of-the-art research progress in length scale-related fatigue performance of conventionally-fabricated metals evaluated by miniature specimens. Some key factors for size effects sensitive to microstructures including the specimen thickness, grain size and a ratio between them are highlighted to summarize some general rules for size effects. Then, ongoing research progress and new challenges in evaluating the fatigue performance of additive manufactured parts controlled by location-specific defects, microstructure heterogeneities as well as mechanical anisotropy using miniature specimen testing technique are discussed and addressed. Finally, a potential roadmap to establish a data-driven evaluation platform based on a large number of miniature specimen-based experiment data, theoretical computations and the 'big data' analysis with machine learning is proposed. It is expected that this overview would provide a novel strategy for the realistic evaluation and fast qualification of fatigue properties of additive manufactured parts we have been facing to. (C) 2019 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology. |
| 资助项目 | National Natural Science Foundation of China (NSFC)[51771207] ; National Natural Science Foundation of China (NSFC)[51571199] |
| WOS研究方向 | Materials Science ; Metallurgy & Metallurgical Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000464017000023 |
| 出版者 | JOURNAL MATER SCI TECHNOL |
| 资助机构 | National Natural Science Foundation of China (NSFC) |
| 源URL | [http://ir.imr.ac.cn/handle/321006/132825]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Zhang, G. P. |
| 作者单位 | 1.Siemens Ltd, Mat & Mfg Qualificat Grp, Corp Technol, Beijing 100102, Peoples R China 2.Chinese Acad Sci, Shenyang Natl Lab Mat Sci, Inst Met Res, 72 Wenhua Rd, Shenyang 110016, Liaoning, Peoples R China 3.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Liaoning, Peoples R China 4.Tsinghua Univ, State Key Lab Tribol, Beijing 100084, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wan, H. Y.,Chen, G. F.,Li, C. P.,et al. Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens[J]. JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,2019,35(6):1137-1146. |
| APA | Wan, H. Y.,Chen, G. F.,Li, C. P.,Qi, X. B.,&Zhang, G. P..(2019).Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens.JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,35(6),1137-1146. |
| MLA | Wan, H. Y.,et al."Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens".JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY 35.6(2019):1137-1146. |
入库方式： OAI收割
来源：金属研究所
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