IMR OpenIR
Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens
Wan, H. Y.; Chen, G. F.; Li, C. P.; Qi, X. B.; Zhang, G. P.
2019-06-01
Source PublicationJOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
ISSN1005-0302
Volume35Issue:6Pages:1137-1146
AbstractThis 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.
KeywordAdditive manufacturing Miniature specimen Fatigue Size effect Location-specific Data analysis
Indexed BySCI
Language英语
WOS IDWOS:000464017000023
PublisherJOURNAL MATER SCI TECHNOL
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/81065
Collection中国科学院金属研究所
Recommended Citation
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.
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