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Modeling and Prediction of Fatigue Properties of Additively Manufactured Metals

Modeling and Prediction of Fatigue Properties of Additively Manufactured Metals Additive manufacturing (AM) has emerged as an advanced technique for the fabrication of complex near-net shaped and light-weight metallic parts with acceptable mechanical performance. The strength of AM metals has been confirmed comparable or even superior to that of metals manufactured by conventional processes, but the fatigue performance is still a knotty issue that may hinder the substitution of currently used metallic components by AM counterparts when the cyclic loading and thus fatigue failure dominates. As essential complements to high-cost and time-consuming experimental fatigue tests of AM metals, models for fatigue performance prediction are highly desirable. In this review, different models for predicting the fatigue properties of AM metals are summarized in terms of fatigue life, fatigue limit and fatigue crack growth, with a focus on the incorporation of AM characteristics such as AM defect and processing parameters into the models. For predicting the fatigue life of AM metals, empirical models and theoretical models (including local characteristic model, continuum damage mechanics model and probabilistic method) are presented. In terms of fatigue limit, the introduced models involve the Kitagawa–Takahashi model, the Murakami model, the El-Haddad model, etc. For modeling the fatigue crack growth of AM metals, the summarized methodologies include the Paris equation, the Hartman-Schijve equation, the NASGRO equation, the small-crack growth model, and numerical methods. Most of these models for AM metals are similar to those for conventionally processed materials, but are modified and pay more attention to the AM characteristics. Finally, an outlook for possible directions of the modeling and prediction of fatigue properties of AM metals is provided. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mechanica Solida Sinica Springer Journals

Modeling and Prediction of Fatigue Properties of Additively Manufactured Metals

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Springer Journals
Copyright
Copyright © The Chinese Society of Theoretical and Applied Mechanics 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
0894-9166
eISSN
1860-2134
DOI
10.1007/s10338-023-00380-5
Publisher site
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Abstract

Additive manufacturing (AM) has emerged as an advanced technique for the fabrication of complex near-net shaped and light-weight metallic parts with acceptable mechanical performance. The strength of AM metals has been confirmed comparable or even superior to that of metals manufactured by conventional processes, but the fatigue performance is still a knotty issue that may hinder the substitution of currently used metallic components by AM counterparts when the cyclic loading and thus fatigue failure dominates. As essential complements to high-cost and time-consuming experimental fatigue tests of AM metals, models for fatigue performance prediction are highly desirable. In this review, different models for predicting the fatigue properties of AM metals are summarized in terms of fatigue life, fatigue limit and fatigue crack growth, with a focus on the incorporation of AM characteristics such as AM defect and processing parameters into the models. For predicting the fatigue life of AM metals, empirical models and theoretical models (including local characteristic model, continuum damage mechanics model and probabilistic method) are presented. In terms of fatigue limit, the introduced models involve the Kitagawa–Takahashi model, the Murakami model, the El-Haddad model, etc. For modeling the fatigue crack growth of AM metals, the summarized methodologies include the Paris equation, the Hartman-Schijve equation, the NASGRO equation, the small-crack growth model, and numerical methods. Most of these models for AM metals are similar to those for conventionally processed materials, but are modified and pay more attention to the AM characteristics. Finally, an outlook for possible directions of the modeling and prediction of fatigue properties of AM metals is provided.

Journal

Acta Mechanica Solida Sinica – Springer Journals

Published: Apr 1, 2023

Keywords: Additive manufacturing; Fatigue properties; Metals; Modeling and prediction; Microstructure

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  • An experimental study of residual stress and direction-dependence of fatigue crack growth behaviour in as-built and stress-relieved selective-laser-melted Ti6Al4V
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  • XFEM based analysis of fatigue crack growth in damaged wing-fuselage attachment lug
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    Ghandriz, R; Hart, K; Li, J
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    Duan, CH; Weng, ZW; Luo, XP; Han, XX; Zhao, MH
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    Yi, M; Chang, K; Liang, C; Liucheng, Z; Yangyiwei, Y; Yi, X
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    Ohmer, D; Yi, M; Gutfleisch, O; Xu, B
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  • Machine learning in additive manufacturing: state-of-the-art and perspectives
    Wang, C; Tan, XP; Tor, SB; Lim, CS
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    Bao, H; Wu, S; Wu, Z; Kang, G; Peng, X; Withers, PJ