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.