Defect tolerant fatigue assessment of AM materials: Size effect and probabilistic prospects

Abstract

Despite the significant advantages such as rapid prototyping of complex structures, engineering application of Additive Manufacturing (AM) technique has been limited due to the weak fatigue performance and lacking of fatigue design rules of AM parts. Particularly, this application relies on the improvement of AM processing technique and integrity assessment of AM parts, the latter usually demands costly and time-consuming fatigue tests, especially for full-scale tests. Accordingly, the size effect and fatigue performance scatter in AM materials are explored on basis of defect data scanned by CT and experimental data in this work. Firstly, the distribution of maximum defects of AM materials under size effect is extrapolated via extreme value statistics theory; then a strength altering factor is proposed to characterize the effect of defects on fatigue scatter and size effect. From essential structure of fatigue curves, the relationship among defects, fatigue strength and fatigue curves are quantitatively analysed to extrapolate the probabilistic fatigue curves for AM materials; finally, three series of AlSi10Mg specimens with different processing parameters and gauge volumes prove the method effectiveness that the “location” and “scale” of fatigue curves is successfully predicted, and defect-tolerant assessment for AM parts is performed by employing the predicted fatigue curves.