PSI - Issue 75

S.S. Penkulinti et al. / Procedia Structural Integrity 75 (2025) 1–9 Author name / Structural Integrity Procedia (2025)

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Nomenclature , Crossland criterion parameters Anisotropic fatigue strength factor Poisson’s ratio , , Euler angles involved in rotation matrix R ′ Local stress field associated to macroscopic loading ′ Macroscopic applied stress tensor ′ Rotated macroscopic stress tensor Σ Macroscopic fatigue strength determined numerically Σ ℎ, Maximum hydrostatic stress over a loading period Ψ Defect sphericity 0 El-Haddad parameter Non-local parameter – radius of the sphere over which stresses are averaged to compute the FIP E Young’s modulus 3 Defect Feret diameter FIP Fatigue Indicator Parameter 2, Amplitude of the second invariant of deviatoric stress tensor R Rotation matrix used to rotate the macroscopic stress tensor Deviatoric stress tensor Local stress field associated to macroscopic elementary loading k-th elementary macroscopic stress tensor involved in the decomposition of ′ 1. Introduction One limitation of Laser Powder Bed Fusion (L-PBF) technology is the presence of process-induced defects such as gas pores or lack-of-fusion (LoF) defects, which have detrimental impact on the fatigue behavior. It is today well known that in the presence of defects the fatigue resistance is sensitive to the size , position (surface, sub-surface or internal) and shape of the defects (Murakami 2002). This is also true for additively-manufactured alloys where, in the High Cycle Fatigue (HCF) regime, the critical fatigue cracks initiate at one of the largest defects near the surface when uniaxial loading is applied (Bonneric et al. 2025). Additionally, the presence of LoF defects can cause anisotropy in the fatigue behavior. Several works have evidenced that horizontally built samples ( i.e. perpendicular to the build direction (BD)) have higher fatigue strength than vertically built samples (Sun et al. 2020, Wu et al. 2021). This result is usually attributed to the fact that the area of Lof defects projected on a plane normal to the building direction is larger for vertical samples than for horizontal ones, making the defect size parameter √ (see Murakami 2002) higher in vertical samples. However, the microstructure might also contribute to the fatigue anisotropy that is commonly observed when testing different build orientations under uniaxial loading (Nezhadfar et al. 2021). While some studies exist on the specific impact of the defect orientation with respect to the loading direction on fatigue (see for example the work of Marciniak et al. (2023) considering artificial elliptical defects in C45 steel), none of them addresses the LoF defects and their specific morphology. The aim of this numerical study is to assess the specific impact of defects on the fatigue strength anisotropy for different loading conditions (tension, torsion and tension-torsion). To do so, real defect geometries from X-ray tomography observations have been explicitly integrated in Finite Element (FE) simulations. The application of a multiaxial fatigue criterion as a post-processing of the simulations allowed to assess the fatigue resistance for each simulated configuration (defect / loading type / orientation), and to discuss the impacts of defects and loading types on the anisotropy of the fatigue resistance.