Fatigue strength assessment of additively manufactured metallic structures considering bulk and surface layer characteristics

This paper extends a previously published fatigue strength estimation methodology for additively manufactured metallic bulk material by additionally accounting for effects of as-built surface layers. Interaction of intrinsic defects and surface texture convergently initiates fatigue failure. Holistic consideration of influencing factors significantly contributes to scientific fatigue assessment of structures fabricated by Laser-Powder Bed Fusion (L-PBF). Surface texture is highly dependent on the building parameters and performed post treatments. Three dimensional, optical topography scans form the basis of determining representative areal surface texture parameters. Areal notch valley depth Sv, alongside notch radii ρ evaluation, enables usage of a modified Peterson's approach. Effects of notch-like roughness features are quantified by a reduction factor k_s, as analogously published for bulk material imperfections k_b. Superimposition of ex- and intrinsic material characteristics is empirically assessed by an interaction exponent derived from experimental fatigue data. Macroscopic, tensile residual stresses acting as mean stresses are considered by Smith-Watson-Topper's approach. Unifying presented influencing factors derives a comprehensive model, conceived to estimate fatigue strength of additively manufactured metallic structures. Regardless of post processing condition, sound applicability of developed design approach is substantiated by averaging −7.1%, comparing estimated fatigue strength to experimental results.