Stress intensity factor – Life: Improving high cycle fatigue understanding of laser powder bed fusion 316L stainless steel by combining effects of stress, defect size, and defect shape

• Near surface keyhole pores had the combined effect of a large surface notch. • Application of defect specific stress intensity factor improves fatigue predictions. • Surface valley depth pre-failure was consistent with post failure measurements. • Defect depth alone was not a predictor of fatigue life. • Accurate characterization of surface notches is needed for fatigue life prediction. As-built components made using laser powder bed fusion have a variety of both surface connected and internal defects, which reduce fatigue life. This work manufactures 316L stainless steel fatigue bars with two outer contour parameter sets, one which produces surface notch defects, and one that produces near surface keyhole porosity. Two fully reversed (R = −1) high cycle fatigue testing methods: axial and four-point rotating bending (RBF), produced different stress distributions in the gauge section: axial fatigue produced a uniform distribution while RBF produced a variable distribution with zero stress in the center and maximum stress on the surface. The parameter set with near surface keyhole porosity was found to have lower fatigue life than the parameter set that produced surface notches across test methods at stresses above 125 MPa. Stress intensity factors of the failure initiating defects were characterized by fractography and the relationship between stress intensity factor and cycles to failure was analyzed. The stress intensity-fatigue life relationship was found to be consistent across three of the four combinations of defect types and test methods. The deepest valley measured with optical profilometry (Sv) was a good direct measurement of fractography measured notch depth but unrelated to notch area. Another method of estimating defect area based on fitting a half ellipse showed good correlation with the true measured area though, the two were not identical. An improved understanding of appropriate defect measurement will lead to surface roughness measurements that accurately characterize notch area and improve fatigue predictions.