Fatigue damage process of additively manufactured 316 L steel using X-ray computed tomography imaging

Abstract

Failure under cyclic loading in the presence of manufacturing defects is a substantial risk for additively manufactured (AM) metal components. This study aims to clarify the correlation between process-related defects (internal pores and surface roughness) and fatigue performance of AM 316 L stainless steel. X-ray computed tomography (XCT) has been employed to characterize process-related defects’ features and their synergistic interaction to define the effective defect size parameter areaeff, leading to identifying potential sites for fatigue crack initiation before testing. Then, the defects’ growth is monitored using XCT imaging under cyclic loading to provide further insight into the fatigue damage process of AM stainless steels. A novel characterization framework is developed for monitoring the fatigue crack initiation and propagation based on measuring the variation in specimen surface topography in the axial and circumferential directions. Moreover, a fracture-mechanics based analytical framework is developed for the fatigue life prediction of AM components while the progression of the aspect ratio of semi-elliptical surface crack during its growth is considered. It is found that a significant fraction of the fatigue life is consumed for crack initiation and the damage progression dominantly occurs at the predicted maximum equivalent defect size, which is detected before fatigue testing. Therefore, the critical equivalent defect size can be considered as an initial short crack in the critical defect-based fatigue crack growth model for AM components. The proposed single crack growth model, by applying an appropriate characterization approach to detect the initial semi-elliptic surface short crack based on defects’ features and their interaction, demonstrates promise to be suited as an engineering approach for fatigue life prediction of AM components. This model shows a good correlation between XCT imaging and the predicted crack initiation and propagation phases for the tested AM 316 L stainless steel samples.