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
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Abstract:
Defects have a major influence on the fatigue strength and fatigue behavior. In additive manufacturing in particular, a large number of small and larger defects occur in the material as a result of the process. In this paper, the defects contained in the material are investigated and evaluated using computer tomography images. In addition, methods for classifying spatial defect patterns are presented and applied to two distinctly different sets of manufacturing parameters. Based on the results, a model for simulating the number, size and position of the defects is derived. Finally, an outlook on the prediction of the fatigue strength of additively manufactured components by fracture mechanics is given.