Process-induced defects and failure mechanisms in metal additive manufacturing: A mesoscale coupled damage and plasticity modeling and X-ray computed tomography approach

• The coupled damage-plasticity FE model accurately predicts ductile failure sites and mechanisms in metal AM components with defects. • Experimental validation of failure mechanisms is performed using temporal XCT imaging during tensile loading. • Damage initiates via intervoid necking from defect interaction, followed by intervoid sheeting and shearing during failure. • Surface defect shape, internal defect size, and spacing significantly influence damage initiation and structural response. This study aims to clarify the effect of process-induced defects on the damage behavior of metal additive manufactured (AM) components at the mesoscale using a numerical approach based on the coupled continuum damage mechanics (CDM) and plasticity model to provide a guideline for assessing the strength of metal AM components by considering defects’ features and their interaction. For this purpose, the finite element (FE) simulations, instantiated from the real microstructures captured by the initial X-ray computed tomography (XCT) imaging from the intact sample at several locations around the specimen, are deployed to reveal the activity of multiple failure mechanisms. FE simulations precisely identify the sites and the mechanism of ductile failure compared to experimentally observed sites of damage initiation and evolution based on XCT imaging in a temporal domain during tensile loading for the AM 316L stainless steel sample. It is found that the intervoid necking mechanism mainly controls the interaction of internal and surface defects and internal defects in close proximity. Then, the other intervoid sheeting and intervoid shearing mechanisms are active sequentially during the failure process. A systematic investigation is carried out to first reveal the defect-property relationships in damage progression and deformation patterns of these materials and then to define acceptance limits for internal and surface defects’ shape, size, distribution, and proximity to each other, identifying when the imperfections become defects. The results of this study can pave the road to overcoming the limitation of more widespread use of metal AM materials in different industries by providing a validated numerical approach to optimizing process parameters based on understanding the interaction between different process parameters, resultant internal and surface defects, and damage behavior of these materials under service loading.