Additive manufacturing (AM) process methods such as powder bed fusion (LPBF) of metal powder layers can produce layered material systems with designed microstructures, which may exhibit scatter in mechanical properties (e.g., lower yield and lower failure strain), corrosion due to porosity and print anomalies. This study shows the development of AM process simulation to predict As-built material characteristic and their scatter comparing with experimental test data. ICME (Integrated Computational Materials Engineering) was used to simulate yield, ultimate, strain, and reduction of the area of sample AM. The method was extended to predict oxidation and damage of as-built parts. The samples were fabricated horizontally and vertically in multiple and scatter directions to find the effect on the mechanical properties such as ultimate tensile strength (UTS) and yield strength (YS). The probabilistic sensitivities show that in order for the next-generation technology to improve the strength of 3D printed materials, they must control the void volume fraction (trapped gas) and orientation of voids. The studied 3D print modality processes: (a) LPBF of AlSi10Mg, and (b) Electron Beam (EBM) of Ti-6Al-4V materials are shown to be over 99.99% reliable. The statistics of 3D printed Ti-6Al-4V have been observed for room and high temperature (RT/HT). The ICME Material Characterization and Qualification (MCQ) software material model prediction capabilities were used to predict (a) Material Allowable, a variation in Stress Strain Curves Characteristic Points and Residual Stress due to air particle (void/defect) shape and size and orientation. The probabilistic simulation computes Cumulative Distribution Function (CDF) and probabilistic sensitivities for YS, UTS, and %Elongation as well as A and B basis allowable of the As-Built 3D printed material and; and (b) Fracture Control Plan fracture toughness determination, and fatigue crack growth vs. stress intensity.
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