Simulation-Based Uncertainty Quantification for Additively Manufactured Cellular Structures

Additive manufacturing (AM) processes are capable of producing complex shapes which introduce significant computational difficulties related to material characterization and reliability evaluation. Certification of AM-fabricated components for mission-critical roles has been challenging due to the complexity in modeling and variability in performance of tested parts. This paper discusses how multiscale modeling and simulation can be used in characterizing AM materials. Specifically, polynomial chaos expansion is employed to handle input uncertainties and an efficient upscaling method is applied to match probabilistic performances in fine- and coarse-scale models. The procedure is integrated into the multiscale modeling of AM-fabricated parts. The presented example clearly demonstrates how the upscaling procedure can identify homogenized properties under the consideration of uncertain inputs.