Strength and fatigue behavior assessment of the SCALMALLOY^® material to functionally adapt the performance of L-PBF components within CAE simulations

Thanks to Laser Powder Bed Fusion (L-PBF) technology, SCALMALLOY^® was the first aluminum powder material designed for Additive Manufacturing (AM), achieving a fine microstructure with high performance that is comparable to other cast materials. Despite the mechanical properties that can be achieved, there are some inherent factors that can impede components performance (i.e., surface roughness). Parts produced by L-PBF are usually characterized by rough “as-built” surfaces; hence, it is fundamental during the design phase to understand and consider how the quality of surfaces impacts on the part performance. This paper aims to provide a Computer-Aided Engineering (CAE) workflow to design components with different finishing regions in accordance with the functional distinction that exists among them. To achieve this goal, a comparison of the mechanical properties achieved for SCALMALLOY^® specimens with and without post-processing is here assessed to fit proper material models for numerical simulation purposes. The material models, built with/from experimental data, are fit to functionally adapt the performance of 3D-printed objects inside CAE simulations like a Functionally Graded Material (FGM). A CAE design workflow is here applied to a case study, suitable to demonstrate how the methodology may support the integrated product–process design of structural parts reducing the cost of post-processing in AM. This approach may mitigate the performance decrease of “as-built” surfaces since the experimental results show a different fatigue endurance limit between the “as-built” and CNC machined specimens about of three times.