Abstract
In this study, we present an efficient Topology Optimization (TO) approach designed to optimize support structures in metal Additive Manufacturing (AM), with a particular focus on Powder Bed Fusion (PBF) technology. The developed framework uses a purely thermal formulation to identify regions within the design that are susceptible to high heat concentrations. In the proposed modeling of the AM process, we postulate that new material layers are included in a partially built design that has already cooled to a controlled temperature. This aspect provides a layer-by-layer model of AM entirely local, enabling the building process parallelization and resulting in an algorithm with superior computational efficiency. Numerical results show the robustness of the proposed strategy, with the successful incorporation of support structures beneath overhanging surfaces and their effectiveness across a wide range of geometries and orientations. Furthermore, this framework is also applied to optimize the geometry orientation within the build chamber, further enhancing its applicability in the AM context.
Published Version
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