A MULTI-MATERIAL TOPOLOGY OPTIMIZATION APPROACH FOR LARGE-SCALE ADDITIVE MANUFACTURING OF NON-PERIODIC ARCHITECTED STRUCTURES

Topology optimization algorithms allow the design of optimized structures under prescribed constraints, loads, and boundary conditions. In this contribution, a structural optimization framework is proposed to deal with the challenges posed by large-scale additive manufacturing. The formulation is a volume constrained compliance-based optimization, which leverages on the selection of suitable non-periodic architectures at the microscale, such as spinodal architected materials, by a multi-material and homogenization-based approach. The implemented architectures have unstructured and stochastic features, which are suitable for smooth transitions between different materials. The wide range of spinodal material classes achievable is combined with porosity and orientation setting, which provide high design freedom. The proposed approach is exemplified by exploiting the features of a novel large-scale water jetting powder-bed 3D printing technology.