Concurrent topology optimization of shells with self-supporting infills for additive manufacturing

This paper presents a systematic design optimization approach for shells with self-supporting infills for Additive Manufacturing (AM). The design workflow includes a concurrent Topology Optimization (TO) of the shells and the infills using a density based TO approach, followed by a model reconstruction that is tailored to guarantee a precise overhang control on the output Boundary-represented (B-rep) geometry. In the TO model, a new overhang constraint is developed to ensure that the TO result satisfying an overhang angle is defined on a basis of the discrete mesh elements. The TO process is stabilized by utilizing an adaptive parameter updating strategy and a two-field based formulation is proposed to control the minimum length scale. The topology optimized result is re-constructed into a B-rep model afterwards, in which the maximum overhang span of the explicit geometry is strictly controlled to satisfy the manufacturability requirement of an actual AM process. By applying the proposed TO and the associated geometry reconstruction together, the optimized infills are not only self-supporting but also can support the optimized shells from the structural inside. Truly manufacturable shell-infill structures with desirable mechanical properties can be obtained regardless of the voxel granularity of TO. Numerical examples and AM prototypes are given to demonstrate the effectiveness and the applicability of the proposed approach. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper presents a systematic design optimization approach for shells with self-supporting infills for Additive Manufacturing (AM). The design workflow involves concurrent Topology Optimization (TO) of the shells and infills, with a focus on overhang control and manufacturability requirements. By utilizing a density based TO approach and a two-field based formulation, the optimized infills can support the shells and meet mechanical properties regardless of voxel granularity.