Support structure constrained topology optimization for additive manufacturing.

There is significant interest today in integrating additive manufacturing (AM) and topology optimization (TO). However, TO often leads to designs that are not AM friendly. For example, topologically optimized designs may require significant amount of support structures before they can be additively manufactured, resulting in increased fabrication and clean-up costs.In this paper, we propose a TO methodology that will lead to designs requiring significantly reduced support structures. Towards this end, the concept of support structure topological sensitivity is introduced. This is combined with performance sensitivity to result in a TO framework that maximizes performance, subject to support structure constraints. The robustness and efficiency of the proposed method is demonstrated through numerical experiments, and validated through fused deposition modeling, a popular AM process. Addresses additive manufacturing support structure constraint in topology optimization.Introduces topological sensitivity for support structures.Combines support structure sensitivity with performance sensitivity.Proposes a robust and efficient algorithm for support structure constrained topology optimization.