Self-supporting structure design with feature-driven optimization approach for additive manufacturing

Lu Zhou, Ole Sigmund, Weihong Zhang

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

In this work, a topology optimization approach is developed for additive manufacturing (AM) of 2D and 3D self-supporting structures. Three important issues, i.e., overhang angle control, avoidance of the so-called V-shaped areas and minimum length scale control are addressed. 2D solid polygon and 3D polyhedron features are introduced as basic design primitives that are capable of translations, deformations and intersections to drive topological changes of the structure. The overhang angle control is realized in a straightforward way only by imposing upper bounds to related design variables without introducing any nonlinear constraint. The V-shaped area is avoided by simply limiting the positions of solid features. Minimum length scale control is controlled by a robust formulation. Numerical examples in 2D and 3D demonstrate the effectiveness of the proposed approach for various build directions, critical overhang angles and minimum length scales considered in AM.

Original languageEnglish
Article number114110
JournalComputer Methods in Applied Mechanics and Engineering
Volume386
DOIs
StatePublished - 1 Dec 2021

Keywords

  • Additive manufacturing
  • Minimum length scale
  • Overhang angle control
  • Self-supporting structures
  • Solid polygon/polyhedron features
  • V-shaped area

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