Design and experimental validation of self-supporting topologies for additive manufacturing

Yun Fei Fu, Bernard Rolfe, Louis N.S. Chiu, Yanan Wang, Xiaodong Huang, Kazem Ghabraie

Research output: Contribution to journalArticleResearchpeer-review

20 Citations (Scopus)

Abstract

Incorporating additive manufacturing (AM) constraints in topology optimisation can lead to performance optimality while ensuring manufacturability of designs. Numerical techniques have been previously proposed to obtain support-free designs in AM, however, few works have verified the manufacturability of their solutions. Physical verification of manufacturability becomes more critical recalling that the conventional density-based topology optimisation methods will inevitably require post-processing to smooth the boundaries before sending the results to a 3D printer. This paper presents the smooth design of self-supporting topologies using the combination of a new Solid Isotropic Microstructure with Penalisation method (SIMP) developed based on elemental volume fractions and an existing AM filter. Manufacturability of selected simulation results are verified with Fused Deposition Modeling (FDM) technology. It is illustrated that the proposed method is able to generate convergent self-supporting topologies which are printable using FDM.

Original languageEnglish
Pages (from-to)382-394
Number of pages13
JournalVirtual and Physical Prototyping
Volume14
Issue number4
DOIs
Publication statusPublished - 24 Jul 2019

Keywords

  • additive manufacturing
  • elemental volume fractions
  • level-set function
  • self-supporting design
  • smooth boundary representation
  • Topology optimisation

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