A projective transformation-based topology optimization using moving morphable components

The moving morphable components (MMC)-based topology optimization method makes it possible to directly connect theoretical designs to computer-aided design (CAD) systems. To improve the manufacturability of the optimal result, this paper proposes a projective transformation-based topology optimizati...

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Bibliographic Details
Published in:Computer methods in applied mechanics and engineering 2021-04, Vol.376, p.113646, Article 113646
Main Authors: Wang, Rixin, Zhang, Xianmin, Zhu, Benliang
Format: Article
Language:English
Subjects:
CAD
Computer aided design
Construction methods
Design optimization
Feature construction
Finite element method
Independent variables
Interpolation
Manufacturability
Moving morphable component
Optimization
Sensitivity analysis
Topology optimization
XFEM
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Summary:The moving morphable components (MMC)-based topology optimization method makes it possible to directly connect theoretical designs to computer-aided design (CAD) systems. To improve the manufacturability of the optimal result, this paper proposes a projective transformation-based topology optimization using moving morphable components (PMMC), which can reduce the performance loss when the optimized design is ported to practical manufacturing. The basic idea is to treat an arbitrary component as a projection of a component template independent of design variables. A hierarchical feature construction method is used to reconstruct the internal details within an element while reducing the interpolation error, in order to achieve a high-precision feature representation and sensitivity analysis that are not affected by the quality of the background mesh. The proposed method not only ensures the consistency of the geometric model and the analysis model, but also flexibly addresses components that are difficult to describe explicitly. The effectiveness of the proposed method is verified through a series of numerical examples. •A projective transformation-based explicit topology optimization method is developed.•The interpolation error caused by topology description functions (TDFs) is evaluated.•A new parameters mapping scheme that does not rely on explicit TDFs is proposed.•The consistency between the geometric model and the analysis model can be improved.
ISSN:0045-7825
1879-2138
DOI:10.1016/j.cma.2020.113646