An interface-enriched generalized finite element method for level set-based topology optimization

Journal Article (2020)
Author(s)

Sanne J. van den Boom (TU Delft - Computational Design and Mechanics)

J. Zhang (TU Delft - Computational Design and Mechanics)

F. Van Keulen (TU Delft - Computational Design and Mechanics)

AM Aragon (TU Delft - Computational Design and Mechanics)

Research Group
Computational Design and Mechanics
Copyright
© 2020 S.J. van den Boom, J. Zhang, A. van Keulen, A.M. Aragon
DOI related publication
https://doi.org/10.1007/s00158-020-02682-5
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 S.J. van den Boom, J. Zhang, A. van Keulen, A.M. Aragon
Related content
Research Group
Computational Design and Mechanics
Issue number
1
Volume number
63
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Abstract

During design optimization, a smooth description of the geometry is important, especially for problems that are sensitive to the way interfaces are resolved, e.g., wave propagation or fluid-structure interaction. A level set description of the boundary, when combined with an enriched finite element formulation, offers a smoother description of the design than traditional density-based methods. However, existing enriched methods have drawbacks, including ill-conditioning and difficulties in prescribing essential boundary conditions. In this work, we introduce a new enriched topology optimization methodology that overcomes the aforementioned drawbacks; boundaries are resolved accurately by means of the Interface-enriched Generalized Finite Element Method (IGFEM), coupled to a level set function constructed by radial basis functions. The enriched method used in this new approach to topology optimization has the same level of accuracy in the analysis as the standard finite element method with matching meshes, but without the need for remeshing. We derive the analytical sensitivities and we discuss the behavior of the optimization process in detail. We establish that IGFEM-based level set topology optimization generates correct topologies for well-known compliance minimization problems.