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A dual mesh method with adaptivity for stress-constrained topology optimization

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Abstract

This paper is concerned with the topological optimization of elastic structures, with the goal of minimizing the compliance and/or mass of the structure, subject to a stress constraint. It is well known that depending upon the geometry and the loading conditions, the stress field can exhibit singularities, if these singularities are not adequately resolved, the topological optimization process will be ineffective. For computational efficiency, adaptive mesh refinement is required to adequately resolve the stress field. This poses a challenge for the traditional Solid Isotropic Material with Penalization (SIMP) method that employs a one-to-one correspondence between the finite element mesh and the optimization design variables because as the mesh is refined, the optimization process must somehow be re-started with a new set of design variables. The proposed solution is a dual mesh approach, one finite element mesh defines the material distribution, a second finite element mesh is used for the computation of the displacement and stress fields. This allows for stress-based adaptive mesh refinement without modifying the definition of the optimization design variables. A second benefit of this dual mesh approach is that there is no need to apply a filter to the design variables to enforce a length scale, instead the length scale is determined by the design mesh. This reduces the number of design variables and allows the designer to apply spatially varying length scale if desired. The efficacy of this dual mesh approach is established via several stress-constrained topology optimization problems.

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Notes

  1. We introduce a lower bound, i.e., 𝜖 > 0, on the Berstein coefficients to avoid singularity in the analysis. However, this may ignore a globally optimal design as discussed in Cheng and Jiang (1992, 1997), Bruggi (2008), Le et al. (2010). We apply the relaxed stress indicator method to alleviate this issue as in Le et al. (2010).

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Authors and Affiliations

  1. Lawrence Livermore National Laboratory, Livermore, CA, USA

    Daniel A. White, Youngsoo Choi & Jun Kudo

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  1. Daniel A. White
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  2. Youngsoo Choi
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  3. Jun Kudo
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Correspondence to Daniel A. White.

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White, D.A., Choi, Y. & Kudo, J. A dual mesh method with adaptivity for stress-constrained topology optimization. Struct Multidisc Optim 61, 749–762 (2020). https://doi.org/10.1007/s00158-019-02393-6

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