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Analytical relationships for imposing minimum length scale in the robust topology optimization formulation

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Abstract

When using the robust topology optimization formulation in the density framework, the minimum size of the solid and void phases must be imposed implicitly through the parameters that define the density filter and the smoothed Heaviside projection. Finding these parameters can be time consuming and cumbersome, hindering a general code implementation of the robust formulation. Motivated by this issue, in this article, we provide analytical expressions that explicitly relate the minimum length scale and the parameters that define it. The expressions are validated on a density-based framework. To facilitate the reproduction of results, MATLAB codes are provided.

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Notes

  1. For the sake of clarity, this manuscript changes two notations with respect to Qian and Sigmund (2013). Here, \(2r_{\text {min.Solid}}^{\text {int}}\) and \(r_{\min \limits }\) respectively represent b and R in the cited article.

  2. The maximum size is actually imposed using an annular region (Fernández et al. 2020), but for illustrative purposes, a circular region is drawn.

  3. https://github.com/DenisTri/Analytical_Min_Size

References

  • Andreasen CS, Elingaard MO, Aage N (2020) Level set topology and shape optimization by density methods using cut elements with length scale control. Struct Multidiscip Optim: 1–23

  • Bendsøe MP (1989) Optimal shape design as a material distribution problem. Struct Optim 1:193–202

    Article  Google Scholar 

  • Bendsøe MP, Kikuchi N (1988) Generating optimal topologies in structural design using a homogenization method. Comput Methods Appl Mech Eng 71(2):197–224

    Article  MathSciNet  Google Scholar 

  • Bourdin B (2001) Filters in topology optimization. Int J Numer Methods Eng 50(9):2143–2158

    Article  MathSciNet  Google Scholar 

  • Bruns TE, Tortorelli DA (2001) Topology optimization of non-linear elastic structures and compliant mechanisms. Computer Methods Appl Mech Eng 190(26-27):3443–3459

    Article  Google Scholar 

  • Chen S, Chen W (2011) A new level-set based approach to shape and topology optimization under geometric uncertainty. Struct Multidiscip Optim 44(1):1–18

    Article  MathSciNet  Google Scholar 

  • Christiansen R, Lazarov B, Jensen J, Sigmund O (2015) Creating geometrically robust designs for highly sensitive problems using topology optimization: acoustic cavity design. Struct Multidiscip Optim 52:737–754

    Article  MathSciNet  Google Scholar 

  • Clausen A, Andreassen E (2017) On filter boundary conditions in topology optimization. Struct Multidiscip Optim 56(5):1147– 1155

    Article  MathSciNet  Google Scholar 

  • da Silva GA, Beck AT, Sigmund O (2019) Topology optimization of compliant mechanisms with stress constraints and manufacturing error robustness. Comput Methods Appl Mech Eng 354:397– 421

    Article  MathSciNet  Google Scholar 

  • Fernández E, Kk Yang, Koppen S, Alarcón P, Bauduin S, Duysinx P (2020) Imposing minimum and maximum member size, minimum cavity size, and minimum separation distance between solid members in topology optimization. Comput Methods Appl Mech Eng 368:113157

    Article  MathSciNet  Google Scholar 

  • Fernández E, Ayas C, Langelaar M, Duysinx P (2021) Topology optimization for large-scale additive manufacturing: Generating designs tailored to the deposition nozzle size (Under Review)

  • Lazarov BS, Sigmund O (2011) Filters in topology optimization based on helmholtz-type differential equations. Int J Numer Methods Eng 86(6):765–781

    Article  MathSciNet  Google Scholar 

  • Pedersen C, Allinger P (2006) Industrial implementation and applications of topology optimization and future needs, vol 137. Springer, Berlin, pp 229–238

    Google Scholar 

  • Pellens J, Lombaert G, Lazarov B, Schevenels M (2018) Combined length scale and overhang angle control in minimum compliance topology optimization for additive manufacturing. Struct Multidiscipl Optim

  • Qian X, Sigmund O (2013) Topological design of electromechanical actuators with robustness toward over-and under-etching. Comput Methods Appl Mech Eng 253:237–251

    Article  MathSciNet  Google Scholar 

  • Sigmund O (1997) On the design of compliant mechanisms using topology optimization. J Struct Mech 25(4):493–524

    Google Scholar 

  • Sigmund O (2009) Manufacturing tolerant topology optimization. Acta Mech Sinica 25(2):227–239

    Article  Google Scholar 

  • Sigmund O, Maute K (2013) Topology optimization approaches. Struct Multidiscip Optim 48 (6):1031–1055

    Article  MathSciNet  Google Scholar 

  • Silva G, Beck A, Sigmund O (2020) Topology optimization of compliant mechanisms considering stress constraints, manufacturing uncertainty and geometric nonlinearity. Comput Methods Appl Mech Eng 365:112972

    Article  MathSciNet  Google Scholar 

  • Wang F, Lazarov BS, Sigmund O (2011) On projection methods, convergence and robust formulations in topology optimization. Struct Multidiscip Optim 43(6):767–784

    Article  Google Scholar 

  • Wang F, Jensen J, Sigmund O (2011b) Robust topology optimization of photonic crystal waveguides with tailored dispersion properties. JOSA B 28:387–397

    Article  Google Scholar 

  • Wang F, Lazarov BS, Sigmund O, Jensen JS (2014) Interpolation scheme for fictitious domain techniques and topology optimization of finite strain elastic problems. Comput Methods Appl Mech Eng 276:453–472

    Article  MathSciNet  Google Scholar 

  • Xu S, Cai Y, Cheng G (2010) Volume preserving nonlinear density filter based on heaviside functions. Struct Multidiscip Optim 41(4):495–505

    Article  MathSciNet  Google Scholar 

  • Yan S, Wang F, Sigmund O (2018) On the non-optimality of tree structures for heat conduction. Int J Heat Mass Transf 122:660–680

    Article  Google Scholar 

  • Zhou M, Fleury R, Patten S, Stannard N, Mylett D, Gardner S (2011) Topology optimization-practical aspects for industrial applications. In: 9th World congress on structural and multidisciplinary optimization

  • Zhu JH, Zhang WH, Xia L (2016) Topology optimization in aircraft and aerospace structures design. Arch Comput Methods Eng 23:595–622

    Article  MathSciNet  Google Scholar 

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Funding

The authors acknowledge the research project FAFil (Fabrication Additive laser par dépôt de Fil), funded by INTERREG V A Grande Région and the European Regional Development Fund (ERDF).

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Correspondence to Denis Trillet.

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The authors declare that they have no conflict of interest.

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Responsible Editor: Gengdong Cheng

Replication of results

This manuscript contains two MATLAB codes as supplementary material that can be found on GitHubsFootnote 3. The first is called SizeSolution.m and provides a list of filter and projection parameters that impose user defined minimum length scales. The second is called NumericalSolution.m and builds the graphs in Fig. 6 using the numerical method proposed by Wang et al. (2011).

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Appendix

Appendix

As we show the contour plot of the minimum sizes ratio, it is possible to produce the same kind of figure for the offset distances. These are plotted in Fig. 19 and illustrate again the symmetric behavior of the sizes with the threshold values for a case where ηint = 0.5.

Fig. 19
figure 19

Contour plot of the offset distances in the domain (ηero,ηdil)

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Trillet, D., Duysinx, P. & Fernández, E. Analytical relationships for imposing minimum length scale in the robust topology optimization formulation. Struct Multidisc Optim 64, 2429–2448 (2021). https://doi.org/10.1007/s00158-021-02998-w

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