Skip to main content
Log in

Constructing self-supporting structures in biscale topology optimization

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

The self-supporting requirement is very necessary in additive manufacturing so that the printed structure will not collapse during fabrication. Imposing the self-supporting constraint on topology optimization allows for designing a performance optimized structure that is ready-to-print. However, although biscale topology optimization has been widely studied, conducting self-supporting topology optimization separately for the macro-structure and for each micro-structure is not sufficient to produce an overall self-supporting structure, as first observed in this study. The issue is resolved via an approach to bridge the gap between the requirements of self-supporting at the two scales via distinguishing the macro-cells based on their relative locations. In addition, the self-supporting constraint is expressed as a simple quadratic function included in the topology optimization in both scales, and a convolution operator is designed to efficiently implement its detection. Ultimately, a completely self-supporting overall structure is generated within a biscale topology optimization framework and extends its potentiality to produce design to be directly fabricated via additive manufacturing. Performance of the approach is demonstrated via various 2D and 3D examples.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. Langelaar, M.: An additive manufacturing filter for topology optimization of print-ready designs. Struct. Multidiscip. Optim. 55, 1–13 (2016)

  2. Langelaar, M.: Topology optimization of 3D self-supporting structures for additive manufacturing. Addit. Manuf. 12, 60–70 (2016)

    Google Scholar 

  3. Daniel, T.: The development of design rules for selective laser melting, University of Wales, Cardiff (2009)

  4. Majhi, J., Janardan, R., Schwerdt, J., Smid, M., Gupta, P.: Minimizing support structures and trapped area in two-dimensional layered manufacturing. Comput. Geom. 12(3–4), 241–267 (1999)

    Article  MathSciNet  Google Scholar 

  5. Vanek, J., Galicia, J., Benes, B.: Clever support: efficient support structure generation for digital fabrication. Comput. Graph. Forum 33(5), 117–125 (2014)

    Article  Google Scholar 

  6. Wang, C., Chen, Y.: Thickening freeform surfaces for solid fabrication. Rapid Prototyp. J. 19(6), 395–406 (2013)

    Article  Google Scholar 

  7. Dumas, J., Hergel, J., Lefebvre, S.: Bridging the gap: automated steady scaffoldings for 3D printing. ACM Trans. Graph. 33(4), 1–10 (2014)

    Article  Google Scholar 

  8. Wu, J., Wang, C.C., Zhang, X., Westermann, R.: Self-supporting rhombic infill structures for additive manufacturing. Comput. Aided Des. 80, 32–42 (2016)

    Article  Google Scholar 

  9. Hu, K., Jin, S., Wang, C.C.: Support slimming for single material based additive manufacturing. Comput. Aided Des. 65, 1–10 (2015)

    Article  Google Scholar 

  10. Brackett, D., Ashcroft, I., Hague, R.: Topology optimization for additive manufacturing. In: Proceedings of the Solid Freeform Fabrication Symposium, Austin, TX, pp. 348–362 (2011)

  11. Gaynor, A.T., Guest, J.K.: Topology optimization for additive manufacturing: considering maximum overhang constraint. In: 15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, pp. 16–20 (2014)

  12. Qian, X.: Undercut and overhang angle control in topology optimization: a density gradient based integral approach. Int. J. Numer. Meth. Eng. 111(3), 247–272 (2017)

    Article  MathSciNet  Google Scholar 

  13. Guo, X., Zhou, J., Zhang, W., Du, Z., Liu, C., Liu, Y.: Self-supporting structure design in additive manufacturing through explicit topology optimization. Comput. Methods Appl. Mech. Eng. 323, 27–63 (2017)

    Article  MathSciNet  Google Scholar 

  14. Huang, X., Zhou, S.W., Xie, Y.M., Li, Q.: Topology optimization of microstructures of cellular materials and composites for macrostructures. Comput. Mater. Sci. 67, 397–407 (2013)

    Article  Google Scholar 

  15. Yan, X., Huang, X., Zha, Y., Xie, Y.M.: Concurrent topology optimization of structures and their composite microstructures. Comput. Struct. 133(3), 103–110 (2014)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  17. Bendsoe, M.P.: Optimal shape design as a material distribution problem. Struct. Optim. 1(4), 193–202 (1989)

    Article  Google Scholar 

  18. Xie, Y.M., Steven, G.P.: A simple evolutionary procedure for structural optimization. Comput. Struct. 49(5), 885–896 (1993)

    Article  Google Scholar 

  19. Huang, X., Xie, Y.M.: A further review of ESO type methods for topology optimization. Struct. Multidiscip. Optim. 41(5), 671–683 (2010)

    Article  Google Scholar 

  20. Wang, M.Y., Wang, X., Guo, D.: A level set method for structural topology optimization. Adv. Eng. Softw. 192(1), 227–246 (2004)

    MathSciNet  MATH  Google Scholar 

  21. Dijk, N.P.V., Maute, K., Langelaar, M., Keulen, F.V.: Level-set methods for structural topology optimization: a review. Struct. Multidiscip. Optim. 48(3), 437–472 (2013)

    Article  MathSciNet  Google Scholar 

  22. Qian, X.: Topology optimization in b-spline space. Comput. Methods Appl. Mech. Eng. 265(3), 15–35 (2013)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  24. Andreassen, E., Andreasen, C.S.: How to determine composite material properties using numerical homogenization. Comput. Mater. Sci. 83(2), 488–495 (2014)

    Article  Google Scholar 

  25. Liang, X., Breitkopf, P.: Design of materials using topology optimization and energy-based homogenization approach in matlab. Struct. Multidiscip. Optim. 52(6), 1229–1241 (2015)

    Article  MathSciNet  Google Scholar 

  26. Zuo, Z.H., Xie, Y.M.: A simple and compact python code for complex 3D topology optimization. Adv. Eng. Softw. 85, 1–11 (2015)

    Article  Google Scholar 

  27. Vatanabe, S.L., Lippi, T.N., Lima, C.R.D., Paulino, G.H., Silva, E.C.N.: Topology optimization with manufacturing constraints: a unified projection-based approach. Adv. Eng. Softw. 100, 97–112 (2016)

    Article  Google Scholar 

  28. Liu, J., Ma, Y.: A survey of manufacturing oriented topology optimization methods. Adv. Eng. Softw. 100, 161–175 (2016)

    Article  Google Scholar 

  29. Groen, J.P., Sigmund, O.: Homogenization-based topology optimization for high-resolution manufacturable microstructures. Int. J. Numer. Meth. Eng. 113(8), 1148–1163 (2018)

    Article  MathSciNet  Google Scholar 

  30. Wang, W., Liu, Y.J., Wu, J., Tian, S., Wang, C.C.L., Liu, L., Liu, X.: Support-free hollowing. In: IEEE Transactions on Visualization & Computer Graphics, p. 99, no. 1–1 (2017)

  31. Xie, Y., Chen, X.: Support-free interior carving for 3D printing. Vis. Inf. 1(1), 9–15 (2017)

    Google Scholar 

  32. Zhao, D., Li, M., Liu, Y.: A novel application framework for self-supporting topology optimization. Vis. Comput. 37, 1169–1184 (2021). https://doi.org/10.1007/s00371-020-01860-2

  33. Xu, C., Li, M., Huang, J., Gao, S.: Efficient biscale design of semiregular porous structures with desired deformation behavior. Comput. Struct. 182, 284–295 (2017)

    Article  Google Scholar 

  34. Ming, P.: Numerical methods for multiscale elliptic problems. J. Comput. Phys. 214, 421–445 (2006)

    Article  MathSciNet  Google Scholar 

  35. Abdulle, A., Nonnenmacher, A.: A short and versatile finite element multiscale code for homogenization problems. Comput. Methods Appl. Mech. Eng. 198(37–40), 2839–2859 (2009)

    Article  MathSciNet  Google Scholar 

  36. Li, H., Luo, Z., Zhang, N., Gao, L., Brown, T.: Integrated design of cellular composites using a level-set topology optimization method. Comput. Methods Appl. Mech. Eng. 309, 453–475 (2016)

    Article  MathSciNet  Google Scholar 

  37. Svanberg, K.: The method of moving asymptotes—a new method for structural optimization. Int. J. Numer. Meth. Eng. 24(2), 359–373 (1987)

    Article  MathSciNet  Google Scholar 

  38. Xia, L., Breitkopf, P.: Concurrent topology optimization design of material and structure within \(\text{ FE}^{2}\) nonlinear multiscale analysis framework. Comput. Methods Appl. Mech. Eng. 278, 524–542 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

The valuable comments from the anonymous reviewers are greatly appreciated. The work described in the study is partially supported by National Key Research and Development Program (No. 2020YFC2201303), and the NSF of China (No. 61872320).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ming Li.

Ethics declarations

Conflict of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work; there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, D., Gu, T.T., Liu, Y. et al. Constructing self-supporting structures in biscale topology optimization. Vis Comput 38, 1065–1082 (2022). https://doi.org/10.1007/s00371-021-02068-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-021-02068-8

Keywords

Navigation