Skip to main content
Log in

Efficient use of iterative solvers in nested topology optimization

  • Research Paper
  • Published:
Structural and Multidisciplinary Optimization Aims and scope Submit manuscript

Abstract

In the nested approach to structural optimization, most of the computational effort is invested in the solution of the analysis equations. In this study, it is suggested to reduce this computational cost by using an approximation to the solution of the analysis problem, generated by a Krylov subspace iterative solver. By choosing convergence criteria for the iterative solver that are strongly related to the optimization objective and to the design sensitivities, it is possible to terminate the iterative solution of the nested equations earlier compared to traditional convergence measures. The approximation is computationally shown to be sufficiently accurate for the purpose of optimization though the nested equation system is not necessarily solved accurately. The approach is tested on several large-scale topology optimization problems, including minimum compliance problems and compliant mechanism design problems. The optimized designs are practically identical while the time spent on the analysis is reduced significantly.

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.

Similar content being viewed by others

References

  • Amir O, Bendsøe MP, Sigmund O (2009a) Approximate reanalysis in topology optimization. Int J Numer Methods Eng 78:1474–1491

    Article  MATH  Google Scholar 

  • Amir O, Stolpe M, Sigmund O (2009b) Efficient use of iterative solvers in nested topology optimization. In: Proceedings of the 8th world congress on structural and multidisciplinary optimization, Lisbon, Portugal

    Google Scholar 

  • 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 71:197–224

    Article  Google Scholar 

  • Bendsøe MP, Sigmund O (2003) Topology optimization—theory, methods and applications. Springer, Berlin

    Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  Google Scholar 

  • Evgrafov A, Rupp CJ, Maute K, Dunn ML (2008) Large-scale parallel topology optimization using a dual-primal substructuring solver. Struct Multidisc Optim 36:329–345

    Article  MathSciNet  Google Scholar 

  • Hestenes MR, Stiefel E (1952) Methods of conjugate gradients for solving linear systems. J Res Natl Bur Stand 49(6):409–436

    MATH  MathSciNet  Google Scholar 

  • Kim TS, Kim JE, Kim YY (2004) Parallelized structural topology optimization for eigenvalue problems. Int J Solids Struct 41:2623–2641

    Article  MATH  Google Scholar 

  • Kirsch U (1991) Reduced basis approximations of structural displacements for optimal design. AIAA J 29:1751–1758

    Article  MATH  Google Scholar 

  • Mahdavi A, Balaji R, Freckerand M, Mockensturm EM (2006) Topology optimization of 2D continua for minimum compliance using parallel computing. Struct Multidisc Optim 32:121–132

    Article  Google Scholar 

  • Meijerink JA, van der Vorst HA (1977) An iterative solution method for linear equation systems of which the coefficient matrix is a symmetric M-matrix. Math Comput 31:148–162

    Article  MATH  Google Scholar 

  • O’Leary DP (1980) The block conjugate gradient algorithm and related methods. Linear Algebra Appl 29:293–322

    Article  MATH  MathSciNet  Google Scholar 

  • Saad Y (2003) Iterative methods for sparse linear systems, 2nd edn. SIAM, Philadelphia

    MATH  Google Scholar 

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

    Article  Google Scholar 

  • Sigmund O (2001) A 99 line topology optimization code written in matlab. Struct Multidisc Optim 21:120–127

    Article  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  • van der Sluis A, van der Vorst HA (1986) The rate of convergence of conjugate gradients. Numer Math 48:543–560

    Article  MATH  MathSciNet  Google Scholar 

  • Vemaganti K, Lawrence EW (2005) Parallel methods for optimality criteria-based topology optimization. Comput Methods Appl Mech Eng 194:3637–3667

    Article  MATH  MathSciNet  Google Scholar 

  • Wang S, de Sturler E, Paulino GH (2007) Large-scale topology optimization using preconditioned Krylov subspace methods with recycling. Int J Numer Methods Eng 69:2441–2468

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Oded Amir.

Additional information

This is an extended version of a paper presented at WCSMO-8, held in Lisbon, Portugal, June 2009.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Amir, O., Stolpe, M. & Sigmund, O. Efficient use of iterative solvers in nested topology optimization. Struct Multidisc Optim 42, 55–72 (2010). https://doi.org/10.1007/s00158-009-0463-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00158-009-0463-4

Keywords

Navigation