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Structural Displacement Requirement in a Topology Optimization Algorithm Based on Isogeometric Entities

Author

Listed:
  • Thibaut Rodriguez

    (Arts et Métiers ParisTech, Institut de Mécanique et d’Ingénierie, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5295
    French Atomic Energy Commission)

  • Marco Montemurro

    (Arts et Métiers ParisTech, Institut de Mécanique et d’Ingénierie, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5295)

  • Paul Texier

    (French Atomic Energy Commission)

  • Jérôme Pailhès

    (Arts et Métiers ParisTech, Institut de Mécanique et d’Ingénierie, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5295)

Abstract

This work deals with the formulation of a general design requirement on the displacement of a continuum medium in the framework of a special density-based algorithm for topology optimization. The algorithm makes use of non-uniform rational basis spline hyper-surfaces to represent the pseudo-density field describing the part topology and of the well-known solid isotropic material with penalization approach. The proposed formulation efficiently exploits the properties of the isogeometric basis functions, which allow defining an implicit filter. In particular, the structural displacement requirement is formulated in the most general sense, by considering displacements on loaded and non-loaded regions. The gradient of the structural displacement is evaluated in closed form by using the principle of virtual work. Moreover, a sensitivity analysis of the optimized topology to the integer parameters, involved in the definition of the hyper-surface, is carried out. The effectiveness of the proposed approach is proven through meaningful 2D and 3D benchmarks.

Suggested Citation

  • Thibaut Rodriguez & Marco Montemurro & Paul Texier & Jérôme Pailhès, 2020. "Structural Displacement Requirement in a Topology Optimization Algorithm Based on Isogeometric Entities," Journal of Optimization Theory and Applications, Springer, vol. 184(1), pages 250-276, January.
    • Handle: RePEc:spr:joptap:v:184:y:2020:i:1:d:10.1007_s10957-019-01622-8
    DOI: 10.1007/s10957-019-01622-8
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    Cited by:

    1. Mitjana, F. & Cafieri, S. & Bugarin, F. & Segonds, S. & Castanie, F. & Duysinx, P., 2021. "Topological gradient in structural optimization under stress and buckling constraints," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    2. Yun-Fei Fu & Kai Long & Bernard Rolfe, 2023. "On Non-Penalization SEMDOT Using Discrete Variable Sensitivities," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 644-677, August.

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