IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v409y2021ics0096300321000801.html
   My bibliography  Save this article

Topological gradient in structural optimization under stress and buckling constraints

Author

Listed:
  • Mitjana, F.
  • Cafieri, S.
  • Bugarin, F.
  • Segonds, S.
  • Castanie, F.
  • Duysinx, P.

Abstract

Structural topology optimization aims to design mechanical structures by seeking the optimal material layout within a given design space. Within this framework, this paper addresses the minimization of the structural mass under stress and buckling constraints, formulated as a nonlinear combinatorial optimization problem. An algorithm is proposed for such a problem, that follows a topological gradient-based approach. The adjoint method is applied to efficiently compute the constraint gradients. An iterative algorithm for buckling analysis, featuring low memory requirements, is also proposed. Numerical results, including a real application arising in the aeronautical field, illustrate the efficiency of the two proposed algorithms.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:apmaco:v:409:y:2021:i:c:s0096300321000801
    DOI: 10.1016/j.amc.2021.126032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321000801
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:409:y:2021:i:c:s0096300321000801. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.