IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v233y2025icp530-552.html
   My bibliography  Save this article

Multi-material topology optimization using isogeometric method based reaction–diffusion level set techniques

Author

Listed:
  • Kumar, Harsh
  • Rakshit, Sourav

Abstract

This work presents a new approach to multi-material topology optimization (MMTO) using Isogeometric Analysis (IGA) based reaction–diffusion equation (RDE) level set method. Level set based topology optimization, frequently used for achieving clear material boundaries and avoiding checkerboard patterns in topology optimization problems is further augmented by RDEs which enhance numerical stability of the solver. The multi-material formulation uses a blended combination of different level-set functions to ensure that each point in the domain corresponds to a single material. In this work, isogeometric analysis (IGA) is used for the first time in RDE-based level set for solving MMTO problems. The same Non-Uniform Rational B-Splines (NURBS) basis function is used for approximating state variables, geometry modeling and level set function, thus facilitating seamless coupling between analysis and product design. Using the IGAFEM toolbox (Nguyen et al., 2015), MMTO is performed for a few benchmark problems for varying material composition and mesh sizes. Results indicate that satisfactory distribution of material is achieved in all the MMTO examples and bi-quadratic element based IGA is a competent tool to be applied in RDE-based level set method for topology optimization. Future work will focus on using the same IGA framework for further shape optimization of the designed structures to produce fabrication ready CAD models.

Suggested Citation

  • Kumar, Harsh & Rakshit, Sourav, 2025. "Multi-material topology optimization using isogeometric method based reaction–diffusion level set techniques," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 233(C), pages 530-552.
  • Handle: RePEc:eee:matcom:v:233:y:2025:i:c:p:530-552
    DOI: 10.1016/j.matcom.2025.02.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037847542500045X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2025.02.010?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.

    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:matcom:v:233:y:2025:i:c:p:530-552. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.