IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i24p4965-d1300678.html
   My bibliography  Save this article

Generalized Multiscale Finite Element Method and Balanced Truncation for Parameter-Dependent Parabolic Problems

Author

Listed:
  • Shan Jiang

    (School of Science, Nantong University, Nantong 226019, China)

  • Yue Cheng

    (School of Science, Nantong University, Nantong 226019, China)

  • Yao Cheng

    (School of Mathematical Sciences, Suzhou University of Science and Technology, Suzhou 215009, China)

  • Yunqing Huang

    (School of Mathematics and Computational Science, Xiangtan University, Xiangtan 411105, China
    Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan 411105, China
    Key Laboratory of Intelligent Computing Information Processing of Ministry of Education, Xiangtan 411105, China)

Abstract

We propose a generalized multiscale finite element method combined with a balanced truncation to solve a parameter-dependent parabolic problem. As an updated version of the standard multiscale method, the generalized multiscale method contains the necessary eigenvalue computation, in which the enriched multiscale basis functions are picked up from a snapshot space on users’ demand. Based upon the generalized multiscale simulation on the coarse scale, the balanced truncation is applied to solve its Lyapunov equations on the reduced scale for further savings while ensuring high accuracy. A θ -implicit scheme is utilized for the fully discretization process. Finally, numerical results validate the uniform stability and robustness of our proposed method.

Suggested Citation

  • Shan Jiang & Yue Cheng & Yao Cheng & Yunqing Huang, 2023. "Generalized Multiscale Finite Element Method and Balanced Truncation for Parameter-Dependent Parabolic Problems," Mathematics, MDPI, vol. 11(24), pages 1-14, December.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:24:p:4965-:d:1300678
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/24/4965/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/24/4965/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Denis Spiridonov & Jian Huang & Maria Vasilyeva & Yunqing Huang & Eric T. Chung, 2019. "Mixed Generalized Multiscale Finite Element Method for Darcy-Forchheimer Model," Mathematics, MDPI, vol. 7(12), pages 1-13, December.
    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.

      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:gam:jmathe:v:11:y:2023:i:24:p:4965-:d:1300678. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      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.