IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-75319-5_8.html
   My bibliography  Save this book chapter

Model Order Reduction a Key Technology for Digital Twins

In: Reduced-Order Modeling (ROM) for Simulation and Optimization

Author

Listed:
  • Dirk Hartmann

    (Siemens AG, Corporate Technology)

  • Matthias Herz

    (Siemens AG, Corporate Technology)

  • Utz Wever

    (Siemens AG, Corporate Technology)

Abstract

An increasing number of disruptive innovations with high economic and social impact shape our digitalizing world. Speed and extending scope of these developments are limited by available tools and paradigms to master exploding complexities. Simulation technologies are key enablers of digitalization. They enable digital twins mirroring products and systems into the digital world. Digital twins require a paradigm shift. Instead of expert centric tools, engineering and operation require autonomous assist systems continuously interacting with its physical and digital environment through background simulations. Model order reduction (MOR) is a key technology to transfer highly detailed and complex simulation models to other domains and life cycle phases. Reducing the degree of freedom, i.e., increasing the speed of model execution while maintaining required accuracies and predictability, opens up new applications. Within this contribution, we address the advantages of model order reduction for model-based system engineering and real-time thermal control of electric motors.

Suggested Citation

  • Dirk Hartmann & Matthias Herz & Utz Wever, 2018. "Model Order Reduction a Key Technology for Digital Twins," Springer Books, in: Winfried Keiper & Anja Milde & Stefan Volkwein (ed.), Reduced-Order Modeling (ROM) for Simulation and Optimization, pages 167-179, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-75319-5_8
    DOI: 10.1007/978-3-319-75319-5_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:sprchp:978-3-319-75319-5_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.