IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-69182-2_4.html
   My bibliography  Save this book chapter

Modeling of Turbulent Flows Applied to Numerical Simulations of Galaxy Clusters

In: High Performance Computing in Science and Engineering, Garching/Munich 2007

Author

Listed:
  • Luigi Iapichino

    (Universität Würzburg, Institut für Theoretische Physik und Astrophysik)

  • Jens C. Niemeyer

    (Universität Würzburg, Institut für Theoretische Physik und Astrophysik)

  • Julian Adamek

    (Universität Würzburg, Institut für Theoretische Physik und Astrophysik)

  • Surajit Paul

    (Universität Würzburg, Institut für Theoretische Physik und Astrophysik)

  • Mario Scuderi

    (Sezione di Catania, Dipartimento di Fisica e Astronomia dell’Universitá di Catania, and Istituto Nazionale di Fisica Nucleare)

Abstract

FEARLESS (Fluid mEchanics with Adaptively Refined Large Eddy SimulationS) is a novel numerical approach for hydrodynamical simulations of turbulent flows, which combines the use of the adaptive mesh refinement (AMR) with a subgrid scale (SGS) model for the unresolved scales. We report some results of our first research phase, aimed to the test of new AMR criteria suitable for resolving velocity fluctuations. In this first stage of the project, no SGS model was used. Our simulations of a subcluster merger event clearly show that an accurate resolution of the turbulent flow is important not only for following the evolution of the shear instability, but also for its back-reaction on the subcluster core. A better resolution of the turbulent flow can also affect the level of turbulence in the cluster core, according to the first results of our cosmological simulations. Especially in the latter problem, a significant improvement in the modeling is expected from the use of the full FEARLESS implementation.

Suggested Citation

  • Luigi Iapichino & Jens C. Niemeyer & Julian Adamek & Surajit Paul & Mario Scuderi, 2009. "Modeling of Turbulent Flows Applied to Numerical Simulations of Galaxy Clusters," Springer Books, in: Siegfried Wagner & Matthias Steinmetz & Arndt Bode & Matthias Brehm (ed.), High Performance Computing in Science and Engineering, Garching/Munich 2007, pages 45-56, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-69182-2_4
    DOI: 10.1007/978-3-540-69182-2_4
    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

    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:978-3-540-69182-2_4. 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.