IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v182y2021icp116-142.html
   My bibliography  Save this article

Accuracy and computational efficiency of dealiasing schemes for the DNS of under resolved flows with strong gradients

Author

Listed:
  • Sinhababu, Arijit
  • Ayyalasomayajula, Sathyanarayana

Abstract

In this paper, we have studied the effect of residual aliasing error of the second order Runge–Kutta (RK2) based Random Phase Shift Method (RPSM) which shows smoothing effect in the solution of under-resolved flows involving strong gradients. Firstly, we show that RPSM is almost as accurate as the fully dealiased 3/2 Padding scheme but with similar computational cost as the fast 2/3 Truncation scheme. Secondly, we show that RPSM has high accuracy in the case of under-resolved shear layer and Surface Quasi-Geostrophic (SQG) flows. Further, we show that the 2/3 Truncation scheme turns more computationally expensive than 3/2 Padding or RPSM when we try to achieve the same level of accuracy. Filtering based dealiasing schemes are found to be an inappropriate choice for a variety of flow problems because they are prone to unphysical parasitic currents. For the first time error norm based computational efficiency, i.e., high accuracy at the lower computational cost of RPSM scheme is shown. Although some artifacts of dealiasing remain due to Fourier windowing in RPSM, it is found to be numerically stable even in under-resolved conditions at later simulation time. We have validated our numerical results with the analytical ones and also with the previous literature.

Suggested Citation

  • Sinhababu, Arijit & Ayyalasomayajula, Sathyanarayana, 2021. "Accuracy and computational efficiency of dealiasing schemes for the DNS of under resolved flows with strong gradients," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 116-142.
  • Handle: RePEc:eee:matcom:v:182:y:2021:i:c:p:116-142
    DOI: 10.1016/j.matcom.2020.10.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475420303712
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2020.10.020?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:182:y:2021:i:c:p:116-142. 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.