IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v523y2019icp211-221.html
   My bibliography  Save this article

Quantification of the complexity and unpredictability of a turbulent cylinder wake using excess entropy

Author

Listed:
  • Tao, Xingtian
  • Wu, Huixuan

Abstract

The complexity of a turbulent wake flow is studied using the excess entropy method. Turbulent complexity originates from the deterministic but unpredictable nature of the governing equation, and the excess entropy method is useful in providing a systematic way to quantify the random and coherent patterns in a flow field using information-per-letter and degree-of-complexity, respectively. In this study, the excess entropy calculated using the transverse velocity component decreases considerably along the stream-wise direction, which is consistent with the fact that large-scale structures dissociate and disappear in the far wake. The flow gradually becomes more random and unpredictable. On the other hand, the excess entropy obtained from the streamwise velocity sequence reveals that the pattern of small-scale structures remains largely unchanged during the flow evolution, even though their intensity becomes weaker. Quantifying the coherence and randomness of turbulence provides a more complete description of a complex flow field. The parameter selection in the complexity evaluation is also discussed in the paper.

Suggested Citation

  • Tao, Xingtian & Wu, Huixuan, 2019. "Quantification of the complexity and unpredictability of a turbulent cylinder wake using excess entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 211-221.
  • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:211-221
    DOI: 10.1016/j.physa.2019.02.040
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119301931
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.02.040?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:phsmap:v:523:y:2019:i:c:p:211-221. 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/physica-a-statistical-mechpplications/ .

    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.