IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i24p5808-5813.html
   My bibliography  Save this article

Autocorrelation function formulations and the turbulence dissipation rate: Application to dispersion models

Author

Listed:
  • Degrazia, Gervásio A.
  • Acevedo, Otávio C.
  • Carvalho, Jonas C.
  • Maldaner, Silvana
  • Gonçalves, Juliana Bittencourt
  • Rizza, Umberto

Abstract

The classical statistical diffusion theory and the binomial autocorrelation function are used to obtain a new formulation for the turbulence dissipation rate ε. The approach employs the Maclaurin series expansion of a logarithm function contained in the dispersion parameter formulation. The numerical coefficient of this new relation for ε is 100% larger than the numerical coefficient of the classical relation derived from the exponential autocorrelation function. A similar approach shows that the dispersion parameter obtained from the even exponential autocorrelation function does not result in a relation for ε and, therefore, is not suitable for application in dispersion models. In addition, a statistical comparison to experimental ground-level concentration data demonstrates that this newly derived relation for ε as well as other formulations for the turbulence dissipation rate are suitable for application in Lagrangian stochastic dispersion models. Therefore, the analysis shows that there is an uncertainty regarding the turbulence dissipation rate function form and the autocorrelation function form.

Suggested Citation

  • Degrazia, Gervásio A. & Acevedo, Otávio C. & Carvalho, Jonas C. & Maldaner, Silvana & Gonçalves, Juliana Bittencourt & Rizza, Umberto, 2010. "Autocorrelation function formulations and the turbulence dissipation rate: Application to dispersion models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5808-5813.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:24:p:5808-5813
    DOI: 10.1016/j.physa.2010.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110007806
    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.2010.09.001?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:389:y:2010:i:24:p:5808-5813. 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.