EconPapers    
Economics at your fingertips  
 

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

Xingtian Tao and Huixuan Wu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 523, issue C, 211-221

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.

Keywords: Excess entropy; Turbulent wake; Flow complexity; Unpredictability (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119301931
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

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:523:y:2019:i:c:p:211-221

DOI: 10.1016/j.physa.2019.02.040

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:211-221