Vortex Dynamics in Evolutive Flows: A Weakly Chaotic Phenomenon

Description:

In this article, the authors make use of a wavelet method to extract, from experimental velocity signals obtained in an evolutive flow, the dominating velocity components generated by vortex dynamics.

Creator(s):
Creation Date: 2003  
Partner(s):
UNT College of Arts and Sciences
Collection(s):
UNT Scholarly Works
Usage:
Total Uses: 76
Past 30 days: 3
Yesterday: 0
Creator (Author):
Bellazzini, Jacopo

Universitá di Pisa

Creator (Author):
Menconi, Giulia

Universitá di Pisa

Creator (Author):
Ignaccolo, Massimiliano

University of North Texas

Creator (Author):
Buresti, Guido

Universitá di Pisa

Creator (Author):
Grigolini, Paolo

University of North Texas; Universitá di Pisa and INFM; Istituto dei Processi Chimico Fisici del Consiglio Nazionale delle Ricerche

Publisher Info:
Publisher Name: American Physical Society
Place of Publication: [College Park, Maryland]
Date(s):
  • Creation: 2003
Description:

In this article, the authors make use of a wavelet method to extract, from experimental velocity signals obtained in an evolutive flow, the dominating velocity components generated by vortex dynamics.

Degree:
Department: Physics
Note:

Copyright 2003 American Physical Society. The following article appeared in Physical Review E, 68:2; http://pre.aps.org/abstract/PRE/v68/i2/e026126

Note:

Abstract: We make use of a wavelet method to extract, from experimental velocity signals obtained in an evolutive flow, the dominating velocity components generated by vortex dynamics. We characterize the resulting time series complexity by means of a joint use of data compression and of an entropy diffusion method. We assess that the time series emerging from the wavelet analysis of the vortex dynamics is a weakly chaotic process with a vanishing Kolmogorov-Sinai entropy and a power-law growth of the information content. To reproduce the Fourier spectrum of the experimental signal, we adopt a harmonic dependence on time with a fluctuating frequency, ruled by an inverse power-law distribution of random events. The complexity of these fluctuations is determined by studying the corresponding artificial sequences. We reproduce satisfactorily both spectral and complex properties of the experimental signal by locating the complexity of the fluctuating process at the border between the stationary and the nonstationary states.

Physical Description:

10 p.

Language(s):
Subject(s):
Keyword(s): vortex dynamics | entropy diffusion
Source: Physical Review E, 2003, College Park: American Physical Society
Partner:
UNT College of Arts and Sciences
Collection:
UNT Scholarly Works
Identifier:
  • DOI: 10.1103/PhysRevE.68.026126
  • ARK: ark:/67531/metadc67634
Resource Type: Article
Format: Text
Rights:
Access: Public
Citation:
Publication Title: Physical Review E
Volume: 68
Issue: 2
Pages: 10
Peer Reviewed: Yes