Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Vortex dynamics in evolutive flows: a weakly chaotic phenomenon.

Jacopo Bellazzini1, Giulia Menconi, Massimiliano Ignaccolo

  • 1Dipartimento di Ingegneria Aerospaziale, Università di Pisa, Italy.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 4, 2003
PubMed
Summary

A wavelet method reveals that vortex dynamics in evolutive flows exhibit weakly chaotic behavior. This complexity, characterized by entropy diffusion, is key to reproducing experimental signal properties.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

From visibility graphs to cognition.

Frontiers in network physiology·2026
Same author

Continuous bidirectional coupling of heart rate variability and emotions in dyad speaker-listener dynamics reveals unique interpersonal synchronization.

Frontiers in systems neuroscience·2026
Same author

Bidirectional coupling of physiology and emotions reveals unique speaker-listener dynamics.

Social cognitive and affective neuroscience·2026
Same author

First Experimental Measurements of Biophotons from Astrocytes and Glioblastoma Cell Cultures.

Entropy (Basel, Switzerland)·2026
Same author

Crucial events identify early stage of cardiac autonomic neuropathy progression from ECG signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Identification of mental stress granularity from long-term ECG recordings using novel complexity analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Area of Science:

  • Fluid dynamics
  • Nonlinear dynamics
  • Signal processing

Background:

  • Experimental velocity signals from evolutive flows contain complex dynamics.
  • Vortex dynamics significantly influence fluid flow characteristics.
  • Characterizing time series complexity is crucial for understanding underlying processes.

Purpose of the Study:

  • To extract dominant velocity components from experimental signals using a wavelet method.
  • To characterize the complexity of time series generated by vortex dynamics.
  • To reproduce spectral and complex properties of experimental signals.

Main Methods:

  • Wavelet analysis for extracting velocity components from experimental data.
  • Data compression and entropy diffusion for time series complexity characterization.

Related Experiment Videos

  • Harmonic time dependence with fluctuating frequency to model signal properties.

    • Main Results:

    • Wavelet analysis identified time series exhibiting weakly chaotic behavior.
    • The process showed vanishing Kolmogorov-Sinai entropy and power-law information growth.
    • Reproduced experimental signal's spectral and complex properties by modeling fluctuations at the stationary-nonstationary border.

    Conclusions:

    • Vortex dynamics in evolutive flows can be characterized as a weakly chaotic process.
    • The proposed modeling approach successfully replicates experimental signal characteristics.
    • Complexity arising from fluctuating frequencies at the stationary-nonstationary border is significant.