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Related Experiment Videos

Bistability in bubble formation.

Eduardo Colli1, Viviane S M Piassi, Alberto Tufaile

  • 1Instituto de Matemática e Estatística, Universidade de São Paulo, R. do Matão 1010, CEP 05508-090 São Paulo, Brazil. colli@ime.usp.br

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 9, 2005
PubMed
Summary

Researchers studied bubble train dynamics, observing period-adding cascades and bistability. A mathematical model successfully replicated these experimental findings, confirming complex fluid behaviors.

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Period adding cascades: experiment and modeling in air bubbling.

Chaos (Woodbury, N.Y.)·2012

Area of Science:

  • Fluid dynamics
  • Nonlinear dynamics
  • Chaos theory

Background:

  • Bubble trains generated from nozzles exhibit complex dynamical behaviors.
  • Understanding these dynamics is crucial for various fluidic applications.

Purpose of the Study:

  • To experimentally investigate the time intervals of bubble trains.
  • To model and understand the observed nonlinear phenomena, including period-adding cascades and bistability.
  • To validate a mathematical model against experimental data.

Main Methods:

  • Experimental data collection on bubble train time intervals using air flow rate as a control parameter.
  • Systematic variation of hose length to generate bifurcation diagrams.
  • Construction and analysis of a two-parameter family of one-dimensional maps.

Related Experiment Videos

  • Comparison of model predictions with experimental observations.
  • Main Results:

    • Experimental observation of period-adding cascades and other dynamical phenomena in bubble trains.
    • Successful qualitative matching of experimental bifurcation diagrams with a constructed one-dimensional map model.
    • Experimental confirmation of bistability, where two coexisting attractors were observed.

    Conclusions:

    • The study successfully links experimental bubble train dynamics to a mathematical model.
    • The model accurately predicts complex behaviors like period-adding cascades and bistability.
    • Bistability in bubble train generation is experimentally confirmed and theoretically modeled.