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Binary fluids under steady shear in three dimensions.

K Stratford1, J-C Desplat, P Stansell

  • 1SUPA, School of Physics, The University of Edinburgh, JCMB The King's Buildings, Mayfield Road, Edinburgh, EH9 3JZ, United Kingdom.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 13, 2007
PubMed
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Simulations show binary fluid mixtures reach a steady state under shear, contrary to some theories. Finite correlation lengths were observed in 3D, with scaling exponents similar to 2D at high Reynolds numbers.

Area of Science:

  • Fluid dynamics
  • Computational physics
  • Statistical mechanics

Background:

  • Understanding the behavior of binary fluid mixtures under shear is crucial for various applications.
  • Theoretical models have proposed different scenarios for the steady state of such systems.
  • Previous studies in two dimensions (2D) provided initial insights into scaling behaviors.

Purpose of the Study:

  • To simulate the steady shearing of a three-dimensional (3D) binary fluid mixture with full hydrodynamics.
  • To investigate whether a dynamical steady state is achieved and characterize its properties.
  • To compare observed scaling exponents with theoretical predictions and previous 2D findings.

Main Methods:

  • Lattice Boltzmann method for simulating fluid dynamics.

Related Experiment Videos

  • Three-dimensional simulations of binary fluid mixtures.
  • Analysis of correlation lengths and scaling exponents at different Reynolds numbers.

    • Main Results:

    • A dynamical steady state was attained, contradicting some theoretical expectations.
    • Finite correlation lengths were observed in all three spatial directions.
    • Apparent scaling exponents at moderately high Reynolds numbers matched previous 2D results.

    Conclusions:

    • The study demonstrates a stable steady state for 3D binary fluid mixtures under shear.
    • A potential crossover to different behavior at low Reynolds numbers suggests the need for further investigation.
    • Accessing low Reynolds number regimes in 3D requires significant computational resources.