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Correlation time and diffusion coefficient imaging: application to a granular flow system.

A Caprihan1, J D Seymour

  • 1New Mexico Resonance, Albuquerque, New Mexico 87108, USA.

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|April 28, 2000
PubMed
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A new pulsed-field-gradient NMR method quantifies particle motion in granular flows. It measures velocity autocorrelation functions to determine diffusion coefficients and correlation times in complex systems.

Area of Science:

  • Physics
  • Chemical Engineering
  • Materials Science

Background:

  • Granular flows exhibit complex dynamics, often modeled by Ornstein-Uhlenbeck processes.
  • Characterizing particle motion, including velocity autocorrelation functions, is crucial for understanding transport phenomena.
  • Traditional methods may struggle to resolve spatially varying dynamics in such systems.

Purpose of the Study:

  • To present a parametric method for spatially resolved measurements of velocity autocorrelation functions.
  • To apply this method to a granular flow system using pulsed-field-gradient NMR.
  • To distinguish and quantify multiple correlation times present in particle motion.

Main Methods:

  • Utilized a parametric method to express velocity autocorrelation functions as a sum of exponentials.

Related Experiment Videos

  • Employed pulsed-field-gradient NMR with three gradient pulse sequences of varying motion sensitivity.
  • Measured time-dependent apparent diffusion coefficients and calculated correlation times and diffusion coefficients from images.

    • Main Results:

    • Successfully applied the method to a granular flow of oil-filled spheres in a rotating cylinder.
    • Determined the axial diffusion coefficient (5.5 x 10^-6 m^2/s), correlation time (3 ms), and granular temperature (1.8 x 10^-3 m^2/s^2) at the free surface.
    • Demonstrated the ability to distinguish a range of correlation times present in particle motion.

    Conclusions:

    • The presented parametric NMR method enables spatially resolved characterization of velocity autocorrelation functions in granular flows.
    • The findings provide quantitative insights into particle transport dynamics in this specific system.
    • The method's applicability extends to studying transport in turbulent and porous media flows.