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Implicit large eddy simulation of shock-driven material mixing.

F F Grinstein1, A A Gowardhan, J R Ristorcelli

  • 1Los Alamos National Laboratory, , Los Alamos NM 87545, USA.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|October 23, 2013
PubMed
Summary
This summary is machine-generated.

Even with incomplete data, small-scale turbulence significantly impacts large-scale flow behavior. This study investigates how initial conditions affect turbulent mixing in shock-driven flows.

Keywords:
implicit large eddy simulationlarge eddy simulationshock driventurbulent mixing

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Area of Science:

  • Fluid Dynamics
  • Computational Science
  • Turbulence Research

Background:

  • Under-resolved simulations are common in complex turbulent flows.
  • The influence of subgrid scales on resolved scales remains an open question.
  • Predictability in turbulent mixing is crucial for practical applications.

Purpose of the Study:

  • To investigate the impact of unresolved spatial scales on resolved flow dynamics.
  • To analyze predictability issues in implicit large eddy simulations of turbulent mixing.
  • To determine the effect of initial conditions on shock-driven turbulent mixing.

Main Methods:

  • Utilizing implicit large eddy simulation (ILES) for under-resolved flows.
  • Focusing on shock-driven turbulent mixing in a planar shock-tube configuration.
  • Analyzing the effects of resolved spectral content and interfacial morphology.

Main Results:

  • Filtered-out and subgrid scales can significantly alter large-scale flow evolution.
  • Initial condition morphology and spectral content influence transitional and late-time mixing.
  • Predictability is sensitive to the fidelity of resolved scales and initial states.

Conclusions:

  • Unresolved scales play a critical role in turbulent flow behavior.
  • Careful consideration of initial conditions is necessary for accurate turbulent mixing predictions.
  • This research advances the understanding of under-resolved turbulence modeling.