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Particles on demand for flows with strong discontinuities.

N G Kallikounis1, B Dorschner1, I V Karlin1

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This study enhances the particles-on-demand method for simulating compressible flows. The modified approach improves stability and conservation, outperforming existing methods in complex scenarios.

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Area of Science:

  • Computational fluid dynamics
  • Kinetic theory
  • High-performance computing

Background:

  • Compressible flows with strong discontinuities pose simulation challenges.
  • Existing lattice Boltzmann-like methods have limitations in accuracy and conservation.
  • The particles-on-demand formulation offers a kinetic theory-based approach.

Purpose of the Study:

  • To modify and enhance the particles-on-demand method for simulating compressible flows.
  • To improve the stability, accuracy, and conservation properties of the simulation method.
  • To validate the enhanced method against challenging benchmark problems.

Main Methods:

  • Applied regularization using Grad's projection and reference frame transformations.
  • Implemented a finite-volume scheme for precise mass, momentum, and energy conservation.
  • Validated the modified particles-on-demand method using 1D and 2D compressible flow benchmarks.

Main Results:

  • The modified particles-on-demand method demonstrated excellent performance in simulating complex flows.
  • Successfully handled strong discontinuities in density, pressure, and velocity.
  • Validated against hypersonic, near-vacuum, Richtmyer-Meshkov instability, double Mach reflection, and astrophysical jet scenarios.

Conclusions:

  • The enhanced particles-on-demand method provides a robust and accurate tool for compressible flow simulations.
  • The modifications overcome limitations of previous lattice Boltzmann-like approaches.
  • This method shows significant potential for diverse applications in fluid dynamics research.