Robust turbulence simulation for particle-based fluids using the Rankine vortex model

Xiaokun Wang, Sinuo Liu, Xiaojuan Ban*, Yanrui Xu, Jing Zhou, Jiri Kosinka

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
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We propose a novel turbulence refinement method based on the Rankine vortex model for smoothed particle hydrodynamics (SPH) simulations. Surface details are enhanced by recovering the energy lost due to the lack of the rotation of SPH particles. The Rankine vortex model is used to convert the diffused and stretched angular kinetic energy of particles to the linear kinetic energy of their neighbors. In previous vorticity-based refinement methods, adding more energy than required by the viscous damping effect leads to instability. In contrast, our model naturally prevents the positive feedback effect between the velocity and vorticity fields since the vortex model is designed to alter the velocity without introducing external sources. Experimental results show that our method can recover missing high-frequency details realistically and maintain convergence in both static and highly dynamic scenarios.

Original languageEnglish
Pages (from-to)2285-2298
Number of pages14
JournalVisual computer
Issue number10-12
Early online date4-Aug-2020
Publication statusPublished - Oct-2020


  • Fluid simulation
  • Vortex model
  • Turbulence
  • Smoothed particle hydrodynamics
  • SPH

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