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

Abstract

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.