An importance sampling vortex particle method for turbulence visualization simulation in maritime simulators

Physically-based turbulence modeling significantly enhances the realism of maritime simulator scenarios. We propose a novel importance sampling vortex particle method to simulate turbulent details within the SPH framework. The core of our method is a Monte Carlo estimator that approximates the global vorticity of the fluid system, addressing the computational cost associated with the global iteration of vortex particles. By constructing a probability function for importance sampling of vortex particles, we effectively suppress high-frequency variance fluctuations and improve simulation accuracy. Experimental results demonstrate that our importance sampling vortex particle method effectively reduces vorticity field variance by about 27% compared to uniform sampling, thereby improving simulation accuracy and producing visually prominent turbulent motion in the fluids. This study provides a theoretical reference for realistic ocean scene simulation in maritime simulators.