Work

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

Year: 2025

Type: article

Abstract: 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.

Source: Scientific Reports

DOI: 10.1038/s41598-025-22144-6

Authors: Tianhui Zhu, Hongxiang Ren, Rui Tao, Dejian Wei, Pinliang Xie

Institutions: Dalian Maritime University, Peking University

Language: English

Topic: Fluid Dynamics Simulations and Interactions

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,690

Funder: Guangxi Key Research and Development Program