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

被引：0
|
作者：
Wang, Xiaokun [1 ,2 ]
Liu, Sinuo [1 ]
Ban, Xiaojuan [1 ]
Xu, Yanrui [1 ]
Zhou, Jing [1 ]
Kosinka, Jiri [2 ]
机构：
[1] Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, Beijing, Peoples R China
[2] Univ Groningen, Bernoulli Inst, Groningen, Netherlands
来源：
2020 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES WORKSHOPS (VRW 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
Computing methodologies; Computer graphics; Animation; Physical simulation;
D O I：
10.1109/VRW50115.2020.00-96
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose a novel turbulence refinement method based on the Rankine vortex model for SPH (smoothed particle hydrodynamics) simulations. Surface details are enhanced by recovering the energy lost in the rotational degrees of freedom 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 neighbours. 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.
引用
收藏
页码：657 / 658
页数：2
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