Robust and Efficient SPH Simulation for High-speed Fluids with the Dynamic Particle Partitioning Method

Z. Zheng, Yang Gao, Shuai Li, Hong Qin, A. Hao
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引用次数: 1

Abstract

In this paper, our research efforts are devoted to the efficiency issue of the SPH simulation when the ratio of velocities among fluid particles is large. Specifically, we introduce a k-means clustering method into the SPH framework to dynamically partition fluid particles into two disjoint groups based on their velocities, we then use a two-scale time step scheme for these two types of particles. The smaller time steps are for particles with higher speed in order to preserve temporal details and guarantee the numerical stability. In contrast, the larger time steps are used for particles with smaller speeds to reduce the computational expense, and both types of particles are tightly coupled in the simulation. We conduct various experiments which have manifested the advantages of our methods over the conventional SPH technique and its new variants in terms of efficiency and stability. CCS Concepts •Computing methodologies → Animation; Physical simulation;
基于动态粒子划分方法的高速流体SPH鲁棒高效仿真
本文主要研究流体颗粒间速度比较大时SPH模拟的效率问题。具体而言,我们在SPH框架中引入k-means聚类方法,根据流体颗粒的速度动态划分为两个不相关的组,然后对这两种类型的颗粒使用双尺度时间步长格式。为了保留时间细节和保证数值稳定性,对速度较高的粒子采用较小的时间步长。而对于速度较小的粒子,则采用较大的时间步长来减少计算开销,并且在模拟中两种粒子是紧密耦合的。我们进行了各种实验,证明了我们的方法在效率和稳定性方面优于传统的SPH技术及其新变体。•计算方法→动画;物理模拟;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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