分析增强的基于颗粒的流动可视化

Lieyu Shi, Lei Zhang, Wei-Ju Cao, Guoning Chen
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引用次数: 5

摘要

基于粒子的流体模拟(PFS)是一种无网格的方法,如光滑粒子流体动力学(SPH)和基于位置的流体(PBF),用于研究不同情况下液体的行为,已广泛应用于天体物理学、机械工程和生物医学工程等各个领域。由于PFS的无网格特性,大多数针对基于网格的数据开发的分析技术都需要适应于PFS数据的分析。在这项工作中,我们研究了一些流动分析技术及其对PFS数据分析的扩展,包括FTLE方法,雅可比分析和属性累积框架。特别地,我们将这些分析技术应用于自由表面流体。我们证明,这些分析可以揭示一些有趣的潜在流动模式,否则将很难看到通过许多PFS模拟流动与不同的参数和边界设置。此外,我们指出,执行这些分析的原位分析框架可以潜在地用于指导自适应PFS在模拟期间将计算和存储功率分配到感兴趣的区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis Enhanced Particle-based Flow Visualization
Particle-based fluid simulation (PFS), such as Smoothed Particle Hydrodynamics (SPH) and Position-based Fluid (PBF), is a mesh-free method that has been widely used in various fields, including astrophysics, mechanical engineering, and biomedical engineering for the study of liquid behaviors under different circumstances. Due to its meshless nature, most analysis techniques that are developed for mesh-based data need to be adapted for the analysis of PFS data. In this work, we study a number of flow analysis techniques and their extension for PFS data analysis, including the FTLE approach, Jacobian analysis, and an attribute accumlation framework. In particular, we apply these analysis techniques to free surface fluids. We demonstrate that these analyses can reveal some interesting underlying flow patterns that would be hard to see otherwise via a number of PFS simulated flows with different parameters and boundary settings. In addition, we point out that an in-situ analysis framework that performs these analyses can potentially be used to guide the adaptive PFS to allocate the computation and storage power to the regions of interest during the simulation.
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