SPH仿真的可视化调试

S. Reinhardt, M. Huber, Otilia Dumitrescu, M. Krone, B. Eberhardt, D. Weiskopf
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引用次数: 7

摘要

平滑粒子流体动力学(SPH)是一种流行的无网格、基于粒子的流体模拟方法,具有广泛的应用。SPH有几个数值变体,以及各种模型,如边界条件、可压缩性或不可压缩性和表面张力。这些模型的不同组合导致在模拟过程中出现不同的效果,它们的分析是流体力学的一个关键挑战。在本文中,我们通过提供模拟的可视化调试应用程序来解决这一挑战,该应用程序允许用户评估模型的属性并检测可能的计算错误。我们的多视图应用程序结合了粒子的交互式三维可视化和信息可视化领域的非空间可视化,即散点图和平行坐标图。因此,我们的可视化调试环境可以对多维仿真属性进行定量分析,包括有助于仿真过程的内部和物理属性。所有视图都支持刷图和链接,即在图中选择感兴趣的值范围在3D视图中直接可见,反之,在3D视图中选择粒子会突出显示图中相应的数据点。由于典型的SPH模拟具有大量的数据点,我们采用随机子采样来减少非空间视图中的视觉杂波并加快渲染速度。我们讨论了流体模拟可视化调试的四个实际用例,展示了我们的可视化调试环境如何有助于识别代码错误并增加对仿真模型的理解。我们还展示了耦合视图的组合如何揭示内部细节,从而有助于改善模拟结果。
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Visual Debugging of SPH Simulations
Smoothed particle hydrodynamics (SPH) is a popular mesh-free, particle-based fluid simulation approach for a wide range of applications. There are several numerical variants of SPH along with a variety of models for aspects such as boundary conditions, compressibility or incompressibility, and surface tension. Different combinations of these models lead to varying effects that occur during simulation, and their analysis is a critical challenge for fluid mechanics. In this paper, we address this challenge by presenting a visual debugging application for simulations, which allows users to evaluate the properties of the models and to detect possible computational errors. Our multi-view application uses a combination of interactive 3D visualization of the particles and non-spatial visualizations from the field of information visualization, namely scatter plots and parallel coordinates plots. Our visual debugging environment thus enables a quantitative analysis of the multidimensional simulation attributes, including internal and physical properties contributing to the simulation process. All views support brushing and linking, that is, selections of interesting value ranges in the plots are directly visible in the 3D view and, conversely, the selection of particles in the 3D view highlights the corresponding data points in the plots. Since typical SPH simulations come with large numbers of data points, we employ stochastic subsampling to reduce visual clutter in the non-spatial views and accelerate the rendering speed. We discuss four real-world use cases for visual debugging of fluid simulations that showcase how our visual debugging environment is instrumental for identify code errors and increases the understanding of the simulation models. We also show how the combination of coupled views can reveal internal details, thus serving to improve simulation results.
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