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Tracking and visualizing turbulent 3D features

机译:跟踪和可视化湍流3D特征

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Visualizing 3D time-varying fluid datasets is difficult because of the immense amount of data to be processed and understood. These datasets contain many evolving amorphous regions, and it is difficult to observe patterns and visually follow regions of interest. In this paper, we present a technique which isolates and tracks full-volume representations of regions of interest from 3D regular and curvilinear computational fluid dynamics datasets. Connected voxel regions ("features") are extracted from each time step and matched to features in subsequent time steps. Spatial overlap is used to determine the matching. The features from each time step are stored in octree forests to speed up the matching process. Once the features have been identified and tracked, the properties of the features and their evolutionary history can be computed. This information can be used to enhance isosurface visualization and volume rendering by color coding individual regions. We demonstrate the algorithm on four 3D time-varying simulations from ongoing research in computational fluid dynamics and show how tracking can significantly improve and facilitate the processing of massive datasets.
机译:可视化3D时变流体数据集非常困难,因为要处理和理解的数据量很大。这些数据集包含许多不断演变的无定形区域,很难观察到图案并在视觉上跟踪感兴趣的区域。在本文中,我们提出了一种从3D规则和曲线计算流体动力学数据集中隔离并跟踪感兴趣区域的完整表示形式的技术。从每个时间步中提取相连的体素区域(“特征”),并在随后的时间步中将其与特征匹配。空间重叠用于确定匹配。每个时间步骤中的要素都存储在八叉树林中,以加快匹配过程。一旦识别并跟踪了特征,就可以计算出特征及其演化历史。通过对各个区域进行颜色编码,此信息可用于增强等值面可视化和体积渲染。我们在正在进行的计算流体动力学研究中对四个3D时变仿真进行了演示,并展示了跟踪如何显着改善和促进海量数据集的处理。

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