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Evolution Surfaces for Spatiotemporal Visualization of Vortex Features

机译:涡面特征时空可视化的演化曲面

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摘要

Turbulent fluid flow data are often 4-D, spatially and temporally complex, and require specific techniques for visualization. Common visualization techniques neglect the temporal aspect of this data, limiting the ability to convey feature motion, or offering the user a complicated visualization. To remedy this, we present an approach-evolution surfaces-focused on the spatiotemporal rendering of user-selected flow features (i.e., vortices). By abstracting the spatial representation of these features, the approach renders their spatiotemporal behavior with reduced visual complexity. The behavior of vortex features is presented as surfaces, with textures indicating properties of motion and evolution events (e.g., bifurcation and amalgamation) represented by the surface topology. We evaluated the approach on two data sets generated from empirical measurement and computational simulation (Re = 28 000 and Re = 1200, respectively). Our approach's focus on handling evolution events makes it capable of visualizing higher Reynolds number (Re) flows than other surface-based techniques. This approach has been assessed by fluid dynamicists to assert the validity for flow analysis. Evolution surfaces offer a compact visualization of spatiotemporal vortex behaviors, opening potential avenues for exploration and analysis of fluid flows.
机译:湍流数据通常在空间和时间上是4D的,需要可视化的特定技术。常见的可视化技术忽略了此数据的时间方面,从而限制了传递特征运动的能力,或者为用户提供了复杂的可视化。为了解决这个问题,我们提出了一种方法进化表面,重点关注用户选择的流动特征(即涡旋)的时空渲染。通过抽象化这些特征的空间表示,该方法以降低的视觉复杂性呈现了它们的时空行为。涡流特征的行为表示为表面,纹理表示由表面拓扑表示的运动和演化事件(例如,分叉和合并)的属性。我们对根据经验测量和计算模拟生成的两个数据集(分别为Re = 28 000和Re = 1200)评估了该方法。与其他基于表面的技术相比,我们的方法着重于处理演化事件,使其能够可视化更高的雷诺数(Re)流。流体动力学专家已经对该方法进行了评估,以断言流量分析的有效性。演化表面提供了时空涡旋行为的紧凑可视化,为探索和分析流体流动开辟了潜在的途径。

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