Flow Visualization Based on A Derived Rotation Field
Flow Visualization Based on A Derived Rotation Field
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DOI：
10.2352/issn.2470-1173.2016.1.vda-478
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Lei Zhang;Guoning Chen;R. Laramee;D. Thompson;A. Sescu
中科院分区：
文献类型：
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作者：
Lei Zhang;Guoning Chen;R. Laramee;D. Thompson;A. Sescu
我们确定和调查的Φ字段-一个派生的流属性字段，其值在一个给定的空间位置是由在该点开始的积分曲线。具体地，我们对沿积分曲线沿着的两个连续点处的速度矢量之间的角度差进行积分，以获得Φ场值。Φ场及其梯度幅值的重要性质|∇Φ|领域进行了研究。特别是，我们表明，在导出的Φ场的图案一般是根据一个不等式性质的流动方向对齐。此外，我们还将Φ场与其他一些属性场进行了比较，并讨论了它与LCS和尖点状播种结构等流特征的关系。此外，我们引入了一个计算Φ场及其梯度场的统一框架，并使用Φ场和|∇Φ|场的一些流动可视化和探索任务，包括积分曲线滤波，种子生成和流域分割。我们表明，这些任务可以更有效地进行基于Φ字段中编码的信息。
We identify and investigate the Φ field – a derived flow attribute field whose value at a given spatial location is determined by the integral curve initiated at the point. Specifically, we integrate the angle difference between the velocity vectors at two consecutive points along the integral curve to get the Φ field value. Important properties of the Φ field and its gradient magnitude |∇Φ| field are studied. In particular, we show that the patterns in the derived Φ field are generally aligned with the flow direction based on an inequality property. In addition, we compare the Φ field with some other attribute fields and discuss its relation with a number of flow features, such as LCS and cusp-like seeding structures. Furthermore, we introduce a unified framework for the computation of the Φ field and its gradient field, ∇Φ, and employ the Φ field and |∇Φ| field to a number of flow visualization and exploration tasks, including integral curve filtering, seeds generation and flow domain segmentation. We show that these tasks can be conducted more efficiently based on the information encoded in the Φ field.