Representing and Visualizing Fluid Flow Images and Velocimetry Data by Nonlinear Dynamical Systems
Representing and Visualizing Fluid Flow Images and Velocimetry Data by Nonlinear Dynamical Systems
复制标题
通过非线性动力系统表示和可视化流体流动图像和测速数据
DOI：
10.1006/gmip.1995.1040
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发表时间：
1995
期刊：
影响因子：
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通讯作者：
R. N. Strickland
中科院分区：
文献类型：
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作者：
R. M. Ford;R. N. Strickland
摘要 采用非线性相图来表示粒子追踪实验生成的标量流图像的流线。根据临界点行为，流场被分解为简单的分量流。速度分量采用泰勒级数模型，并通过考虑局部临界点和全局流场行为来计算模型系数。提出了复杂流的合并和分割过程，其中相邻临界点区域的模式被组合和建模。通过使用从泰勒级数模型导出的正交多项式，这些概念被扩展到矢量场数据的压缩。提出了临界点方案和块变换。它们应用于粒子图像测速实验中测量的速度场，并通过计算机模拟生成。压缩比范围为 15:1 至 100:1。
Abstract Nonlinear phase portraits are employed to represent the streamlines of scalar flow images generated by particle tracing experiments. The flow fields are decomposed into simple component flows based on the critical point behavior. A Taylor series model is assumed for the velocity components, and the model coefficients are computed by considering both local critical point and global flow field behavior. A merge and split procedure for complex flows is presented, in which patterns of neighboring critical point regions are combined and modeled. The concepts are extended to the compression of vector field data by using orthogonal polynomials derived from the Taylor series model. A critical point scheme and a block transform are presented. They are applied to velocity fields measured in particle image velocimetry experiments and generated by computer simulations. Compression ratios ranging from 15:1 to 100:1 are achieved.