用于表示、压缩和可视化流体流动图像和测速数据的非线性模型

R. M. Ford, R. N. Strickland
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引用次数: 6

摘要

采用非线性相位肖像来表示粒子跟踪实验生成的标量流图像的流线。根据临界点特性将流场分解为简单的分量流。假设速度分量为泰勒级数模型,并考虑局部临界点和全局流场特性计算模型系数。提出了一种复杂流的合并和分割方法,该方法将相邻临界点区域的模式进行合并和建模。利用泰勒级数模型导出的正交多项式,将这些概念扩展到向量场数据的压缩。提出了一种临界点格式和分块变换。它们被应用于粒子图像测速实验中测量的速度场,并由计算机模拟生成
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Nonlinear models for representation, compression, and visualization of fluid flow images and velocimetry data
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.<>
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