Representing and Visualizing Fluid Flow Images and Velocimetry Data by Nonlinear Dynamical Systems

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.