Scalar features in time-dependent fluid flow are traditionally visualized using 3D representation, and their topology changes over time are often conveyed with abstract graphs. Using such techniques, however, the structural details of feature separation and the temporal evolution of features undergoing topological changes are difficult to analyze. In this paper, we propose a novel approach for the spatio-temporal visualization of feature separation that segments feature volumes into regions with respect to their contribution to distinct features after separation. To this end, we employ particle-based feature tracking to find volumetric correspondences between features at two different instants of time. We visualize this segmentation by constructing mesh boundaries around each volume segment of a feature at the initial time that correspond to the separated features at the later time. To convey temporal evolution of the partitioning within the investigated time interval, we complement our approach with spatio-temporal separation surfaces. For the application of our approach to multiphase flow, we additionally present a feature-based corrector method to ensure phase-consistent particle trajectories. The utility of our technique is demonstrated by application to two-phase (liquid-gas) and multi-component (liquid-liquid) flows where the scalar field represents the fraction of one of the phases.
For the visualization in multiphase flow, we use a corrector method to ensure that the advected particles remain in the given phase during tracing. Related to this problem are approaches for surface tracking. Stam @cite_30 proposed a method for the computation of interface velocities to properly translate surfaces. Bojsen- @cite_31 developed a method for tracking surfaces undergoing topology changes, without prior information on the underlying physics. In the work by @cite_24 , Lagrangian transport is used for correct displacement interpolation. @cite_6 optimize the transportation in terms of Wasserstein distances, which allows for efficient shape transformation. In our work, we analyze the evolution of volumes, and computing Wasserstein distances in this case would be computationally prohibitive and also would not guarantee physically correct correspondences.
@cite_30 @cite_31 @cite_6 @cite_24
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In this article we derive an equation for the velocity of an arbitrary time-evolving implicit surface. Strictly speaking, only the normal component of the velocity is unambiguously defined. This is because an implicit surface does not have a unique parametrization. However, by enforcing a constraint on the evolution of the normal field we obtain a unique tangential component. We apply our formulas to surface tracking and to the problem of computing velocity vectors of a motion blurred blobby surface. Other possible applications are mentioned at the end of the article. We present a method for recovering a temporally coherent, deforming triangle mesh with arbitrarily changing topology from an incoherent sequence of static closed surfaces. We solve this problem using the surface geometry alone, without any prior information like surface templates or velocity fields. Our system combines a proven strategy for triangle mesh improvement, a robust multi-resolution non-rigid registration routine, and a reliable technique for changing surface mesh topology. We also introduce a novel topological constraint enforcement algorithm to ensure that the output and input always have similar topology. We apply our technique to a series of diverse input data from video reconstructions, physics simulations, and artistic morphs. The structured output of our algorithm allows us to efficiently track information like colors and displacement maps, recover velocity information, and solve PDEs on the mesh as a post process. Interpolation between pairs of values, typically vectors, is a fundamental operation in many computer graphics applications. In some cases simple linear interpolation yields meaningful results without requiring domain knowledge. However, interpolation between pairs of distributions or pairs of functions often demands more care because features may exhibit translational motion between exemplars. This property is not captured by linear interpolation. This paper develops the use of displacement interpolation for this class of problem, which provides a generic method for interpolating between distributions or functions based on advection instead of blending. The functions can be non-uniformly sampled, high-dimensional, and defined on non-Euclidean manifolds, e.g., spheres and tori. Our method decomposes distributions or functions into sums of radial basis functions (RBFs). We solve a mass transport problem to pair the RBFs and apply partial transport to obtain the interpolated function. We describe practical methods for computing the RBF decomposition and solving the transport problem. We demonstrate the interpolation approach on synthetic examples, BRDFs, color distributions, environment maps, stipple patterns, and value functions.