State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties. (18th July 2020)

• Record Type: Journal Article
• Authors: Bujack, Roxana; Yan, Lin; Hotz, Ingrid; Garth, Christoph; Wang, Bei
• Is Part Of: Computer graphics forum. Volume 39:Number 3(2020)
• Page Start: 811
• Page End: 835
• Publication Date: 2020-07-18
• Subjects: Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.14037
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: We present a state‐of‐the‐art report on time‐dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time‐independent to time‐dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time‐dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.