State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties

Bujack, Roxana; Yan, Lin; Hotz, Ingrid; Garth, Christoph; Wang, Bei

doi:10.1111/cgf.14037

Title: State of the Art in Time‐Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties

Journal Article · 17 July 2020 · Computer Graphics Forum

DOI: https://doi.org/10.1111/cgf.14037 · OSTI ID:1642326

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Los Alamos National Laboratory USA
Scientific Computing and Imaging Institute University of Utah USA
Scientific Visualization Group Linköpings University Sweden
University of Kaiserslautern Germany

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.

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Sponsoring Organization:: USDOE

OSTI ID:: 1642326

Journal Information:: Computer Graphics Forum, Journal Name: Computer Graphics Forum Journal Issue: 3 Vol. 39; ISSN 0167-7055

Publisher:: Wiley-BlackwellCopyright Statement

Country of Publication:: Netherlands

Language:: English

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