Extracting Features from Time-Dependent Vector Fields Using Internal Reference Frames

• Published in: Computer graphics forum Vol. 33; no. 3; pp. 21 - 30
• Main Authors: Bhatia, H., Pascucci, V., Kirby, R. M., Bremer, P.-T.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.06.2014
• Subjects: Algorithms; Analysis; Categories and Subject Descriptors (according to ACM CCS); Computer graphics; Fluid dynamics; Fluid flow; Frames; I.6.6 [Computing Methodologies]: Simulation And Modeling-Simulation Output Analysis; Image processing systems; Studies; Transforms; Turbulent combustion; Turbulent flow; Unsteady
• ISSN: 0167-7055; 1467-8659
• DOI: 10.1111/cgf.12358

Extracting features from complex, time‐dependent flow fields remains a significant challenge despite substantial research efforts, especially because most flow features of interest are defined with respect to a given reference frame. Pathline‐based techniques, such as the FTLE field, are complex to implement and resource intensive, whereas scalar transforms, such as λ2, often produce artifacts and require somewhat arbitrary thresholds. Both approaches aim to analyze the flow in a more suitable frame, yet neither technique explicitly constructs one. This paper introduces a new data‐driven technique to compute internal reference frames for large‐scale complex flows. More general than uniformly moving frames, these frames can transform unsteady fields, which otherwise require substantial processing of resources, into a sequence of individual snapshots that can be analyzed using the large body of steady‐flow analysis techniques. Our approach is simple, theoretically well‐founded, and uses an embarrassingly parallel algorithm for structured as well as unstructured data. Using several case studies from fluid flow and turbulent combustion, we demonstrate that internal frames are distinguished, result in temporally coherent structures, and can extract well‐known as well as notoriously elusive features one snapshot at a time.