• DocumentCode
    1526045
  • Title

    Feature extraction of separation and attachment lines

  • Author

    Kenwright, David N. ; Henze, Chris ; Levit, Creon

  • Author_Institution
    NASA Ames Res. Center, Moffett Field, CA, USA
  • Volume
    5
  • Issue
    2
  • fYear
    1999
  • Firstpage
    135
  • Lastpage
    144
  • Abstract
    Separation and attachment lines are topologically significant curves that exist on 2D surfaces in 3D vector fields. Two algorithms are presented, one point-based and one element-based, that extract separation and attachment lines using eigenvalue analysis of a locally linear function. Unlike prior techniques based on piecewise numerical integration, these algorithms use robust analytical tests that can be applied independently to any point in a vector field. The feature extraction is fully automatic and suited to the analysis of large-scale numerical simulations. The strengths and weaknesses of the two algorithms are evaluated using analytic vector fields and also results from computational fluid dynamics (CFD) simulations. We show that both algorithms detect open separation lines-a type of separation that is not captured by conventional vector field topology algorithms
  • Keywords
    computational fluid dynamics; computational geometry; data visualisation; eigenvalues and eigenfunctions; feature extraction; flow visualisation; 2D surfaces; 3D vector fields; attachment lines; computational fluid dynamics; eigenvalue analysis; element-based algorithm; feature extraction; locally linear function; numerical simulation; point-based algorithm; separation lines; three dimensional vector fields; topologically significant curves; vector field; visualization; Algorithm design and analysis; Computational fluid dynamics; Computational modeling; Eigenvalues and eigenfunctions; Feature extraction; Large-scale systems; Numerical simulation; Robustness; Testing; Vectors;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/2945.773805
  • Filename
    773805