1 Feature Extraction and Visualization of Flow Fields State-of-the-Art Report Feature Extraction and Visualization of Flow Fields Frits H. Post and Benjamin Vrolijk Delft University of Technology The Netherlands visualisation.tudelft.nl Helwig Hauser, Robert S. Laramee, Helmut Doleisch VRVis Research Center Austria Part 2:Feature-Based FlowViz Part 1: Visualization of Flow Fields

2 Feature Extraction and Visualization of Flow Fields Flow Visualization STAR Overview Part 1: Visualization of Flow Fields  Introduction to Flow Visualization (FlowViz)  Direct FlowViz  Texture-Based FlowViz  Geometric FlowViz Part 2: Feature-Based FlowViz

3 Feature Extraction and Visualization of Flow Fields The FlowViz Job Goal: communicating FlowViz data:  data representing fluid/gas flow, i.e. vector field data (magnitude + direction)  not just scalar data  visualization is a very high bandwidth channel User Goals:  obtain overview of vector field  present characteristics  identify and investigate details and features

4 Feature Extraction and Visualization of Flow Fields Computational vs. Experimental and Empirical FlowVis Computational FlowVis -using computers for FlowVis  data resulting from flow simulation, measurements, or flow modelling, e.g., computational fluid dynamics (CFD)  computer-generated images and animations, often mimicking experimental FlowVis Visualization of actual fluids, e.g. water and air  dye injection  interferometry  Schlieren/shadows  flow topology graphs  etc.

5 Feature Extraction and Visualization of Flow Fields FlowVis Data vs. Data Acquisition Data from Simulation: FOR EACH cell in (irregular) grid:  compute flow direction  compute flow magnitude (explicitly or implicitly)  compute pressure (à la Navier-Stokes equations)  further attributes Data from measurements: FOR EACH location of a (regular) grid:  flow direction (reconstructed)  measure flow magnitude Data from modelling:  Vector Field represented by analytic function  Flow direction and magnitude a function of location (and time)

6 Feature Extraction and Visualization of Flow Fields FlowViz Data Characterized by Many Dimensions Spatial dimensions:  2D (planar flow, simplified or synthetic)  2.5D (boundary flow, flow on surface)  3D (real-world flow) Temporal dimension:  steady flow -1 time step (or instantaneous flow)  time-dependent flow -multiple time steps (turbulent, real- world)  caution is advised in the context of animation Data dimensions:  velocity  temperature  pressure  and many more...

7 Feature Extraction and Visualization of Flow Fields Direct vs. Geometric vs. Feature-Based FlowViz focus on featuresmore detailed viewOverview, 1st impression

8 Feature Extraction and Visualization of Flow Fields FlowViz Fundamentals Flow Data from simulation: vector field represented as samples: v p,t (+ reconstruction) v(p,t) = dp/dt; p,v  R n, t  R Flow Integration  over Grids: Cartesian, curvi-linear, unstructured  integration techniques: Euler and Runge-Kutta  point location (which cell p lies in) and neighbor searching  flow reconstruction within a cell (à la interpolation)  computation of derived data p(s) = p 0 +  v(p(  ),  +t 0 ) d  [instantaneous] p E (t+  t) = p(t) +  t v(p(t),t) [time-dependent]

9 Feature Extraction and Visualization of Flow Fields Direct Flow Visualization Direct Mapping of Flow Attributes to Visualization Space Advantages:  simplicity  less computation time  intuitive Disadvantages:  does not always clearly show flow properties and features, e.g., flow orientation

10 Feature Extraction and Visualization of Flow Fields Direct FlowViz: Color Coded Slicing Color Coding in 2D, instantaneous: mapping flow attribute(s) to hue slicing probe for vortex visualization (Schulz et al) multiple slices for vortex visualization (missing color coded boundary)

11 Feature Extraction and Visualization of Flow Fields Direct FlowViz: Arrow/Hedgehog plots in 2D and 3D, instantaneous

12 Feature Extraction and Visualization of Flow Fields Direct FlowViz: Contours in 2D and isosurfaces in 3D Contours in a slice Isosurface (and color coding) in 3D

13 Feature Extraction and Visualization of Flow Fields Direct FlowViz: Volume Rendering combined with color coding the curvilinear bluntfin data set (Westermann)

14 Feature Extraction and Visualization of Flow Fields Direct FlowViz: Hybrid Solutions -arrow plots and color coding in 2D, steady and unsteady

15 Feature Extraction and Visualization of Flow Fields Texture-Based Flow Visualization Computing textures that provide a dense coverage/visualization of a vector field Advantages:  detailed view of vector field  clearer perception of characteristics  contains elements of direct + geometric FlowViz Disadvantages:  computation time  2.5D, 3D

16 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: Spot Noise (Van Wijk) and LIC (Cabral and Leedom) in 2D, instantaneous

17 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: Spot Noise in 2D, instantaneous, with color coding (de Leeuw) Good for visualizing detail.

18 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: Spot Noise and LIC in 2D, time- dependent (Van Wijk)

19 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: Time-Dependent Texture Advection in 2D Unsteady FlowViz of the Gulf of Mexico (Jobard et al)

20 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: LIC on Surfaces, unsteady A comparison of 3 LIC techniques (left) UFLIC, (middle) ELIC, and (right) PLIC (Verma et. al.)

21 Feature Extraction and Visualization of Flow Fields Texture-Based FlowViz: LIC in 3D, instantaneous (Interrante and Grosch)

22 Feature Extraction and Visualization of Flow Fields Geometric Flow Visualization The computation of objects whose shape is directly related to underlying geometry Advantages:  intuitive  clearer perception of characteristics Disadvantages:  placement  3D

23 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Some Terminology Stream vs. Path vs Streak vs Time lines Streamline  everywhere tangent to flow at instantaneous time, t 0 (blue/aqua) Pathline  path traced by a particle over time, t (red/maroon) Streakline  line traced by continuous injection at location, x 0 (light green) Timeline  temporal evolution of initial line, l 0 (yellow)

24 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Streamlines and Streamlets in 2D, steady-state

25 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Pathlines and Streamlets in 2D, unsteady (Van Wijk)

26 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Timelines in 2D (Van Wijk) and 3D (B. Girod) (unsteady)

27 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Seeding in 2D (B. Jobard) and 3D (Schulz et al) Image-based, topology- based, and interactive seeding strategies

28 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Streamribbons and Streamtubes, 3D, steady-state

29 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Perceptual Issues in 3D, steady-state Illuminated Streamlines (Zoeckler) StreamRunner (Laramee)

30 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Streaklines in 2D (Jobard et al) and 3D (B. Girod)

31 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: StreamBalls (Brill et al), StreamSurfaces (Hultquist), StreamArrows (Loeffelmann et al), 3D, steady-state

32 Feature Extraction and Visualization of Flow Fields Geometric FlowViz: Flow Volumes (Crawfis), steady and unsteady A subset of 3D flow domain specified by initial 2D patch

33 Feature Extraction and Visualization of Flow Fields Some Open Issues in FlowViz  Unsteady FlowViz on Surfaces -esp. Texture- based, unstructured  Steady-State FlowViz in 3D -perceptual issues, seeding strategies  Unsteady FlowViz in 3D -computation time  Lot’s of work to (still) be done.

34 Feature Extraction and Visualization of Flow Fields Acknowledgements: Part 1  Thanks to (1) the KPlus ( ) - Austrian governmental research program, and (3) AVL ( ) for financial support  For more information see: or  Now for Part 2!