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Robert S. Laramee 1 Flow Visualization: The State-of-the-Art Robert S. Laramee The Visual and Interactive.

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Presentation on theme: "Robert S. Laramee 1 Flow Visualization: The State-of-the-Art Robert S. Laramee The Visual and Interactive."— Presentation transcript:

1 Robert S. Laramee r.s.laramee@swansea.ac.uk 1 http://cs.swan.ac.uk/~csbob/ Flow Visualization: The State-of-the-Art Robert S. Laramee The Visual and Interactive Computing Group Computer Science Department Swansea University Swansea, Wales, UK r.s.laramee@swansea.ac.uk

2 Robert S. Laramee r.s.laramee@swansea.ac.uk 2 http://cs.swan.ac.uk/~csbob/ Overview  Introduction to Flow Visualization (FlowViz)  What is Flow Visualization? A Brief Introduction  What approaches have been developed?  Classification:  Direct  Texture-based  Geometric  Feature-based flow visualization  Applications  Conclusions and Future Work A note on scope: An overview is provided with references to more depth.

3 Robert S. Laramee r.s.laramee@swansea.ac.uk 3 http://cs.swan.ac.uk/~csbob/ What is Flow Visualization?  a classic topic within scientific visualization  depiction of vector quantities (as opposed to scalar quantities)  applications include automotive simulation, aerodynamics, turbomachinery, meteorology, oceanography, medical visualization Challenges:  to effectively visualize both magnitude + direction, often simultaneously  large data sets  time-dependent data  multi-field visualization  What should be visualized? (data filtering/feature extraction)

4 Robert S. Laramee r.s.laramee@swansea.ac.uk 4 http://cs.swan.ac.uk/~csbob/ Computational vs. Experimental 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 Robert S. Laramee r.s.laramee@swansea.ac.uk 5 http://cs.swan.ac.uk/~csbob/ 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 or static flow)  time-dependent flow -multiple time steps (or unsteady or transient, real-world)  caution is advised in the context of animation Simulation Data Attributes a.k.a. Data Dimensions:  velocity  temperature  pressure  and many more...

6 Robert S. Laramee r.s.laramee@swansea.ac.uk 6 http://cs.swan.ac.uk/~csbob/ 1. direct: overview of vector field, minimal computation, e.g. glyphs, color mapping 2. texture-based: covers domain with a convolved texture, e.g., Spot Noise, LIC, ISA, IBFV(S) 3. geometric: a discrete object(s) whose geometry reflects flow characteristics, e.g. streamlines 4. feature-based: both automatic and interactive feature-based techniques, e.g. flow topology Flow Visualization Classification

7 Robert S. Laramee r.s.laramee@swansea.ac.uk 7 http://cs.swan.ac.uk/~csbob/ 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  perception in 3D  aliasing

8 Robert S. Laramee r.s.laramee@swansea.ac.uk 8 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: LIC (Cabral and Leedom) in 2D, Instantaneous

9 Robert S. Laramee r.s.laramee@swansea.ac.uk 9 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: Spot Noise in 2D, Instantaneous with Color Coding Good for visualizing detail. (de Leeuw)

10 Robert S. Laramee r.s.laramee@swansea.ac.uk 10 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: Time-Dependent Texture Advection in 2D Unsteady FlowViz of the Gulf of Mexico (Jobard et al)

11 Robert S. Laramee r.s.laramee@swansea.ac.uk 11 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: 2D Unsteady Flow Image Based Flow Visualization (IBFV, Van Wijk)

12 Robert S. Laramee r.s.laramee@swansea.ac.uk 12 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: LIC on Surfaces, Unsteady A comparison of 3 LIC techniques (left) UFLIC, (middle) ELIC, and (right) PLIC (Verma et. al.)

13 Robert S. Laramee r.s.laramee@swansea.ac.uk 13 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: Texture-Advection on Surfaces, Unsteady Image Space Advection (ISA, Laramee et al.) and Image Based Flow Visualization for Curved Surfaces (IBFVS, van Wijk)

14 Robert S. Laramee r.s.laramee@swansea.ac.uk 14 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: Texture Advection in 3D, Unsteady 3D IBFV (Telea and Van Wijk)

15 Robert S. Laramee r.s.laramee@swansea.ac.uk 15 http://cs.swan.ac.uk/~csbob/ Texture-Based FlowViz: Texture Advection in 3D, Unsteady 3D texture-based flow vis with illumination, velocity masking, and focus+context (Weiskopf et al.)

16 Robert S. Laramee r.s.laramee@swansea.ac.uk 16 http://cs.swan.ac.uk/~csbob/ Texture-Based Flow Visualization For more information on texture-based flow visualization techniques, please see: Robert S. Laramee, Helwig Hauser, Helmut Doleisch, Benjamin Vrolijk, Frits H. Post, and Daniel Weiskopf, The State of the Art in Flow Visualization: Dense and Texture-Based Techniques in Computer Graphics Forum, Vol. 23, No. 2, 2004, pages 203-221 (1st STAR)

17 Robert S. Laramee r.s.laramee@swansea.ac.uk 17 http://cs.swan.ac.uk/~csbob/ Geometric Flow Visualization The computation of discrete objects whose shape is directly related to underlying geometry Advantages:  intuitive  clearer perception of characteristics Disadvantages:  placement  visual complexity in 3D

18 Robert S. Laramee r.s.laramee@swansea.ac.uk 18 http://cs.swan.ac.uk/~csbob/ 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)

19 Robert S. Laramee r.s.laramee@swansea.ac.uk 19 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Streamlines and Streamlets in 2D, Steady-State Evenly Space Streamlines (Jobard and Lefer)

20 Robert S. Laramee r.s.laramee@swansea.ac.uk 20 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Pathlines and Streamlets in 2D, Unsteady Pathlines and particles using textures (Van Wik)

21 Robert S. Laramee r.s.laramee@swansea.ac.uk 21 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Timelines in 2.5D and 3D (B. Girod) (unsteady) 2.5D timelines using textures (Laramee et al.) and 3D timelines as discrete objects (B. Girod)

22 Robert S. Laramee r.s.laramee@swansea.ac.uk 22 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Streamribbons and Streamtubes, 3D, Steady-state

23 Robert S. Laramee r.s.laramee@swansea.ac.uk 23 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Perceptual Issues in 3D, Steady- State Illuminated Streamlines (Zoeckler et al) StreamRunner (Laramee)

24 Robert S. Laramee r.s.laramee@swansea.ac.uk 24 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Streaklines in 3D Streaklines in 3D as discrete objects (B. Girod)

25 Robert S. Laramee r.s.laramee@swansea.ac.uk 25 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: StreamBalls, StreamSurfaces, StreamArrows, 3D, Steady-State Streamballs (Brill et a), Streamsurfaces (Hultquist), and StreamArrows (Loeffelmann et al.)

26 Robert S. Laramee r.s.laramee@swansea.ac.uk 26 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: Flow Volumes (3D), Steady and Unsteady A subset of 3D flow domain specified by initial 2D patch (Crawfis)

27 Robert S. Laramee r.s.laramee@swansea.ac.uk 27 http://cs.swan.ac.uk/~csbob/ Geometric FlowViz: High Quality Animation, 3D, Unsteady Visualization of Hurricane Isabel (Helgeland et al.)

28 Robert S. Laramee r.s.laramee@swansea.ac.uk 28 http://cs.swan.ac.uk/~csbob/ Geometric Flow Visualization For more information on geometric flow visualization techniques, please see: Frits H. Post, Benjamin Vrolijk, Helwig Hauser, Robert S. Laramee, and Helmut Doleisch, Feature Extraction and Visualization of Flow Fields in EUROGRAPHICS 2002, State of the Art Reports, pages 69-100, September 4-6 2002, Saarbruecken, Germany (2nd STAR)

29 Robert S. Laramee r.s.laramee@swansea.ac.uk 29 http://cs.swan.ac.uk/~csbob/  swirl motion: characterized by motion about cylinder-aligned axis  more stable (easier)  tumble motion: characterized by motion about axis orthogonal to cylinder  unstable, more difficult Flow Visualization: An Application

30 Robert S. Laramee r.s.laramee@swansea.ac.uk 30 http://cs.swan.ac.uk/~csbob/ Achieving ideal patterns of motion leads to optimal mixing (of air and fuel) conditions  e.g., higher exhaust/gas ratio (EGR)  decrease in fuel consumption  lower emissions 1. Can visualization provide insight into or verify characteristic shape/behavior of flow? 2. What tools help to visualize swirl/tumble motion? 3. Where (in the combustion chamber) are ideal ideal flow pattern not being realized? Flow Visualization: An Application

31 Robert S. Laramee r.s.laramee@swansea.ac.uk 31 http://cs.swan.ac.uk/~csbob/ Flow Visualization: An Application Direct, geometric, and texture-based flow visualization methods are used in 2D, 2.5D, and 3D.

32 Robert S. Laramee r.s.laramee@swansea.ac.uk 32 http://cs.swan.ac.uk/~csbob/ What is Feature-Based Flow Visualization? Recall: What is Flow Visualization?  a classic topic within scientific visualization  depiction of vector quantities (as opposed to scalar quantities) Challenges:  to effectively visualize both magnitude + direction, often simultaneously  large data sets  time-dependent data  multi-field visualization  What should be visualized? (data filtering/feature extraction) Feature-Based Flow Visualization

33 Robert S. Laramee r.s.laramee@swansea.ac.uk 33 http://cs.swan.ac.uk/~csbob/ What is Feature-Based Flow Visualization? What is a feature?  feature: “A prominent or distinctive aspect, quality, or characteristic”, from dictionary.com  feature: any subset of the flow domain deemed interesting by an onlooker, i.e., the viewer (Bob’s definition) What is feature-based flow visualization?  feature-based flow visualization: the focus on and resulting depiction of a subset of the flow domain. (Bob’s definition)

34 Robert S. Laramee r.s.laramee@swansea.ac.uk 34 http://cs.swan.ac.uk/~csbob/ Feature-Based Flow Visualization Pipeline Feature-Based flow visualization involves extracting features from the vector field domain.  selection: conceptually, filtering the data  clustering: coherency is established from point selection  attribute calculation: quantification, e.g., position, volume, orientation --> leads to features

35 Robert S. Laramee r.s.laramee@swansea.ac.uk 35 http://cs.swan.ac.uk/~csbob/ Feature-Based Flow Visualization: Motivation Why?  data reduction: original data set is represented with important features  perception: visualization of 3D and 4D flow is problematic in the absence of feature-based techniques  new insight: “new” characteristics of the flow can be observed  technical advantages: less memory consumption, faster interaction and rendering

36 Robert S. Laramee r.s.laramee@swansea.ac.uk 36 http://cs.swan.ac.uk/~csbob/ Feature Based Flow Visualization: 3D Steady and Unsteady  Vector field clustering (Telea and Van Wijk)  Vortex extraction (Post et al.)

37 Robert S. Laramee r.s.laramee@swansea.ac.uk 37 http://cs.swan.ac.uk/~csbob/ Feature Based Flow Visualization: 3D Unsteady  Cores of swirling particle motion in unsteady flow, extraction based on pathlines (Wienkauf et al.)

38 Robert S. Laramee r.s.laramee@swansea.ac.uk 38 http://cs.swan.ac.uk/~csbob/ Feature Based Flow Visualization: 3D, Unsteady, Interactive  SimVis: interactive, multiple connected views (Doleisch et al.)

39 Robert S. Laramee r.s.laramee@swansea.ac.uk 39 http://cs.swan.ac.uk/~csbob/ Feature-Based Flow Visualization For more information on feature-based flow visualization techniques, please see: Frits H. Post, Benjamin Vrolijk, Helwig Hauser, Robert S. Laramee, and Helmut Doleisch, The State of the Art in Flow Visualisation: Feature Extraction and Tracking in Computer Graphics Forum, Vol. 22, No. 4, 2003, pages 775-792 (3rd STAR)

40 Robert S. Laramee r.s.laramee@swansea.ac.uk 40 http://cs.swan.ac.uk/~csbob/ Topology-Based Flow Visualization Can be considered a sub-field of feature-based flow visualization:  singularities in flow field are extracted, loosely: locations where flow velocity approaches zero, e.g., sources, sinks, etc.  the relationship, connectivity, or topology between singularities is then analyzed and visualized  the topology of vector field is often called “skeleton” of the flow

41 Robert S. Laramee r.s.laramee@swansea.ac.uk 41 http://cs.swan.ac.uk/~csbob/ Topology-Based Flow Visualization, 2.5D Steady  a single framework can be used to extract sources, sinks, saddle points, and periodic orbits  u ncertainty due to discrete nature of simulation, interpolation, and integration can be factored into extraction and visualization  (Chen et al.)

42 Robert S. Laramee r.s.laramee@swansea.ac.uk 42 http://cs.swan.ac.uk/~csbob/ Topology-Based Flow Visualization For more information on topology-based flow visualization techniques, please see: Robert S. Laramee, Helwig Hauser, Lingxiao Zhao, and Frits H. Post, Topology-Based Flow Visualization, The State of the Art, in Topology-Based Methods in Visualization (Proceedings of Topo-In-Vis 2005), Visualization and Mathematics, pages 1-19, 2007, Springer-Verlag (4 th ! STAR)

43 Robert S. Laramee r.s.laramee@swansea.ac.uk 43 http://cs.swan.ac.uk/~csbob/ Four major design goals:  an even distribution of flow to each engine cylinder  avoid regions of stagnant flow  avoid very high velocity flow  minimize fluid pressure loss between inlet and outlet Feature-Based Flow Visualization: An Application

44 Robert S. Laramee r.s.laramee@swansea.ac.uk 44 http://cs.swan.ac.uk/~csbob/ Feature-Based Flow Visualization: An Application  A range of direct, texture-based, geometric, feature- based, and topology-based visualization methods are applied

45 Robert S. Laramee r.s.laramee@swansea.ac.uk 45 http://cs.swan.ac.uk/~csbob/ Flow Visualization: Challenges  FlowViz in 3D -perceptual issues, seeding strategies  Unsteady FlowViz in 3D -computation time  What should be extracted and visualized?  How can features be extracted and visualized? e.g. vortices  costly in terms of processing time  interpretation can be challenging  correctness: verification of result (sometimes ignored) An area still rich in unsolved problems.

46 Robert S. Laramee r.s.laramee@swansea.ac.uk 46 http://cs.swan.ac.uk/~csbob/ Acknowledgements  Thank you for your attention! Any questions? We would like to thank the following:  G. Chen, R. Crawfis, H. Doleisch, C. Garth, B. Girod, H. Hauser, A. Helgeland, V. Interrante, B. Jobard, W. de Leeuw, H. Loeffelmann, F. H. Post, A. Telea, H. Theisel, X. Tricoche, V. Verma, J. J. van Wijk. T. Weinkauf, D. Weiskopf, R. Westermann, E. Zhang  PDF versions of STARS 1-4 and MPEG movies available at: http://cs.swan.ac.uk/~csbob

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