Fluid Simulation and Control for Computer Graphics

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    Fluid Simulation and Control for Computer Graphics - Presentation Transcript

    1. Fluid Simulation and Control for Computer Graphics Michael Bang Nielsen Aarhus University
    2. What is Computer Graphics? • Modeling – Geometry – Appearance • Animation – Keyframes – Motion Capture – Simulation/Synthesis • Rendering – Offline – Realtime
    3. What is Physically Based Animation? • Rigid bodies • Deformable objects • Cloth • Hair • Fluids – Water – Smoke – Fire – Air Important for games, but what about movies and commercials?
    4. Why Computer Generated Effects for Movies and Commercials? Real world smoke and water phenomena are very complex
    5. Why Computer Generated Effects for Movies and Commercials? Ivan Aivazovsky, ”The Ninth Wave”, 1850. It requires remarkable talent and a lot of time to do..
    6. Why Computer Generated Effects for Movies and Commercials? From Rikitt: Special Effects And real phenomena have scale…
    7. Why Computer Generated Effects for Movies and Commercials? From Rikitt: Special Effects And real phenomena have scale…
    8. Why Computer Generated Effects for Movies and Commercials? Copyright Cinefex. But sometimes physical effects work.
    9. State of the Art in Fluid Simulation for Computer Graphics 1: http://www.scanlinevfxla.com/la/en/reels.html 2: Sequence from Golden Compass Molemaker et al.
    10. State of the Art in Fluid Simulation for Computer Graphics Sequence from Day After Tomorrow: Copyright Twentieth Century Fox. But don’t be fooled: Artists spend a lot of time making raw simulations look good
    11. How do we Simulate Fluids for Computer Graphics? From John D. Anderson: Computational Fluid Dynamics Math, Physics, Computer Science, Fluid Dynamics and Computational Fluid Dynamics (CFD)
    12. Fluid Simulation for Computer Graphics Demands are different than in CFD: • Should be visually plausible • Physical accuracy not paramount • Animators/director want a certain visual style
    13. Fluid Simulation for Computer Graphics • Simulation speed – deadlines and interactive preview • The fluid should have character Production designs by Jon Brooks • The artists want control – it should be possible to sculpt the fluid From Inkheart. Image by Double Negative
    14. Guided Fluid Simulation Collaboration between • Michael Bang Nielsen • Brian Bunch Christensen • Nafees Bin Zafar • Doug Roble • Ken Museth I will share both our successes and frustrations with you!
    15. Guided Fluid Simulation Motivation Our Contribution: Coarse Simulation Guided Fine Simulation Fine Simulation
    16. Guided Fluid Simulation Motivation High Res Low Res Low Res Upsampled
    17. Guided Fluid Simulation Problem Statement Develop • Mathematical model • Algorithms • Data structures That make it possible to guide a high resolution fluid simulation using a low resolution simulation
    18. Guided Fluid Simulation The Fundamental Idea The low frequencies of the fine simulation should be equal to the frequencies of the coarse simulation Challenge: Formulate this mathematically
    19. The One-Slide Fluid Mechanics Course Net force = mass x acceleration F = ma ⇒ F Vol =a m Vol ⇒ 1 F ρ Vol =a
    20. The One-Slide Computational Fluid Mechanics Course In computer graphics we apply Operator Splitting: Advection Body forces Incompressibility
    21. Guided Fluid Simulation How do we attack the problem? Advection Body forces Incompressibility The low frequencies of the fine simulation should be equal to the frequencies of the coarse simulation
    22. Guided Fluid Simulation The Force-Based Approach • Forces (all or low frequencies) Thuerey et al. • Blending of divergence free velocity fields – Leads to results that are too smooth
    23. Guided Fluid Simulation How do we attack the problem? Advection Body forces Incompressibility The low frequencies of the fine simulation should be equal to the frequencies of the coarse simulation
    24. Guided Fluid Simulation The Modified Pressure Projection Approach Observation Solving for Incompressibility is identical to the minimization of subject to the constraint
    25. Guided Fluid Simulation The Modified Pressure Projection Approach We add the constraint to the minimization of subject to the constraint
    26. Guided Fluid Simulation The Modified Pressure Projection Approach Calculus of variations leads to the equations Does it work?
    27. Guided Fluid Simulation The Modified Pressure Projection Approach Test-simulations in Matlab Problems: • Matrix singular when filter is wide • Where should we place the constraints?
    28. Guided Fluid Simulation The Modified Pressure Projection Approach Fundamental question: Does our approach fail completely, or can we modify it somehow?
    29. Guided Fluid Simulation The Modified Pressure Projection Second Approach The low frequencies of the fine simulation should be as close as possible to the frequencies of the coarse simulation Challenge: Formulate this mathematically
    30. Guided Fluid Simulation The Modified Pressure Projection Second Approach We add the minimization term to the minimization of subject to the constraint
    31. Guided Fluid Simulation The Modified Pressure Projection Second Approach Calculus of variations leads to the equations Does it work?
    32. Guided Fluid Simulation The Modified Pressure Projection Second Approach Verification in 2D
    33. Guided Fluid Simulation The Modified Pressure Projection Second Approach Fast to solve, but 1602 requires roughly 2GB and we want to do it in 2563…
    34. Guided Fluid Simulation The Modified Pressure Projection Second Approach Computational challenges: • Sparse entries take up 4.04TB in resolution 2563 • We reduced this to 208MB • Linear system is a-symmetric • Solution: Improved multigrid solver • Linear system is slow to solve • Solution: Parallel solver using separable lowpass filters
    35. Guided Fluid Simulation The Modified Pressure Projection Second Approach More computational challenges: • Boundaries traditionally hard to use with multigrid • Which lowpass filter should be used? • How do we handle non-physically based guiding velocity fields?
    36. Results Interpolation between strictly guided and unguided simulation Low res High Res
    37. Links to More Information • http://cs.au.dk/research/areas/computer- graphics-and-scientific-computing/ • http://cg.alexandra.dk/2009/05/15/smoke- rendering-demo/

    + Dept. of Computer Science, Aarhus UniversityDept. of Computer Science, Aarhus University, 1 month ago

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