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Fluid simulation using Laplacian eigenfunctions

Published:02 February 2012Publication History
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We present an algorithm for the simulation of incompressible fluid phenomena that is computationally efficient and leads to visually convincing simulations with far fewer degrees of freedom than existing approaches. Rather than using an Eulerian grid or Lagrangian elements, we represent vorticity and velocity using a basis of global functions defined over the entire simulation domain. We show that choosing Laplacian eigenfunctions for this basis provides benefits, including correspondence with spatial scales of vorticity and precise energy control at each scale. We perform Galerkin projection of the Navier-Stokes equations to derive a time evolution equation in the space of basis coefficients. Our method admits closed-form solutions on simple domains but can also be implemented efficiently on arbitrary meshes.

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References

  1. Adams, B., Pauly, M., Keiser, R., and Guibas, L. J. 2007. Adaptively sampled particle fluids. In ACM SIGGRAPH 2007 Papers. ACM, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Agrachev, A. A. and Sarychev, A. V. 2005. Navier-Stokes equations: Controllability by means of low modes forcing. J. Math. Fluid Mechan. 7, 1, 108--152.Google ScholarGoogle ScholarCross RefCross Ref
  3. Angelidis, A., Neyret, F., Singh, K., and Nowrouzezahrai, D. 2006. A controllable, fast and stable basis for vortex based smoke simulation. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'06). Eurographics Association, 25--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Arnold, V. I. 1966. Sur la géométrie différentielle des groupes de lie de dimension infinie et ses applications à l'hydrodynamique des fluides parfaits. Ann. Inst. Fourier (Grenoble) 16.Google ScholarGoogle Scholar
  5. Barbič, J., da Silva, M., and Popović, J. 2009. Deformable object animation using reduced optimal control. In ACM SIGGRAPH 2009 Papers. ACM, New York, 53:1--53:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bridson, R., Houriham, J., and Nordenstam, M. 2007. Curl-Noise for procedural fluid flow. In ACM SIGGRAPH 2007 Papers. ACM, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Cheng, D. K. 1999. Field and Wave Electromagnetics. Addison-Wesley, Reading, MA.Google ScholarGoogle Scholar
  8. de Witt, T. 2010. Fluid simulation in bases of Laplacian eigenfunctions. M.S. thesis, University of Toronto, Toronto, ON, Canada.Google ScholarGoogle Scholar
  9. Desbrun, M. and Gascuel, M.-P. 1996. Smoothed particles: A new paradigm for animating highly deformable bodies. In Proceedings of the Eurographics Workshop on Computer Animation and Simulation'96. Springer, 61--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Desbrun, M., Kanso, E., and Tong, Y. 2005. Discrete differential forms for computational modeling. In ACM SIGGRAPH 2005 Courses. ACM, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Elcott, S., Tong, Y., Kanso, E., Schröder, P., and Desbrun, M. 2007. Stable, circulation-preserving, simplicial fluids. ACM Trans. Graph. 26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Fattal, R. and Lischinski, D. 2004. Target-driven smoke animation. In ACM SIGGRAPH 2004 Papers. ACM, New York, 441--448. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Fedkiw, R., Stam, J., and Jensen, H. W. 2001. Visual simulation of smoke. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques. ACM, New York, 15--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Foster, N. and Metaxas, D. 1996. Realistic animation of liquids. Graph. Models Image Process. 58, 471--483. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Gamito, M. N., Lopes, P. F., and Gomes, M. R. 1995. Two-Dimensional simulation of gaseous phenomena using vortex particles. In Proceedings of the 6th Eurographics Workshop on Computer Animation and Simulation. Springer, 3--15.Google ScholarGoogle Scholar
  16. Gupta, M. and Narasimhan, S. G. 2007. Legendre fluids: A unified framework for analytic reduced space modeling and rendering of participating media. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'07). Eurographics Association, 17--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Gustafson, K. and Hartman, R. 1983. Divergence-Free bases for finite element schemes in hydrodynamics. SIAM J. Numer. Anal. 20, 697--721.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lentine, M., Zheng, W., and Fedkiw, R. 2010. A novel algorithm for incompressible flow using only a coarse grid projection. In ACM SIGGRAPH 2010 Papers. ACM, New York, 114:1--114:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Losasso, F., Gibou, F., and Fedkiw, R. 2004. Simulating water and smoke with an octree data structure. In ACM SIGGRAPH 2004 Papers. ACM, New York, 457--462. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Marsden, J. E. and Ratiu, T. S. 1999. Introduction to Mechanics and Symmetry, 2nd ed. Texts in Applied Mathematics. No. 17, Springer, New York.Google ScholarGoogle Scholar
  21. McNamara, A., Treuille, A., Popović, Z., and Stam, J. 2004. Fluid control using the adjoint method. In ACM SIGGRAPH 2004 Papers. ACM, New York, 449--456. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Mullen, P., Crane, K., Pavlov, D., Tong, Y., and Desbrun, M. 2009. Energy-Preserving integrators for fluid animation. In ACM SIGGRAPH 2009 Papers. ACM, New York, 38:1--38:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Müller, M., Charypar, D., and Gross, M. 2003. Particle-Based fluid simulation for interactive applications. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'03). Eurographics Association, 154--159. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Orszag, S. A. 1969. Numerical methods for the simulation of turbulence. Phys. Fluids 12, 250--257.Google ScholarGoogle ScholarCross RefCross Ref
  25. Orszag, S. A. and Patterson, G. 1972. Numerical simulation of three-dimensional homogeneous isotropic turbulence. Phys. Rev. Lett. 28, 76--79.Google ScholarGoogle ScholarCross RefCross Ref
  26. Park, S. I. and Kim, M. J. 2005. Vortex fluid for gaseous phenomena. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'05). ACM, New York, 261--270. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Poincaré, H. 1901. Sur une forme nouvelle des équations de la méchanique. C.R. Acad. Sci. 132, 369--371.Google ScholarGoogle Scholar
  28. Rogallo, R., Moin, P., and Reynolds, W. 1981. Numerical experiments in homogeneous turbulence. NASA TM-81315.Google ScholarGoogle Scholar
  29. Selle, A., Fedkiw, R., Kim, B., Liu, Y., and Rossignac, J. 2008. An unconditionally stable MacCormack method. J. Sci. Comput. 35, 350--371. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Silberman, I. 1954. Planetary waves in the atmosphere. J. Meteor. 11, 27--34.Google ScholarGoogle ScholarCross RefCross Ref
  31. Stam, J. 1999. Stable fluids. In Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. ACM Press/Addison-Wesley Publishing Co., New York, 121--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Stam, J. 2002. A simple fluid solver based on the FFT. J. Graph. Tools 6, 43--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Stam, J. and Fiume, E. 1993. Turbulent wind fields for gaseous phenomena. In Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques. ACM, New York, 369--376. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Treuille, A., Lewis, A., and Popović, Z. 2006. Model reduction for real-time fluids. In ACM SIGGRAPH 2006 Papers. ACM, New York, 826--834. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Treuille, A., McNamara, A., Popović, Z., and Stam, J. 2003. Keyframe control of smoke simulations. In ACM SIGGRAPH 2003 Papers. ACM, New York, 716--723. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Twigg, C. D. and James, D. L. 2008. Backward steps in rigid body simulation. In ACM SIGGRAPH 2008 Papers. ACM, New York, 25:1--25:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Weissmann, S. and Pinkall, U. 2010. Filament-Based smoke with vortex shedding and variational reconnection. In ACM SIGGRAPH 2010 Papers. ACM, New York, 115:1--115:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Wicke, M., Stanton, M., and Treuille, A. 2009. Modular bases for fluid dynamics. In ACM SIGGRAPH 2009 Papers. ACM, New York, 39:1--39:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Yudovich, V. I. 1963. Non-Stationary flow of an ideal incompressible liquid. USSR Comput. Math. Math. Phys. 3, 6, 1407--1456.Google ScholarGoogle ScholarCross RefCross Ref
  40. Zhu, Y. and Bridson, R. 2005. Animating sand as a fluid. In ACM SIGGRAPH 2005 Papers. ACM, New York, 965--972. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 31, Issue 1
      January 2012
      149 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/2077341
      Issue’s Table of Contents

      Copyright © 2012 ACM

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      Publication History

      • Published: 2 February 2012
      • Accepted: 1 September 2011
      • Received: 1 July 2011
      Published in tog Volume 31, Issue 1

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