Abstract
We present a new subspace integration method that is capable of efficiently adding and subtracting dynamics from an existing high-resolution fluid simulation. We show how to analyze the results of an existing high-resolution simulation, discover an efficient reduced approximation, and use it to quickly "re-simulate" novel variations of the original dynamics. Prior subspace methods have had difficulty re-simulating the original input dynamics because they lack efficient means of handling semi-Lagrangian advection methods. We show that multi-dimensional cubature schemes can be applied to this and other advection methods, such as MacCormack advection. The remaining pressure and diffusion stages can be written as a single matrix-vector multiply, so as with previous subspace methods, no matrix inversion is needed at runtime. We additionally propose a novel importance sampling-based fitting algorithm that asymptotically accelerates the precomputation stage, and show that the Iterated Orthogonal Projection method can be used to elegantly incorporate moving internal boundaries into a subspace simulation. In addition to efficiently producing variations of the original input, our method can produce novel, abstract fluid motions that we have not seen from any other solver.
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- Amsallem, D., and Farhat, C. 2012. Stabilization of projection-based reduced-order models. International Journal for Numerical Methods in Engineering 91, 4, 358--377.Google Scholar
Cross Ref
- An, S. S., Kim, T., and James, D. L. 2008. Optimizing Cubature for Efficient Integration of Subspace Deformations. ACM Trans. on Graphics 27, 5 (Dec.), 165. Google Scholar
Digital Library
- Anttonen, J., King, P., and Beran, P. 2003. POD-based reduced-order models with deforming grids. Mathematical and Computer Modelling 38, 41--62. Google Scholar
Digital Library
- Baraff, D., and Witkin, A. 1992. Dynamic simulation of non-penetrating flexible bodies. In Computer Graphics (Proceedings of SIGGRAPH 92), 303--308. Google Scholar
Digital Library
- Barbič, J., and James, D. L. 2005. Real-Time Subspace Integration for St. Venant-Kirchhoff Deformable Models. ACM Trans. on Graphics 24, 3 (Aug.), 982--990. Google Scholar
Digital Library
- Bergmann, M., Cordier, L., and Brancher, J.-P. 2005. Optimal rotary control of the cylinder wake using proper orthogonal decomposition reduced-order model. Physics of Fluids 17, 9, 097101.Google Scholar
Cross Ref
- Berkooz, G., Holmes, P., and Lumley, J. L. 1993. The proper orthogonal decomposition in the analysis of turbulent flows. Annual Rev. Fluid Mech, 539--575.Google Scholar
- Bourguet, R., Braza, M., and Dervieux, A. 2011. Reduced-order modeling of transonic flows around an airfoil submitted to small deformations. Journal of Computational Physics 230, 1, 159--184. Google Scholar
Digital Library
- Bro, R., and De Jong, S. 1997. A fast non-negativity-constrained least squares algorithm. Journal of Chemometrics 11, 5, 393--401.Google Scholar
Cross Ref
- Bro, R., 2001. The n-way toolbox. http://bit.ly/Wmq8zM.Google Scholar
- Brochu, T., Keeler, T., and Bridson, R. 2012. Linear-time smoke animation with vortex sheet meshes. In Proceedings of the ACM SIGGRAPH/Eurographics Sym. on Computer Animation, 87--95. Google Scholar
Digital Library
- Carlberg, K., Bou-Mosleh, C., and Farhat, C. 2011. Efficient non-linear model reduction via a least-squares petrovgalerkin projection and compressive tensor approximations. International Journal for Numerical Methods in Engineering 86, 2, 155--181.Google Scholar
Cross Ref
- Chadwick, J. N., An, S. S., and James, D. L. 2009. Harmonic shells: a practical nonlinear sound model for near-rigid thin shells. ACM Trans. Graph. 28, 5 (Dec.), 119:1--119:10. Google Scholar
Digital Library
- Chen, D., and Plemmons, R. 2007. Nonnegativity constraints in numerical analysis. In Symposium on the Birth of Numerical Analysis.Google Scholar
- De Witt, T., Lessig, C., and Fiume, E. 2012. Fluid simulation using laplacian eigenfunctions. ACM Trans. Graph. 31, 1, 10:1--10:11. Google Scholar
Digital Library
- Deparis, S., and Rozza, G. 2009. Reduced basis method for multi-parameter-dependent steady navierstokes equations: Applications to natural convection in a cavity. Journal of Computational Physics 228, 12, 4359--4378. Google Scholar
Digital Library
- Fedkiw, R., Stam, J., and Jensen, H. W. 2001. Visual simulation of smoke. In Proceedings of SIGGRAPH, 15--22. Google Scholar
Digital Library
- Foster, N., and Metaxas, D. 1997. Modeling the motion of a hot, turbulent gas. In Proceedings of SIGGRAPH, ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, 181--188. Google Scholar
Digital Library
- Golub, G., and Van Loan, C. 1996. Matrix Computations, 3rd ed. The Johns Hopkins University Press, Baltimore. Google Scholar
Digital Library
- Guennebaud, G., Jacob, B., et al., 2010. Eigen v3. http://eigen.tuxfamily.org.Google Scholar
- Henderson, R. D. 2012. Scalable fluid simulation in linear time on shared memory multiprocessors. In Proceedings of the Digital Production Symposium, ACM Press, 43--52. Google Scholar
Digital Library
- Homescu, C., Petzold, L. R., and Serban, R. 2005. Error estimation for reduced-order models of dynamical systems. SIAM Journal on Numerical Analysis 43, 4, 1693--1714. Google Scholar
Digital Library
- James, D. L., and Fatahalian, K. 2003. Precomputing interactive dynamic deformable scenes. ACM Transactions on Graphics 22, 3 (July), 879--887. Google Scholar
Digital Library
- Kim, T., and James, D. L. 2009. Skipping steps in deformable simulation with online model reduction. ACM Transactions on Graphics 28, 5 (Dec.), 123:1--123:9. Google Scholar
Digital Library
- Kim, T., and James, D. L. 2011. Physics-based character skinning using multi-domain subspace deformations. In ACM SIGGRAPH/Eurographics Sym. on Computer Animation, ACM, New York, NY, USA, 63--72. Google Scholar
Digital Library
- Kim, T., Thürey, N., James, D., and Gross, M. 2008. Wavelet turbulence for fluid simulation. ACM Trans. Graph. 27 (August), 50:1--50:6. Google Scholar
Digital Library
- Kim, D., Sra, S., and Dhillon, I. S. 2012. A non-monotonic method for large-scale non-negative least squares. Optimization Methods and Software (OMS) (Jan.).Google Scholar
- Kleinberg, J., and Tardos, E. 2006. Algorithm Design. Addison-Wesley. Google Scholar
Digital Library
- Klingner, B. M., Feldman, B. E., Chentanez, N., and O'Brien, J. F. 2006. Fluid animation with dynamic meshes. In Proceedings of SIGGRAPH, 820--825. Google Scholar
Digital Library
- Krysl, P., Lall, S., and Marsden, J. E. 2001. Dimensional model reduction in non-linear finite element dynamics of solids and structures. International Journal for Numerical Methods in Engineering 51, 479--504.Google Scholar
Cross Ref
- Lawson, C. L., and Hanson, R. J. 1974. Solving Least Square Problems. Prentice Hall, Englewood Cliffs, NJ.Google Scholar
- LeGresley, P. A., and Alonso, J. J. 2001. Investigation of non-linear projection for pod based reduced order models for aerodynamics. In AIAA Aerospace Sciences Meeting and Exhibit.Google Scholar
- Lentine, M., Zheng, W., and Fedkiw, R. 2010. A novel algorithm for incompressible flow using only a coarse grid projection. ACM Trans. Graph. 29 (July), 114:1--114:9. Google Scholar
Digital Library
- Losasso, F., Gibou, F., and Fedkiw, R. 2004. Simulating water and smoke with an octree data structure. ACM Trans. Graph. 23, 457--462. Google Scholar
Digital Library
- Lumley, J. 1967. The structure of inhomogeneous turbulent flows. Atmospheric turbulence and radio wave propagation, 166--178.Google Scholar
- Luo, Y., and Duraiswami, R. 2011. Efficient parallel nonnegative least squares on multicore architectures. SIAM Journal on Scientific Computing 33, 5, 2848--2863. Google Scholar
Digital Library
- Meyer, M., and Anderson, J. 2007. Key Point Subspace Acceleration and Soft Caching. ACM Transactions on Graphics 26, 3 (July), 74. Google Scholar
Digital Library
- Moës, N., Dolbow, J., and Belytschko, T. 1999. A finite element method for crack growth without remeshing. International Journal for Numerical Methods in Engineering 46, 1, 131--150.Google Scholar
Cross Ref
- Molemaker, J., Cohen, J. M., Patel, S., and Noh, J. 2008. Low viscosity flow simulations for animation. In ACM SIGGRAPH/Eurographics Sym. on Computer Animation, 9--18. Google Scholar
Digital Library
- Moler, C., and Van Loan, C. 2003. Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later. SIAM Review 45, 1, 3--49.Google Scholar
Digital Library
- Mullen, P., Crane, K., Pavlov, D., Tong, Y., and Desbrun, M. 2009. Energy-preserving integrators for fluid animation. ACM Trans. Graph. 28, 3 (July), 38:1--38:8. Google Scholar
Digital Library
- Narain, R., Sewall, J., Carlson, M., and Lin, M. C. 2008. Fast animation of turbulence using energy transport and procedural synthesis. ACM Trans. Graph. 27 (December), 166:1--166:8. Google Scholar
Digital Library
- Pentland, A., and Williams, J. 1989. Good vibrations: Modal dynamics for graphics and animation. In Computer Graphics (Proceedings of SIGGRAPH 89), 215--222. Google Scholar
Digital Library
- Pfaff, T., Thuerey, N., and Gross, M. 2012. Lagrangian vortex sheets for animating fluids. ACM Trans. Graph. 31, 4 (July), 112:1--112:8. Google Scholar
Digital Library
- Pharr, M., and Humphreys, G. 2010. Physically-Based Rendering: From Theory to Implementation. Morgan Kaufmann. Google Scholar
Digital Library
- Portugal, L. F., Júdice, J. J., and Vicente, L. N. 1994. A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables. Mathematics of Computation 63, 208 (Oct.), 625--643. Google Scholar
Digital Library
- Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. 1992. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, New York, NY, USA. Google Scholar
Digital Library
- Rabani, E., and Toledo, S. 2001. Out-of-core svd and qr decompositions. In SIAM Conference on Parallel Processing for Scientific Computing.Google Scholar
- Schechter, H., and Bridson, R. 2008. Evolving sub-grid turbulence for smoke animation. In ACM SIGGRAPH/Eurographics Sym. on Computer Animation, 1--7. Google Scholar
Digital Library
- Selle, A., Fedkiw, R., Kim, B., Liu, Y., and Rossignac, J. 2008. An unconditionally stable maccormack method. J. Sci. Comput. 35, 2--3 (June), 350--371. Google Scholar
Digital Library
- Seo, J., Irving, G., Lewis, J. P., and Noh, J. 2011. Compression and direct manipulation of complex blendshape models. ACM Trans. Graph. 30, 6 (Dec.), 164:1--164:10. Google Scholar
Digital Library
- Serre, G., Lafon, P., Gloerfelt, X., and Bailly, C. 2012. Reliable reduced-order models for time-dependent linearized euler equations. Journal of Computational Physics 231, 15, 5176--5194. Google Scholar
Digital Library
- Sethian, J. 1999. Level set methods and fast marching methods. Cambridge University Press.Google Scholar
- Shah, A. 2007. Cooking effects. In ACM SIGGRAPH 2007 courses, ACM, New York, NY, USA, SIGGRAPH '07, 45--58. Google Scholar
Digital Library
- Sifakis, E., and Barbič, J. 2012. Fem simulation of 3d deformable solids: a practitioner's guide to theory, discretization and model reduction. In ACM SIGGRAPH 2012 Courses, ACM, New York, NY, USA, SIGGRAPH '12, 20:1--20:50. Google Scholar
Digital Library
- Stam, J. 1999. Stable fluids. In SIGGRAPH 1999, 121--128. Google Scholar
Digital Library
- Stanton, M., Sheng, Y., Wicke, M., Perazzi, F., Yuen, A., and andAdrien Treuille, S. N. 2013. Non-polynomial galerkin projection on deforming meshes. ACM Trans. Graph. 32 (July). Google Scholar
Digital Library
- Treuille, A., Lewis, A., and Popović, Z. 2006. Model reduction for real-time fluids. ACM Transactions on Graphics 25, 3 (July), 826--834. Google Scholar
Digital Library
- Vasilescu, M. A. O., and Terzopoulos, D. 2004. Tensortextures: multilinear image-based rendering. ACM Trans. Graph. 23, 3 (Aug.), 336--342. Google Scholar
Digital Library
- Wicke, M., Stanton, M., and Treuille, A. 2009. Modular bases for fluid dynamics. ACM Trans. on Graphics 28, 3 (Aug.), 39. Google Scholar
Digital Library
Index Terms
Subspace fluid re-simulation
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