article

Keyframe control of smoke simulations

Authors:

Adrien Treuille,

Antoine McNamara,

Zoran Popović,

Jos StamAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 22, Issue 3

Pages 716 - 723

https://doi.org/10.1145/882262.882337

Published: 01 July 2003 Publication History

Abstract

We describe a method for controlling smoke simulations through user-specified keyframes. To achieve the desired behavior, a continuous quasi-Newton optimization solves for appropriate "wind" forces to be applied to the underlying velocity field throughout the simulation. The cornerstone of our approach is a method to efficiently compute exact derivatives through the steps of a fluid simulation. We formulate an objective function corresponding to how well a simulation matches the user's keyframes, and use the derivatives to solve for force parameters that minimize this function. For animations with several keyframes, we present a novel multiple-shooting approach. By splitting large problems into smaller overlapping subproblems, we greatly speed up the optimization process while avoiding certain local minima.

Supplementary Material

MP4 File (mcnamara_treuille_keyframe.mp4)

Download
35.00 MB

References

[1]

ASCHER, U. M., MATTHEIJ, R. M. M., AND RUSELL, R. D. 1988. Numerical Solution of Boundary Value Problems for Ordinary Differential Equations. Prentice-Hall, Englewood Cliffs, New Jersey.

[2]

BEWLEY, T. R., MOIN, P., AND TEMAM, R. 2001. Dns-based predictive control of turbulence: an optimal benchmark for feedback algorithms. Journal of Fluid Mechanics 447, 179--225.

[3]

BEWLEY, T. R. 2001. Flow control: new challenges for a new renaissance. Progress in Aerospace Sciences 37, 21--58.

[4]

BEWLEY, T. R. 2002. The emerging roles of model-based control theory in fluid mechanics. In Advances in Turbulence IX. Proceedings of the Ninth European Turbulence Conference.

[5]

CHEN, J. X., DA VITTORIA LOBO, N., HUGHES, C. E., AND MOSHELL, J. M. 1997. Real-Time Fluid Simulation in a Dynamic Virtual Environment. IEEE Computer Graphics and Applications (May-June), 52--61.

Digital Library

[6]

CHENNEY, S., AND FORSYTH, D. A. 2000. Sampling Plausible Solutions to Multi-body Constraint Problems. In Computer Graphics (SIGGRAPH 2000), ACM, 219--228.

Digital Library

[7]

ENRIGHT, D., MARSCHNER, S., AND FEDKIW, R. 2002. Animation and Rendering of Complex Water Surfaces. In Computer Graphics (SIGGRAPH 2002), ACM, 736--744.

Digital Library

[8]

FEDKIW, R., STAM, J., AND JENSEN, H. 2001. Visual Simulation of Smoke. In Computer Graphics (SIGGRAPH 2001), ACM, 15--22.

Digital Library

[9]

FOSTER, N., AND FEDKIW, R. 2001. Practical Animation of Liquids. In Computer Graphics (SIGGRAPH 2001), ACM, 23--30.

Digital Library

[10]

FOSTER, N., AND METAXAS, D. 1996. Realistic Animation of Liquids. Graphical Models and Image Processing 58, 5, 471--483.

Digital Library

[11]

FOSTER, N., AND METAXAS, D. 1997. Controlling fluid animation. Computer Graphics International, 178--188.

Digital Library

[12]

FOSTER, N., AND METAXAS, D. 1997. Modeling the Motion of a Hot, Turbulent Gas. In Computer Graphics (SIGGRAPH 97), ACM, 181--188.

Digital Library

[13]

GHIL, M., IDE, K., BENNETT, A. F., COURTIER, P., KIMOTO, M., AND (EDS.), N. S. 1997. Data Assimilation in Meteorology and Oceanography: Theory and Practice,. Meteorological Society of Japan and Universal Academy Press.

[14]

KAJIYA, J. T., AND VON HERZEN, B. P. 1984. Ray Tracing Volume Densities. Computer Graphics (SIGGRAPH 84) 18, 3 (July), 165--174.

Digital Library

[15]

NGUYEN, D., FEDKIW, R., AND JENSEN, H. 2002. Physically Based Modeling and Animation of Fire. In Computer Graphics (SIGGRAPH 2002), ACM, 736--744.

Digital Library

[16]

POPOVIĆ, J., SEITZ, S. M., ERDMANN, M., POPOVIĆ, Z., AND WITKIN, A. 2000. Interactive Manipulation of Rigid Body Simulations. In Computer Graphics (SIGGRAPH 2000), ACM, 209--218.

Digital Library

[17]

POPOVIĆ, J. 2001. Interactive Design of Rigid-Body Simulatons for Computer Animation. PhD thesis, Carnegie Mellon University.

Digital Library

[18]

STAM, J. 1999. Stable Fluids. In Computer Graphics (SIGGRAPH 99), ACM, 121--128.

Digital Library

[19]

STOER, J., AND BULIRSCH, R. 1993. Introduction to Numerical Analysis, 2nd ed. Springer.

[20]

WITTING, P. 1999. Computational Fluid Dynamics in a Traditional Animation Environment. In Computer Graphics (SIGGRAPH 99), ACM, 129--136.

Digital Library

[21]

ZHU, C., BYRD, R., LU, P., AND NOCEDAL, J., 1994. Lbfgs-b: Fortran subroutines for large-scale bound constrained optimization.

Cited By

Jin XXu CGao RWu JWang GLi S(2024)DiffSound: Differentiable Modal Sound Rendering and Inverse Rendering for Diverse Inference TasksACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657493(1-12)Online publication date: 13-Jul-2024
https://dl.acm.org/doi/10.1145/3641519.3657493
Xie HArihara KSato SMiyata K(2024)DualSmoke: Sketch-based smoke illustration design with two-stage generative modelComputational Visual Media10.1007/s41095-022-0318-0Online publication date: 8-Feb-2024
https://doi.org/10.1007/s41095-022-0318-0
Chu KHuang JTakana HKitamura Y(2023)Real-Time Reconstruction of Fluid Flow under Unknown DisturbanceACM Transactions on Graphics10.1145/362401143:1(1-14)Online publication date: 17-Oct-2023
https://dl.acm.org/doi/10.1145/3624011
Show More Cited By

Index Terms

Keyframe control of smoke simulations
1. Computing methodologies
  1. Computer graphics
    1. Animation

Recommendations

Fluid control using the adjoint method

We describe a novel method for controlling physics-based fluid simulations through gradient-based nonlinear optimization. Using a technique known as the adjoint method, derivatives can be computed efficiently, even for large 3D simulations with millions ...
Keyframe control of smoke simulations
SIGGRAPH '03: ACM SIGGRAPH 2003 Papers

We describe a method for controlling smoke simulations through user-specified keyframes. To achieve the desired behavior, a continuous quasi-Newton optimization solves for appropriate "wind" forces to be applied to the underlying velocity field ...
Pattern-guided smoke animation with lagrangian coherent structure

Fluid animation practitioners face great challenges from the complexity of flow dynamics and the high cost of numerical simulation. A major hindrance is the uncertainty of fluid behavior after simulation resolution increases and extra turbulent effects ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 22, Issue 3

July 2003

683 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/882262

Issue’s Table of Contents

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2003

Published in TOG Volume 22, Issue 3

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

188
Total Citations
View Citations
1,875
Total Downloads

Downloads (Last 12 months)13
Downloads (Last 6 weeks)2

Reflects downloads up to 23 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Jin XXu CGao RWu JWang GLi S(2024)DiffSound: Differentiable Modal Sound Rendering and Inverse Rendering for Diverse Inference TasksACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657493(1-12)Online publication date: 13-Jul-2024
https://dl.acm.org/doi/10.1145/3641519.3657493
Xie HArihara KSato SMiyata K(2024)DualSmoke: Sketch-based smoke illustration design with two-stage generative modelComputational Visual Media10.1007/s41095-022-0318-0Online publication date: 8-Feb-2024
https://doi.org/10.1007/s41095-022-0318-0
Chu KHuang JTakana HKitamura Y(2023)Real-Time Reconstruction of Fluid Flow under Unknown DisturbanceACM Transactions on Graphics10.1145/362401143:1(1-14)Online publication date: 17-Oct-2023
https://dl.acm.org/doi/10.1145/3624011
James DLevin D(2023)ViCMA: Visual Control of Multibody AnimationsSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618223(1-11)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618223
Jia SWang SLi TChern A(2023)Physical Cyclic AnimationsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36069386:3(1-18)Online publication date: 24-Aug-2023
https://dl.acm.org/doi/10.1145/3606938
Tang JKim BAzevedo VSolenthaler B(2023)Physics‐Informed Neural Corrector for Deformation‐based Fluid ControlComputer Graphics Forum10.1111/cgf.1475142:2(161-173)Online publication date: 23-May-2023
https://doi.org/10.1111/cgf.14751
Sivakumaran GPaquette EMould D(2022)Time Reversal and Simulation Merging for Target-Driven Fluid AnimationProceedings of the 15th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3561975.3562952(1-9)Online publication date: 3-Nov-2022
https://dl.acm.org/doi/10.1145/3561975.3562952
Ren BYe XPan ZZhang T(2022)Versatile Control of Fluid-directed Solid Objects Using Multi-task Reinforcement LearningACM Transactions on Graphics10.1145/355473142:2(1-14)Online publication date: 18-Oct-2022
https://dl.acm.org/doi/10.1145/3554731
Goel PJames D(2022)Unified many-worlds browsing of arbitrary physics-based animationsACM Transactions on Graphics10.1145/3528223.353008241:4(1-15)Online publication date: 22-Jul-2022
https://dl.acm.org/doi/10.1145/3528223.3530082
Li YDu TWu KXu JMatusik W(2022)DiffCloth: Differentiable Cloth Simulation with Dry Frictional ContactACM Transactions on Graphics10.1145/352766042:1(1-20)Online publication date: 3-Oct-2022
https://dl.acm.org/doi/10.1145/3527660
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents