research-article

Modular bases for fluid dynamics

Authors:

Adrien TreuilleAuthors Info & Claims

SIGGRAPH '09: ACM SIGGRAPH 2009 papers

Article No.: 39, Pages 1 - 8

https://doi.org/10.1145/1576246.1531345

Published: 27 July 2009 Publication History

Abstract

We present a new approach to fluid simulation that balances the speed of model reduction with the flexibility of grid-based methods. We construct a set of composable reduced models, or tiles, which capture spatially localized fluid behavior. We then precompute coupling terms so that these models can be rearranged at runtime. To enforce consistency between tiles, we introduce constraint reduction. This technique modifies a reduced model so that a given set of linear constraints can be fulfilled. Because dynamics and constraints can be solved entirely in the reduced space, our method is extremely fast and scales to large domains.

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Cited By

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
Flynn SHart DMorse BHolladay SEgbert P(2021)Generalized fluid carving with fast lattice-guided seam computationACM Transactions on Graphics10.1145/3478513.348054440:6(1-15)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1145/3478513.3480544
Bai KWang CDesbrun MLiu X(2021)Predicting high-resolution turbulence details in space and timeACM Transactions on Graphics10.1145/3478513.348049240:6(1-16)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1145/3478513.3480492
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Index Terms

Modular bases for fluid dynamics
1. Computing methodologies
  1. Computer graphics
    1. Animation
  2. Modeling and simulation
    1. Simulation types and techniques
      1. Simulation by animation

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Published In

cover image ACM Conferences

SIGGRAPH '09: ACM SIGGRAPH 2009 papers

July 2009

795 pages

ISBN:9781605587264

DOI:10.1145/1576246

Conference Chair:
Thomas Funkhouser,
Editor:
Hugues Hoppe
ACM Transactions on Graphics

Copyright © 2009 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]

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Published: 27 July 2009

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SIGGRAPH09: Special Interest Group on Computer Graphics and Interactive Techniques Conference

August 3 - 7, 2009

Louisiana, New Orleans

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SIGGRAPH '09 Paper Acceptance Rate 78 of 439 submissions, 18%;

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Cited By

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
Flynn SHart DMorse BHolladay SEgbert P(2021)Generalized fluid carving with fast lattice-guided seam computationACM Transactions on Graphics10.1145/3478513.348054440:6(1-15)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1145/3478513.3480544
Bai KWang CDesbrun MLiu X(2021)Predicting high-resolution turbulence details in space and timeACM Transactions on Graphics10.1145/3478513.348049240:6(1-16)Online publication date: 10-Dec-2021
https://dl.acm.org/doi/10.1145/3478513.3480492
Wiewel SKim BAzevedo VSolenthaler BThuerey NLevin DKry P(2020)Latent space subdivisionProceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation10.1111/cgf.14097(1-11)Online publication date: 6-Oct-2020
https://dl.acm.org/doi/10.1111/cgf.14097
Xiao XZhou YWang HYang X(2020)A Novel CNN-Based Poisson Solver for Fluid SimulationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.287337526:3(1454-1465)Online publication date: 1-Mar-2020
https://doi.org/10.1109/TVCG.2018.2873375
Kim BAzevedo VThuerey NKim TGross MSolenthaler B(2019)Deep Fluids: A Generative Network for Parameterized Fluid SimulationsComputer Graphics Forum10.1111/cgf.1361938:2(59-70)Online publication date: 7-Jun-2019
https://doi.org/10.1111/cgf.13619
Cui QSen PKim T(2018)Scalable laplacian eigenfluidsACM Transactions on Graphics10.1145/3197517.320135237:4(1-12)Online publication date: 30-Jul-2018
https://dl.acm.org/doi/10.1145/3197517.3201352
Umetani NBickel B(2018)Learning three-dimensional flow for interactive aerodynamic designACM Transactions on Graphics10.1145/3197517.320132537:4(1-10)Online publication date: 30-Jul-2018
https://dl.acm.org/doi/10.1145/3197517.3201325
Heggelund YJarvis CKhalil M(2015)A Fast Reduced Order Method for Assessment of Wind Farm LayoutsEnergy Procedia10.1016/j.egypro.2015.11.40380(30-37)Online publication date: 2015
https://doi.org/10.1016/j.egypro.2015.11.403
Huang ZGong GHan L(2015)Physically-based smoke simulation for computer graphicsMultimedia Tools and Applications10.1007/s11042-014-1992-474:18(7569-7594)Online publication date: 1-Sep-2015
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