Neural Implicit Reduced Fluid Simulation

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dc.contributor.authorTao, Yuanyuanen_US
dc.contributor.authorPuhachov, Ivanen_US
dc.contributor.authorNowrouzezahrai, Dereken_US
dc.contributor.authorKry, Paulen_US
dc.contributor.editorZordan, Victoren_US
dc.date.accessioned2024-08-20T08:28:08Z
dc.date.available2024-08-20T08:28:08Z
dc.date.issued2024
dc.description.abstractHigh-fidelity simulation of fluid dynamics is challenging because of the high dimensional state data needed to capture fine details and the large computational cost associated with advancing the system in time. We present neural implicit reduced fluid simulation (NIRFS), a reduced fluid simulation technique that combines a neural-implicit representation of fluid shapes and a neural ordinary differential equation to model the dynamics of fluid in the reduced latent space. Trajectories for NIRFS can be computed at very little cost in comparison to simulations for generating training data, while preserving many of the fine details. We show that this approach can work well, capturing the shapes and dynamics involved in a variety of scenarios with constrained initial conditions, e.g., droplet-droplet collisions, crown splashes, and fluid slosh in a container. In each scenario, we learn the latent implicit representation of fluid shapes with a deep-network signed distance function, as well as the energy function and parameters of a damped Hamiltonian system, which helps guarantee desirable properties of the latent dynamics. To ensure that latent shape representations form smooth and physically meaningful trajectories, we simultaneously learn the latent representation and dynamics. We evaluate novel simulations for conservation of volume and momentum conservation, discuss design decisions, and demonstrate an application of our method to fluid control.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animation - Posters
dc.identifier.doi10.2312/sca.20241166
dc.identifier.isbn978-3-03868-263-9
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/sca.20241166
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/sca20241166
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Modeling and simulation; Computer graphics; Artificial intelligence
dc.subjectComputing methodologies → Modeling and simulation
dc.subjectComputer graphics
dc.subjectArtificial intelligence
dc.titleNeural Implicit Reduced Fluid Simulationen_US
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