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research-article

Divergence-Free SPH for Incompressible and Viscous Fluids

Authors:

Dan KoschierAuthors Info & Claims

IEEE Transactions on Visualization and Computer Graphics, Volume 23, Issue 3

Pages 1193 - 1206

https://doi.org/10.1109/TVCG.2016.2578335

Published: 01 March 2017 Publication History

Abstract

In this paper we present a novel Smoothed Particle Hydrodynamics (SPH) method for the efficient and stable simulation of incompressible fluids. The most efficient SPH-based approaches enforce incompressibility either on position or velocity level. However, the continuity equation for incompressible flow demands to maintain a constant density and a divergence-free velocity field. We propose a combination of two novel implicit pressure solvers enforcing both a low volume compression as well as a divergence-free velocity field. While a compression-free fluid is essential for realistic physical behavior, a divergence-free velocity field drastically reduces the number of required solver iterations and increases the stability of the simulation significantly. Thanks to the improved stability, our method can handle larger time steps than previous approaches. This results in a substantial performance gain since the computationally expensive neighborhood search has to be performed less frequently. Moreover, we introduce a third optional implicit solver to simulate highly viscous fluids which seamlessly integrates into our solver framework. Our implicit viscosity solver produces realistic results while introducing almost no numerical damping. We demonstrate the efficiency, robustness and scalability of our method in a variety of complex simulations including scenarios with millions of turbulent particles or highly viscous materials.

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cover image IEEE Transactions on Visualization and Computer Graphics

IEEE Transactions on Visualization and Computer Graphics Volume 23, Issue 3

March 2017

106 pages

ISSN:1077-2626

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Copyright © 2017.

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IEEE Educational Activities Department

United States

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Published: 01 March 2017

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Cited By

Jain PQu ZChen PStein O(2024)Neural Monte Carlo Fluid SimulationACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657438(1-11)Online publication date: 13-Jul-2024
https://dl.acm.org/doi/10.1145/3641519.3657438
Tu ZLi CZhao ZLiu LWang CWang CQin H(2024)A Unified MPM Framework Supporting Phase-field Models and Elastic-viscoplastic Phase TransitionACM Transactions on Graphics10.1145/363804743:2(1-19)Online publication date: 3-Jan-2024
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Zhang YLong SXu YWang XYao CKosinka JFrey STelea ABan XKry PCani MSkouras MWang H(2024)Multiphase Viscoelastic Non-Newtonian Fluid SimulationProceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation10.1111/cgf.15180(1-12)Online publication date: 21-Aug-2024
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Szabó G(2024)Towards the automatic network resource management of OPC UA in 5G private networksComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2024.110581250:COnline publication date: 1-Aug-2024
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Jeske SWesthofen LLöschner FFernández-fernández JBender J(2023)Implicit Surface Tension for SPH Fluid SimulationACM Transactions on Graphics10.1145/363193643:1(1-14)Online publication date: 30-Nov-2023
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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
Li WWang TPan ZGao XWu KDesbrun M(2023)High-Order Moment-Encoded Kinetic Simulation of Turbulent FlowsACM Transactions on Graphics10.1145/361834142:6(1-13)Online publication date: 5-Dec-2023
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Li ZXu QYe XRen BLiu L(2023)DiffFR: Differentiable SPH-Based Fluid-Rigid Coupling for Rigid Body ControlACM Transactions on Graphics10.1145/361831842:6(1-17)Online publication date: 5-Dec-2023
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