research-article

Multiple-Fluid SPH Simulation Using a Mixture Model

Authors:

Shi-Min HuAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 33, Issue 5

Article No.: 171, Pages 1 - 11

https://doi.org/10.1145/2645703

Published: 23 September 2014 Publication History

Abstract

This article presents a versatile and robust SPH simulation approach for multiple-fluid flows. The spatial distribution of different phases or components is modeled using the volume fraction representation, the dynamics of multiple-fluid flows is captured by using an improved mixture model, and a stable and accurate SPH formulation is rigorously derived to resolve the complex transport and transformation processes encountered in multiple-fluid flows. The new approach can capture a wide range of real-world multiple-fluid phenomena, including mixing/unmixing of miscible and immiscible fluids, diffusion effect and chemical reaction, etc. Moreover, the new multiple-fluid SPH scheme can be readily integrated into existing state-of-the-art SPH simulators, and the multiple-fluid simulation is easy to set up. Various examples are presented to demonstrate the effectiveness of our approach.

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Cited By

Li WWu KDesbrun M(2024)Kinetic Simulation of Turbulent Multifluid FlowsACM Transactions on Graphics10.1145/365817843:4(1-17)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3658178
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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
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Index Terms

Multiple-Fluid SPH Simulation Using a Mixture Model
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 Transactions on Graphics

ACM Transactions on Graphics Volume 33, Issue 5

August 2014

152 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2672594

Editor:
Julie Dorsey
Yale University

Issue’s Table of Contents

Copyright © 2014 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2014

Accepted: 01 April 2014

Revised: 01 March 2014

Received: 01 September 2013

Published in TOG Volume 33, Issue 5

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UNC Carolina Development Foundation
Ser Cymru National Research Network in Advanced Engineering and Materials
Ministry of Science and Technology of the People's Republic of China
National Natural Science Foundation of China
Division of Information and Intelligent Systems

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Li WWu KDesbrun M(2024)Kinetic Simulation of Turbulent Multifluid FlowsACM Transactions on Graphics10.1145/365817843:4(1-17)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3658178
Ni XWang RWang BChen B(2024)An Induce-on-Boundary Magnetostatic Solver for Grid-Based FerrofluidsACM Transactions on Graphics10.1145/365812443:4(1-14)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3658124
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
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Wang XXu YLiu SRen BKosinka JTelea AWang JSong CChang JLi CZhang JBan X(2024)Physics-based fluid simulation in computer graphics: Survey, research trends, and challengesComputational Visual Media10.1007/s41095-023-0368-y10:5(803-858)Online publication date: 27-Apr-2024
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Schmidt MSavoye Y(2024)Fluid SimulationEncyclopedia of Computer Graphics and Games10.1007/978-3-031-23161-2_55(725-730)Online publication date: 5-Jan-2024
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