research-article

Recovering Turbulence Details using Velocity Correction for SPH Fluids

Authors:

Cong WangAuthors Info & Claims

SA '19: SIGGRAPH Asia 2019 Technical Briefs

Pages 95 - 98

https://doi.org/10.1145/3355088.3365145

Published: 17 November 2019 Publication History

Abstract

In general, kinetic energy of water molecules at translational rotational degree of freedoms (DOFs) occupies the dominant position. However, coarse space discretization always results in severe numerical dissipation if only the linear kinetic energy is considered. Therefore, we proposed a novel turbulence refinement method using velocity correction for SPH simulation. In this method, surface details were enhanced by recovering the energy lost in DOFs for SPH particles. We used a free vortex model to convert particles’ diffused and stretched angular kinetic energy to its neighbours’ linear kinetic energy. Turbulence details would be efficiently generated using the shear between slices. Compared with previous methods, our method can generate turbulence and vortex more vividly and stably.

References

[1]

Alexis Angelidis and Fabrice Neyret. 2005. Simulation of smoke based on vortex filament primitives. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation. ACM, 87–96.

Digital Library

[2]

Cx K Batchelor and GK Batchelor. 1967. An introduction to fluid dynamics. Cambridge university press.

[3]

Jan Bender and Dan Koschier. 2015. Divergence-free smoothed particle hydrodynamics. In Proceedings of the 14th ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, 147–155.

Digital Library

[4]

Jan Bender, Dan Koschier, Tassilo Kugelstadt, and Marcel Weiler. 2018. Turbulent Micropolar SPH Fluids with Foam. IEEE transactions on visualization and computer graphics (2018).

[5]

Mengyu Chu and Nils Thuerey. 2017. Data-driven synthesis of smoke flows with CNN-based feature descriptors. ACM Transactions on Graphics (TOG) 36, 4 (2017), 69.

Digital Library

[6]

Ronald Fedkiw, Jos Stam, and Henrik Wann Jensen. 2001. Visual simulation of smoke. (2001), 15–22.

[7]

de Goes Fernando, Wallez Corentin, and Huang Jin. 2015. Power particles:an incompressible fluid solver based on power diagrams. ACM Transactions on Graphics 34, 4 (2015), 1–11.

[8]

Markus Ihmsen, Jens Cornelis, Barbara Solenthaler, Christopher Horvath, and Matthias Teschner. 2014. Implicit incompressible SPH. IEEE Transactions on Visualization and Computer Graphics 20, 3(2014), 426–435.

Digital Library

[9]

Theodore Kim, Jerry Tessendorf, and Nils Thuerey. 2013. Closest point turbulence for liquid surfaces. ACM Transactions on Graphics (TOG) 32, 2 (2013), 15.

Digital Library

[10]

Dan Koschier, Jan Bender, Barbara Solenthaler, and Matthias Teschner. 2019. Smoothed Particle Hydrodynamics Techniques for the Physics Based Simulation of Fluids and Solids. (2019).

[11]

Michael Lentine, Mridul Aanjaneya, and Ronald Fedkiw. 2011. Mass and momentum conservation for fluid simulation. In Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, 91–100.

Digital Library

[12]

Matthias Müller, David Charypar, and Markus Gross. 2003. Particle-based fluid simulation for interactive applications. In Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation. Eurographics Association, 154–159.

Digital Library

[13]

Sang Il Park and Myoung Jun Kim. 2005. Vortex fluid for gaseous phenomena. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation. ACM, 261–270.

Digital Library

[14]

Tobias Pfaff, Nils Thuerey, and Markus Gross. 2012. Lagrangian vortex sheets for animating fluids. ACM Transactions on Graphics (TOG) 31, 4 (2012), 112.

Digital Library

[15]

Jos. Stam. 1999. Stable fluids. ACM Transactions on Graphics(1999), 121–128.

[16]

John Steinhoff and David Underhill. 1994. Modification of the Euler equations for “vorticity confinement”: Application to the computation of interacting vortex rings. Physics of Fluids - PHYS FLUIDS 6 (08 1994), 2738–2744. https://doi.org/10.1063/1.868164

[17]

Bo Zhu, Xubo Yang, and Ye Fan. 2010. Creating and preserving vortical details in sph fluid. In Computer Graphics Forum, Vol. 29. Wiley Online Library, 2207–2214.

Cited By

Cheng JLiu ZLiu TChai Y(2024)A Parallel Ice Melting Simulation Based on ParticleBiologically Inspired Cognitive Architectures 202310.1007/978-3-031-50381-8_23(197-207)Online publication date: 14-Feb-2024
https://doi.org/10.1007/978-3-031-50381-8_23
Liu ZXu YWang XBan XZheng Z(2021)Simulation and visualization of solid-liquid phase transition and interactive using particle-based method2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)10.1109/CCCI52664.2021.9583207(1-5)Online publication date: 15-Oct-2021
https://doi.org/10.1109/CCCI52664.2021.9583207
Liu SBan XZeng XZhao FGao YWu WZhang HChen FHall TGao XXu M(2020)A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulationBMC Bioinformatics10.1186/s12859-020-03660-w21:1Online publication date: 9-Sep-2020
https://doi.org/10.1186/s12859-020-03660-w
Show More Cited By

Index Terms

Recovering Turbulence Details using Velocity Correction for SPH Fluids
1. Computing methodologies
  1. Computer graphics
    1. Animation
      1. Physical simulation
    2. Shape modeling
  2. Modeling and simulation
2. Mathematics of computing
  1. Continuous mathematics
    1. Topology
      1. Geometric topology

Index terms have been assigned to the content through auto-classification.

Recommendations

Convergent turbulence refinement toward irrotational vortex
SIGGRAPH '19: ACM SIGGRAPH 2019 Posters

We proposed a detail refinement method to enhance the visual effect of turbulence in irrotational vortex. We restore the missing angular velocity from the particles and convert them into linear velocity to recover turbulent detail due to numerical ...
Ghost SPH for animating water

We propose a new ghost fluid approach for free surface and solid boundary conditions in Smoothed Particle Hydrodynamics (SPH) liquid simulations. Prior methods either suffer from a spurious numerical surface tension artifact or drift away from the mass ...
A conservative SPH method for surfactant dynamics

In this paper, a Lagrangian particle method is proposed for the simulation of multiphase flows with surfactant. The model is based on the multiphase smoothed particle hydrodynamics (SPH) framework of Hu and Adams (2006) [1]. Surface-active agents (...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

SA '19: SIGGRAPH Asia 2019 Technical Briefs

November 2019

121 pages

ISBN:9781450369459

DOI:10.1145/3355088

Copyright © 2019 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]

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 November 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

The National Key Research and Development Program of China
National Natural Science Foundation of China

Conference

SA '19

Sponsor:

SIGGRAPH

SA '19: SIGGRAPH Asia 2019

November 17 - 20, 2019

QLD, Brisbane, Australia

Acceptance Rates

Overall Acceptance Rate 178 of 869 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
202
Total Downloads

Downloads (Last 12 months)23
Downloads (Last 6 weeks)1

Reflects downloads up to 26 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Cheng JLiu ZLiu TChai Y(2024)A Parallel Ice Melting Simulation Based on ParticleBiologically Inspired Cognitive Architectures 202310.1007/978-3-031-50381-8_23(197-207)Online publication date: 14-Feb-2024
https://doi.org/10.1007/978-3-031-50381-8_23
Liu ZXu YWang XBan XZheng Z(2021)Simulation and visualization of solid-liquid phase transition and interactive using particle-based method2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)10.1109/CCCI52664.2021.9583207(1-5)Online publication date: 15-Oct-2021
https://doi.org/10.1109/CCCI52664.2021.9583207
Liu SBan XZeng XZhao FGao YWu WZhang HChen FHall TGao XXu M(2020)A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulationBMC Bioinformatics10.1186/s12859-020-03660-w21:1Online publication date: 9-Sep-2020
https://doi.org/10.1186/s12859-020-03660-w
Wang XLiu SBan XXu YZhou JKosinka J(2020)Robust turbulence simulation for particle-based fluids using the Rankine vortex model2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW50115.2020.00179(656-657)Online publication date: Mar-2020
https://doi.org/10.1109/VRW50115.2020.00179
Liu SWang BBan X(2020)Multiple-scale Simulation Method for Liquid with Trapped Air under Particle-based Framework2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)10.1109/VR46266.2020.00109(842-850)Online publication date: Mar-2020
https://doi.org/10.1109/VR46266.2020.00109
Wang XLiu SBan XXu YZhou JKosinka J(2020)Robust turbulence simulation for particle-based fluids using the Rankine vortex modelThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01914-536:10-12(2285-2298)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s00371-020-01914-5

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 Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents