Dennison, R. and Maddock, S. orcid.org/0000-0003-3179-0263 (2024) Using the polynomial particle-in-cell method for liquid-fabric interaction. In: 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024). GRAPP 2024: 19th International Conference on Computer Graphics Theory and Applications, 27-29 Feb 2024, Rome, Italy. SCITEPRESS (Science and Technology Publications) , pp. 244-251. ISBN 9789897586798
Abstract
Liquid-fabric interaction simulations using particle-in-cell (PIC) based models have been used to simulate a wide variety of phenomena and yield impressive visual results. However, these models suffer from numerical damping due to the data interpolation between the particles and grid. Our paper addresses this by using the polynomial PIC (PolyPIC) model instead of the affine PIC (APIC) model that is used in current state-of-the art wet cloth models. Theoretically, PolyPIC has lossless energy transfer and so should avoid any problems of undesirable damping and numerical viscosity. Our results show that PolyPIC does enable more dynamic coupled simulations. The use of PolyPIC allows for simulations with reduced numerical dissipation and improved resolution of vorticial details over previous work. For smaller scale simulations, there is minimal impact on computational performance when using PolyPIC instead of APIC. However, as simulations involve a larger number of particles and mesh elements, PolyPIC can require up to a 2.5× as long to generate 4.0s of simulation due to a requirement for a decrease in timestep size to remain stable.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 by SCITEPRESS – Science and Technology Publications. Paper published under CC license (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Keywords: | Physically-Based Modeling; Fluid Simulation; Cloth Simulation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Mar 2024 15:43 |
Last Modified: | 08 Mar 2024 17:10 |
Status: | Published |
Publisher: | SCITEPRESS (Science and Technology Publications) |
Refereed: | Yes |
Identification Number: | 10.5220/0012359300003660 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209828 |