A comparison of linear consistent correction methods for first-order SPH derivatives

Simple item page
dc.contributor.authorWesthofen, Lukasen_US
dc.contributor.authorJeske, Stefanen_US
dc.contributor.authorBender, Janen_US
dc.contributor.editorWang, Huaminen_US
dc.contributor.editorYe, Yutingen_US
dc.contributor.editorVictor Zordanen_US
dc.date.accessioned2023-10-16T12:33:46Z
dc.date.available2023-10-16T12:33:46Z
dc.date.issued2023
dc.description.abstractAwell-known issue with the widely used Smoothed Particle Hydrodynamics (SPH) method is the neighborhood deficiency. Near the surface, the SPH interpolant fails to accurately capture the underlying fields due to a lack of neighboring particles. These errors may introduce ghost forces or other visual artifacts into the simulation. In this work we investigate three different popular methods to correct the first-order spatial derivative SPH operators up to linear accuracy, namely the Kernel Gradient Correction (KGC), Moving Least Squares (MLS) and Reproducing Kernel Particle Method (RKPM). We provide a thorough, theoretical comparison in which we remark strong resemblance between the aforementioned methods. We support this by an analysis using synthetic test scenarios. Additionally, we apply the correction methods in simulations with boundary handling, viscosity, surface tension, vorticity and elastic solids to showcase the reduction or elimination of common numerical artifacts like ghost forces. Lastly, we show that incorporating the correction algorithms in a state-of-the-art SPH solver only incurs a negligible reduction in computational performance.en_US
dc.description.number3
dc.description.sectionheadersFluids and Points
dc.description.seriesinformationProceedings of the ACM on Computer Graphics and Interactive Techniques
dc.description.volume6
dc.identifier.doi10.1145/3606933
dc.identifier.issn2577-6193
dc.identifier.urihttps://doi.org/10.1145/3606933
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3606933
dc.publisherACM Association for Computing Machineryen_US
dc.subjectCCS Concepts: Computing methodologies -> Physical simulation smoothed particle hydrodynamics, computer animation, moving least squares, reproducing kernel particle method"
dc.subjectComputing methodologies
dc.subjectPhysical simulation smoothed particle hydrodynamics
dc.subjectcomputer animation
dc.subjectmoving least squares
dc.subjectreproducing kernel particle method"
dc.titleA comparison of linear consistent correction methods for first-order SPH derivativesen_US
Files
Collections
SCA 2023: Eurographics/SIGGRAPH Symposium on Computer Animation