Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • ÄŒeÅ¡tina
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • LatvieÅ¡u
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Westhofen, Lukas"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • No Thumbnail Available
    Item
    A comparison of linear consistent correction methods for first-order SPH derivatives
    (ACM Association for Computing Machinery, 2023) Westhofen, Lukas; Jeske, Stefan; Bender, Jan; Wang, Huamin; Ye, Yuting; Victor Zordan
    Awell-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.

Eurographics Association © 2013-2025  |  System hosted at Graz University of Technology      
DSpace software copyright © 2002-2025 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback