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DTSTAMP:20240214T070242Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T160000
DTEND;TZID=Australia/Melbourne:20231212T161000
UID:siggraphasia_SIGGRAPH Asia 2023_sess121_papers_671@linklings.com
SUMMARY:An Implicitly Stable Mixture Model for Dynamic Multi-fluid Simulat
 ions
DESCRIPTION:Technical Papers\n\nYanrui Xu (University of Groningen, Univer
 sity of Science and Technology Beijing); Xiaokun Wang (University of Scien
 ce and Technology Beijing, Bournemouth University); Jiamin Wang, Chongming
  Song, Tiancheng Wang, and Yanlan Zhang (University of Science and Technol
 ogy Beijing); Jian Chang and Jianjun Zhang (Bournemouth University); Jiri 
 Kosinka (University of Groningen); Alexandru Telea (Utrecht University); a
 nd Xiaojuan Ban (University of Science and Technology Beijing)\n\nParticle
 -based simulation has become increasingly popular in real-time application
 s due to its efficiency and adaptability, especially in generating highly 
 dynamic fluid effects. Nevertheless, the swift and stable simulation of in
 teractions between distinct fluids continues to pose challenges for curren
 t mixture model techniques. When using a single mixture flow field to repr
 esent all fluid phases, numerical discontinuities in phase fields can resu
 lt in significant losses of dynamic effects and unstable conservation of m
 ass and momentum.\nTo tackle these issues, we present an advanced implicit
  mixture model for smoothed particle hydrodynamics. Instead of relying on 
 an explicit mixture field for all dynamic computations and phase transfers
  between particles, our approach calculates phase momentum sources from th
 e mixture model to derive explicit, continuous velocity phase fields. We t
 hen implicitly obtain the mixture field using our proposed phase-mixture m
 omentum mapping mechanism, ensuring the conservation of incompressibility,
  mass, and momentum. In addition, we propose a mixture viscosity model and
  establish viscous effects between the mixture and individual fluid phases
  to avoid instability under extreme inertia conditions.\nThrough a series 
 of experiments, we show that our method effectively improves dynamic effec
 ts compared to existing mixture models while reducing critical instability
  factors. This makes our approach particularly well-suited for long-durati
 on, efficiency-oriented virtual reality scenarios.\n\nRegistration Categor
 y: Full Access\n\nSession Chair: Christopher Batty (University of Waterloo
 )
URL:https://asia.siggraph.org/2023/full-program?id=papers_671&sess=sess121
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