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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035311Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221208T153000
DTEND;TZID=Asia/Seoul:20221208T170000
UID:siggraphasia_SIGGRAPH Asia 2022_sess170_papers_416@linklings.com
SUMMARY:Curl-Flow: Boundary-Respecting Pointwise Incompressible Velocity I
 nterpolation for Grid-Based Fluids
DESCRIPTION:Technical Papers\n\nCurl-Flow: Boundary-Respecting Pointwise I
 ncompressible Velocity Interpolation for Grid-Based Fluids\n\nChang, Parto
 no, Azevedo, Batty\n\nWe propose to augment standard grid-based fluid solv
 ers with pointwise divergence-free velocity interpolation, thereby ensurin
 g exact incompressibility down to the sub-cell level. Our method takes as 
 input a discretely divergence-free velocity field generated by a staggered
  grid pressure projection, and first recovers a corresponding discrete vec
 tor potential. Instead of solving a costly vector Poisson problem for the 
 potential, we develop a fast parallel sweeping strategy to find a candidat
 e potential and apply a gauge transformation to enforce the Coulomb gauge 
 condition and thereby make it numerically smooth. Interpolating this discr
 ete potential generates a pointwise vector potential whose analytical curl
  is a pointwise incompressible velocity field. Our method further supports
  irregular solid geometry through the use of level set-based cut-cells and
  a novel Curl-Noise-inspired potential ramping procedure that simultaneous
 ly offers strictly non-penetrating velocities and incompressibility. Exper
 imental comparisons demonstrate that our vector potential reconstruction p
 rocedure is consistently faster than prior methods, especially those that 
 solve vector Poisson problems. Moreover, in exchange for its modest extra 
 cost, our overall Curl-Flow framework produces significantly improved part
 icle trajectories that closely respect irregular obstacles, do not suffer 
 from spurious sources or sinks, and yield superior particle distributions 
 over time.\n\nRegistration Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLang
 uage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_416&sess=sess17
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