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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
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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
0
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