Jumyung “JC” Chang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Christopher Batty
We propose a novel methodology to enhance grid-based fluid animation with pointwise divergence-free velocity interpolation. Our method takes as input a discretely divergence-free staggered grid velocity field generated by a standard pressure projection, and first recovers a consistent corresponding edge-based discrete vector potential in 3D (or node-based stream function in 2D). We interpolate these values to form a pointwise potential, and apply the continuous curl operator to recover a pointwise flow field that is perfectly incompressible. Our method supports irregular geometry through the use of level set-based cut-cells. To recover a smooth and velocity-consistent discrete vector potential in 3D, we employ a sweeping approach followed by a gauge correction that requires a single scalar Poisson solve, rather than a vector Poisson problem. In both 2D and 3D, we show how modified interpolation strategies can be applied to better account for the presence of irregular cut-cell boundaries. Our results demonstrate that our overall proposed Curl-Flow framework produces significantly better particle trajectories that suffer from far fewer spurious sources or sinks, respect irregular obstacles, and better preserve particle distributions over time.
To join this PhD seminar on MS Teams, please go to https://teams.microsoft.com/l/meetup-join/19%3a6b5c8a17d0094e3bb9b59e861a434a0b%40thread.tacv2/1623691355424?context=%7b%22Tid%22%3a%22723a5a87-f39a-4a22-9247-3fc240c01396%22%2c%22Oid%22%3a%22a19a9d53-a3f4-40d5-9078-cf54abd59696%22%7d.
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