Adaptively Sampled Particle Fluids

“We present novel adaptive sampling algorithms for particle-based
fluid simulation. We introduce a sampling condition based on geometric
local feature size that allows focusing computational resources
in geometrically complex regions, while reducing the number
of particles deep inside the fluid or near thick flat surfaces. Further
performance gains are achieved by varying the sampling density
according to visual importance. In addition, we propose a novel
fluid surface definition based on approximate particle–to–surface
distances that are carried along with the particles and updated appropriately.
The resulting surface reconstruction method has several
advantages over existing methods, including stability under
particle resampling and suitability for representing smooth flat surfaces.
We demonstrate how our adaptive sampling and distancebased
surface reconstruction algorithms lead to significant improvements
in time and memory as compared to single resolution particle
simulations, without significantly affecting the fluid flow behavior.”

Adaptively Sampled Particle Fluids


  1. NT says:

    Hmm, I’m having troubles viewing PDFs on the linked website. Can’t open or download any of them.

  2. animationphysics says:

    Yeah, it looks like the PDF links are down. They were up earlier today, so I’m not sure what happened.

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