Just a quick note to say that the pre-print for our paper on particle physics for real-time applications is now available. Visit the project page for all the downloads, or check out the submission video below:
The paper contains most of the practical knowledge and insight about Position-Based Dynamics that I gained while developing Flex. In addition, it introduces a few new features such as implicit friction and smoke simulation.
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FLEX is the name of the new GPU physics solver I have been working on at NVIDIA. It was announced at the Montreal editor's day a few weeks ago, and today we have released some more information in the form of a video trailer and a Q&A with the PhysX fan site.
The solver builds on my Position Based Fluids work, but adds many new features such as granular materials, clothing, pressure constraints, lift + drag model, rigid bodies with plastic deformation, and more.
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Slides for my SIGGRAPH presentation of Position Based Fluids are available here:
http://mmacklin.com/pbf_slides.pdf
During the presentation I showed videos of some more recent results including two-way coupling of fluids with clothing and rigid bodies. They're embedded below:
Overall it has been a great SIGGRAPH, I met tons of new people who provided lots of inspiration for new research ideas. Thanks!
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Position Based Fluids (PBF) is the title of our paper that has been accepted for presentation at SIGGRAPH 2013. I've set up a project page where you can download the paper and all the related content here:
http://blog.mmacklin.com/publications
I have continued working on the technique since the submission, mainly improving the rendering, and adding features like spray and foam (based on the excellent paper from the University of Freiburg: Unified Spray, Foam and Bubbles for Particle-Based Fluids).
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This post is about generating meshes for finite element simulations. I'll be covering other aspects of FEM based simulation in a later post, until then I recommend checking out Matthias Müller's very good introduction in the SIGGRAPH 2008 Real Time Physics course [1].
After spending the last few weeks reading, implementing and debugging meshing algorithms I have a new-found respect for people in this field. It is amazing how many ways meshes can "go wrong", even the experts have it tough:
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This is a quick post to document some work I did while writing a mass spring simulation using an implicit integrator. Implicit, or backward Euler integration is well described in David Baraff's Physically Based Modelling SIGGRAPH course and this post assumes some familiarity with it.
Springs are a workhorse in physical simulation, once you have unconditionally stable springs you can use them to model just about anything, from rigid bodies to drool and snot.
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