Special CMX Seminar

While Computer Graphics (CG) has often been inspired by Computational Fluid Dynamics (CFD), its most common algorithmic solutions to fluid animation remain limited in scope (they cannot handle high Reynolds numbers and/or high density ratios when simulating water-air interaction) and scalability. As a consequence, they have found little to no industrial applications aside from special effects in movies. In this talk, I will discuss recent progress in Lattice Boltzmann solvers which offer a nice, massively-parallel way to bridge the gap between CG and CFD for both incompressible single-phase and multi-phase fluid simulation using an atypical discretization of phase space. If time allows, I will also discuss recent progress in Machine Learning that offer plausible space-time upsampling of coarse simulations at low computational cost.