Adaptive Sampling in Position-Based Fluids (DAEV)

Position-Based Fluids (PBF) are a Lagrangian fluid-simulation method and are an implementation of Smoothed Particle Hydrodynamics integrated into the Position-Based Dynamics (PBD) framework. In PBD, constraints applied to object positions are used to enforce a variety of physical laws. In the case of PBF, the fluid is represented by particles and constraints are added that prevent fluid compression. The original PBF method defines all particles to be of equal mass and rest density. Our method generalizes PBF to allow particles to represent varying amounts of fluid. This enables the fluid to be simulated with regionally varying levels of detail with the intent to reduce memory consumption and to increase performance. We evaluated our method with an implementation running on the GPU.