Visual smoke simulation with adaptive octree refinement

Abstract

Three dimensional fluid simulation becomes expensive on high resolution grids which can easily consume a large amount of physical memory. This paper presents an octree-based algorithm for visual simulation of smoke on ordinary workstations. This method adaptively subdivides the whole simulation volume into multiple subregions using an octree. Each leaf node in the octree also holds a uniform subgrid which is the basic unit for simulation. Because of the octree partition, the physical memory of the workstation only needs to be sufficiently large to hold a small number of subgrids with the majority of the subgrids stored on hard disks. A previous smoke simulation algorithm based on a semi-Lagrangian scheme has been adapted to this hybrid octree-based data structure. A pair of PullUp and Push-Down procedures are designed to solve the Poisson equation for pressure at each octree node. A novel node subdivision and merging scheme is also developed to dynamically adjust the octree during each iteration of the simulation so that regions containing more details are more likely to be subdivided to achieve better accuracy. The result is an algorithm that can solve smoke simulation on large grids using a limited amount of memory.