Particle Importance Based Fluid Simulation.
ABSTRACT We present a novel method using particle importance to accelerate the traditional smoothed particle hydrodynamics based fluid simulation. Reynolds number and vorticity are exploited as the new criteria to evaluate the importance for each particle. If a particle is unimportant, its current acceleration and velocity are used to update values in the next time step with the complex state updating step removed, in this way the computation time is saved. We also propose an improved surface tension model. The experiments demonstrate that this new method is not only easy to implement, but also greatly improves the simulation speed without visual quality sacrifice.
Article: Adaptively sampled particle fluids[show abstract] [hide abstract]
ABSTRACT: 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 distance-based 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. © 2007 ACM.
- [show abstract] [hide abstract]
ABSTRACT: In practical implementations, meshless methods using moving least-squares (MLS) approximation and global Galerkin formulation require a background mesh for domain integration. An adaptive procedure based on background mesh is developed for meshless methods using MLS. It comprises a cell energy error estimate and a local domain refinement technique. The error estimate differs from conventional pointwise approaches in that it evaluates error based on individual cells instead of points. For each cell, a computed cell energy and a reference cell energy are generated based on a same stress field by using two different integration schemes; the difference between the two energy values is used as the basic measure of error estimation. The advantage of this strategy is that it requires only one stress field and no reference field needs to be furnished. This has significance, as the stress field generated by meshless methods is already very smooth and traditional error estimates based on stress smoothing techniques for finite element methods are not applicable. To achieve high efficiency in domain refinement, a local technique based on the Delaunay algorithm is implemented. In this technique, each node is assigned a scaling factor to control local nodal density; refinement of the neighborhood of a node is accomplished simply by adjusting its scaling factor. The numerical experiments in this paper show that the proposed adaptive procedure is simple, effective and efficient. The limitations of the approach are also discussed.Computer Methods in Applied Mechanics and Engineering. 01/2002;
- Eurographics Workshop on Computer Animation and Simulation (EGCAS). 11/1998;