An Adaptive Model for Particle Fluid Surface Reconstruction

Abstract

SUMMARYIn this letter, we present an efficient method for high quality surface reconstruction from simulation data of smoothed particles hydrodynamics (SPH). For computational efficiency, instead of computing scalar field in overall particle sets, we only construct scalar field around fluid surfaces. Furthermore, an adaptive scalar field model is proposed, which adaptively adjusts the smoothing length of ellipsoidal kernel by a constraint-correction rule. Then the isosurfaces are extracted from the scalar field data. The proposed method can not only effectively preserve fluid details, such as splashes, droplets and surface wave phenomena, but also save computational costs. The experimental results show that our method can reconstruct the realistic fluid surfaces with different particle sets. key words: particle-based fluid, surface reconstruction, adaptive model, scalar field

A fast framework construction and visualization method for particle-based fluid

“…Unfortunately, because the computing of projection is cost expensive, it cannot be used for upsampling points in real time. In [29], an adaptive scalar field model was proposed for reconstructing fluid surface. Although it can generate high quality fluid, its accuracy depends on very large Marching Cube (MC) grids, resulting in the large computational time and memory requirements.…”