An Adaptive Model for Particle Fluid Surface Reconstruction

摘要

In 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.