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An Adaptive Model for Particle Fluid Surface Reconstruction

Fengquan ZHANG, Xukun SHEN, Xiang LONG

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Summary :

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.

Publication
IEICE TRANSACTIONS on Information Vol.E96-D No.5 pp.1247-1250
Publication Date
2013/05/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E96.D.1247
Type of Manuscript
LETTER
Category
Computer Graphics

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