An Adaptive Model for Particle Fluid Surface Reconstruction

Fengquan ZHANG; Xukun SHEN; Xiang LONG

doi:10.1587/transinf.E96.D.1247

An Adaptive Model for Particle Fluid Surface Reconstruction

Fengquan ZHANG, Xukun SHEN, Xiang LONG

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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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Fengquan ZHANG, Xukun SHEN, Xiang LONG, "An Adaptive Model for Particle Fluid Surface Reconstruction" in IEICE TRANSACTIONS on Information, vol. E96-D, no. 5, pp. 1247-1250, May 2013, doi: 10.1587/transinf.E96.D.1247.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E96.D.1247/_p

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@ARTICLE{e96-d_5_1247,
author={Fengquan ZHANG, Xukun SHEN, Xiang LONG, },
journal={IEICE TRANSACTIONS on Information},
title={An Adaptive Model for Particle Fluid Surface Reconstruction},
year={2013},
volume={E96-D},
number={5},
pages={1247-1250},
abstract={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.},
keywords={},
doi={10.1587/transinf.E96.D.1247},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - An Adaptive Model for Particle Fluid Surface Reconstruction
T2 - IEICE TRANSACTIONS on Information
SP - 1247
EP - 1250
AU - Fengquan ZHANG
AU - Xukun SHEN
AU - Xiang LONG
PY - 2013
DO - 10.1587/transinf.E96.D.1247
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2013
AB - 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.
ER -