Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

3D Mesh Generation Based on Improved Advancing Front Method

Authors
Qianru Xie, Guohua Geng
Corresponding Author
Qianru Xie
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.33How to use a DOI?
Keywords
mesh generation; AFT; Octree
Abstract
Being able to generate 3D meshes automatically is an important issue in the domain of finite element analysis. A novel algorithm of 3D finite element mesh generation is proposed. The algorithm combines the Octree and advancing front technology to create meshes which have significantly higher quality and lower computational cost than single method. The key step and the main contribution of this work are to apply background grid to control the density and size of mesh, simultaneously reduce the intersection computation costs when internal units are generated. First the background grid is constructed using the Octree, and then the model surface is triangulated according to background grid. After that 3D entity unit is constructed and the whole mesh is optimized finally. The experiments results indicate that, compared with advancing front technology, the increment for its efficiency is about 20%, which reduce the time complexity.
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Proceedings
2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2017
ISBN
978-94-6252-324-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/msam-17.2017.33How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Qianru Xie
AU  - Guohua Geng
PY  - 2017/03
DA  - 2017/03
TI  - 3D Mesh Generation Based on Improved Advancing Front Method
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 147
EP  - 151
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.33
DO  - https://doi.org/10.2991/msam-17.2017.33
ID  - Xie2017/03
ER  -