Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)

A Rapid Parametric Modeling Method of SWATH Based on Siemens NX Extended Development

Authors
Qu Yang, Guan Guan, Yan Lin, Lei Wang
Corresponding Author
Qu Yang
Available Online April 2018.
DOI
https://doi.org/10.2991/cmsa-18.2018.2How to use a DOI?
Keywords
SWATH; siemens NX extended development; parametric modeling
Abstract

A rapid parametric modeling method capable to automatically build and modify the form of SWATH based on Siemens NX extended development is described, aiming at solving the problem of long time consuming and low utilization of the traditional SWATH modeling method. The underwater hull and strut are parameterized based on the analysis of SWATH profile. The modeling strategy is driven by the extended development program with the use of UG/OPEN API tool provided by Siemens NX. The validity of the method is proven in the case of a 2.7m SWATH experimental model. The method can provide a flexible model for subsequent design and optimization.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
April 2018
ISBN
10.2991/cmsa-18.2018.2
ISSN
1951-6851
DOI
https://doi.org/10.2991/cmsa-18.2018.2How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qu Yang
AU  - Guan Guan
AU  - Yan Lin
AU  - Lei Wang
PY  - 2018/04
DA  - 2018/04
TI  - A Rapid Parametric Modeling Method of SWATH Based on Siemens NX Extended Development
BT  - Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
PB  - Atlantis Press
SP  - 4
EP  - 7
SN  - 1951-6851
UR  - https://doi.org/10.2991/cmsa-18.2018.2
DO  - https://doi.org/10.2991/cmsa-18.2018.2
ID  - Yang2018/04
ER  -