Research on Knowledge Network Modelling for Aero-craft System Design

Xiang Zhai, Feng Dai, Huiyang Qu, Lingling Zhong, Chenyong Du

2017

Abstract

A great amount of existing knowledge is required during the development of aero-craft system. At present, the existing knowledge organization model construct different knowledge model for different stages is difficult to adapt to the complicated product life cycle application. This study proposes a product development oriented knowledge network model focusing on expressing the knowledge demands and connecting the computer-aided system. Under the overall knowledge network model, this study describes the ontology description method of spacecraft product model, development tasks and aerospace terminology. Recommending missile aerodynamic knowledge within the design stage is presented as a case study, and the framework and the method is proved to be effective.

Download


Paper Citation


in Harvard Style

Zhai X., Dai F., Qu H., Zhong L. and Du C. (2017). Research on Knowledge Network Modelling for Aero-craft System Design . In Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-265-3, pages 240-247. DOI: 10.5220/0006403202400247


in Bibtex Style

@conference{simultech17,
author={Xiang Zhai and Feng Dai and Huiyang Qu and Lingling Zhong and Chenyong Du},
title={Research on Knowledge Network Modelling for Aero-craft System Design},
booktitle={Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2017},
pages={240-247},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006403202400247},
isbn={978-989-758-265-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Research on Knowledge Network Modelling for Aero-craft System Design
SN - 978-989-758-265-3
AU - Zhai X.
AU - Dai F.
AU - Qu H.
AU - Zhong L.
AU - Du C.
PY - 2017
SP - 240
EP - 247
DO - 10.5220/0006403202400247