Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

A Ship Mission Reliability Modeling Method Based on GTST in Schematic Design Phase

Authors
Yang Jianjun, Li Fang
Corresponding Author
Yang Jianjun
Available Online June 2015.
DOI
10.2991/kam-15.2015.22How to use a DOI?
Keywords
ship mission reliability; schematic design; GTST; simulation.
Abstract

As the existing modeling methods for ship mission reliability are unable to effectively calculate the accuracy of mission reliability, this paper proposes a modeling method that divides a ship mission reliability model into the upper part and the lower part. The upper part is a complete mission profile based on meta task, while the lower part reflects the relations between mission and equipment through GTST. The Monte-Carlo method is employed to design the simulation algorithm for ship mission reliability, which takes into account the time to repair some equipment and is able to effectively address the relevance of mission phases. The operability and correctness of this method is illustrated with the mission reliability modeling and simulation of regular ship navigation.

Copyright
© 2015, 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 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
10.2991/kam-15.2015.22
ISSN
1951-6851
DOI
10.2991/kam-15.2015.22How to use a DOI?
Copyright
© 2015, 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  - Yang Jianjun
AU  - Li Fang
PY  - 2015/06
DA  - 2015/06
TI  - A Ship Mission Reliability Modeling Method Based on GTST in Schematic Design Phase
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 76
EP  - 81
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.22
DO  - 10.2991/kam-15.2015.22
ID  - Jianjun2015/06
ER  -