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A framework to improve the naval survivability design process based on the vulnerability of a platform's systems

Friebe, M, Skahen, D and Aksu, S 2019 , 'A framework to improve the naval survivability design process based on the vulnerability of a platform's systems' , Ocean Engineering, vol. 173 , pp. 677-686 , doi: 10.1016/j.oceaneng.2018.12.074.

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Abstract

Offshore Patrol Vessels (OPVs) are a relatively small type of vessel designed for quick naval defence response in littoral zone. OPVs also have a complex system layout, because they are constructed to include both commercial and naval aspects with functionality to facilitate its operational defence duties and capability. Furthermore, this complex system layout may not be optimised for survivability. This study presents a novel framework to examine survivability related system and functional dependencies of an actual OPV, combining different modelling techniques. The OPV is modelled and analysed using a physics-based vulnerability assessment model and integrated into a dynamic system supply and demand model. The output is then analysed through a machine learning algorithm to identify functional relationships between systems and the vessel's operational capabilities to then build a Bayesian Network for further analysis. The Bayesian Network model is used to identify single point failures and analyse the OPV's equipment/on-board systems for sensitivity to the survivability of the platform. The results demonstrate the ability of the machine learning algorithm to build a Bayesian Network that can effectively improve the naval design process and subsequently contribute to enhancing the survivability of OPVs.

Item Type: Article
Authors/Creators:Friebe, M and Skahen, D and Aksu, S
Keywords: Bayesian Network, Ship survivability
Journal or Publication Title: Ocean Engineering
Publisher: Pergamon-Elsevier Science Ltd
ISSN: 0029-8018
DOI / ID Number: 10.1016/j.oceaneng.2018.12.074
Copyright Information:

Copyright 2019 Elsevier Ltd.

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