Abstract
Any small leakage in the submarines can lead to serious consecutive damages since it operates under high water pressure. Such leakage including damages on pipe and hull eventually incur human casualties and loss of expensive equipments as well as the loss of combat capabilities. In such cases, a decision-making system is necessary to respond immediately to the damages in order to maintain the safety or the survival of the submarine. So far, human decision has been the most important one based on personal experience, existing data, and any electronic information available. However, it is well recognized that such decisions may not be enough in certain emergency situations. The system that depends on only human experience may cause serious mistakes in devastating and scared situations. So it is necessary to have an automatic system that can generate responses and give advice the operator how to make decisions to maintain the survivability of the damaged vessel. In this paper, a knowledge-based decision support system for submarine safety is developed. The domain knowledge is acquired from the submarine design documents, design expertise, and interviews with operator. The knowledge consists of the responses regarding damage on pressure hull and piping system. Expert Elements are deduced to obtain the decision from the knowledge base, and for instance, the system makes recommendations on how the damages on hull and pipes decision and whether to stay in the sea or to blow. It is confirmed that developed system is well simulated to the real situation throughout sample applications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
H. H Zhou, B. G Silverman, J. Simkol, CLEER: An AI System Developed to Assist Equipment Arrangements on Warship” May 1989, Naval Engineers Journal
R. B. Byrnes, et al “The Rational Behavior Software Architecture for Intelligent Ships” Mar. 1996, Naval Engineer Journal
Chou Y.C., Benjamin CO., “An AI-Based Decision Support System for Naval Ship Design”, Naval Engineers Journal, May 1992
J. H. Graham, R. K. Ragade, J. Shea “Design Decision Support System for the Engineering/Re-engineering of Complex Naval System, July 1997, Naval Engineer Journal
J. G. Shea “Virtual Prototyping using Knowledge-Based Modeling and Simulation Techniques” May 1993, Naval Engineer Journal
J. R. Hardin, et al “A Gas Turbine Condition Monitoring System” Nov. 1995, Naval Engineer Journal
R L. Carting “A Knowledge-Base System for the Threat Evaluation and Weapon Assignment Process”, Jan. 1993, Naval Engineer Journal
J. Garber, J. Bourne, J. Snyder “Hull Structural Survival System” 1997, Advanced Marine Enterprise Ltd.
Scott, A.C, Clayton, J.E, Gibson, E.L “Practical Guide to Knowledge Acquisition” 1991, Addison-Wesley Publishing Company
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, D., Lee, J., Lee, K.H. (2002). A Decision-Support System to Improve Damage Survivability of Submarine. In: Hendtlass, T., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2002. Lecture Notes in Computer Science(), vol 2358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48035-8_40
Download citation
DOI: https://doi.org/10.1007/3-540-48035-8_40
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43781-9
Online ISBN: 978-3-540-48035-8
eBook Packages: Springer Book Archive