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Optimal Design of Submarine Pressure Hull Structures using Genetic Algorithm

Cho, Y S; Paik, J; (2017) Optimal Design of Submarine Pressure Hull Structures using Genetic Algorithm. Journal of the Society of Naval Architects of Korea , 54 (4) Green open access

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Abstract

In this paper, a method is presented for the optimal design of submarine pressure hull structures by taking advantage of genetic algorithm techniques. The objective functions and design constraints in the process of structural optimization are based on the ultimate limit states of hull structures. One of the benefits associated with the utilization of genetic algorithm is that the optimization process can be completed within short generations of design variables for the pressure hull structure model. Applied examples confirm that the proposed method is useful for the optimal design of submarine pressure hull structures. Details of the design procedure with applied examples are documented. The conclusions and insights obtained from the study are summarized.

Type: Article
Title: Optimal Design of Submarine Pressure Hull Structures using Genetic Algorithm
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.koreascience.or.kr/journal/AboutJournal...
Additional information: This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited
Keywords: Pressure hull structure(압력선체구조), Optimal design(최적설계), Genetic algorithm(유전알고리즘), Objective function(목 적함수)
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10057427
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