Chinese Journal of Ship Research, Volume. 17, Issue 2, 109(2022)

Genetic algorithm based optimization method for kentledge laying of submersibles

Bo TANG1, Kun YANG2, Haibo ZHOU1, Shengjun ZHOU1, and Zhenjin YANG1
Author Affiliations
  • 1Wuhan Second Ship Design and Research Institute, Wuhan 430205, China
  • 2The 92578 Unit of PLA, Beijing 100161, China
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    Objectives

    Typically, the fixed kentledge laying scheme of a submersible requires a significant amount of work and can often produce unpleasant results in engineering practice. Intelligent algorithms are considered for application in order to optimize the scheme. This paper proposes a genetic algorithm based method to solve the problem.

    Methods

    First, by studying typical transverse sections of kentledge laying in a submersible and reverse-thinking the finite element method, a simplified equivalent mathematic model is constructed. Next, constraint functions and objective functions are extracted from the model. By using a genetic algorithm, improved fixed kentledge laying schemes are acquired with lower centers of gravity. By computing different examples, this method is proven to be effective in gaining good gravity center results with a much smaller workload.

    Results

    The result shows that the gravity center of the improved scheme can be 23% lower compared to the ordinary scheme. This method is also effective in balancing longitudinal moment and lateral moment at the same time.

    Conclusions

    This study shows that the equivalent mathematical model and optimization method are feasible, and can improve both work efficiency and gravity results. Several general principles are also concluded, which can be helpful in engineering practice.

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    Bo TANG, Kun YANG, Haibo ZHOU, Shengjun ZHOU, Zhenjin YANG. Genetic algorithm based optimization method for kentledge laying of submersibles[J]. Chinese Journal of Ship Research, 2022, 17(2): 109

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    Paper Information

    Category: Ship Design and Performance

    Received: Jan. 20, 2021

    Accepted: --

    Published Online: Mar. 24, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02271

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