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Structural Optimization of Cylindrical Pressure Hulls via NSGA-II.

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Title: Structural Optimization of Cylindrical Pressure Hulls via NSGA-II.
Authors: Zhang, Ya1 zhangya_0426@163.com, Tao, Zhicong2 tzc201129@163.com, Wang, Hao2 1204157459@qq.com, Li, Huixin2 2339261662@qq.com, Zeng, Zihao2 627571028@qq.com
Source: IAENG International Journal of Applied Mathematics. Jul2026, Vol. 56 Issue 7, p2657-2666. 10p.
Subjects: Structural optimization, Multi-objective optimization, Response surfaces (Statistics), Genetic algorithms, Latin hypercube sampling, Hulls (Naval architecture), Mechanical buckling
Abstract: To enhance the stability and safety of submersible pressure hull structures in deep-sea environments, this study first conducts a parametric analysis of an initial ring-stiffened cylindrical pressure hull design. The optimal Latin hypercube sampling method is employed to generate sample points and to evaluate the response of design variables to the optimization objectives. A high-fidelity fourth-order response surface model is then constructed, followed by the formulation of a multi-objective optimization model that considers structural mass, strength, and buckling stability as competing objectives. The NSGA-II genetic algorithm is subsequently applied to perform non-dominated sorting and crowding distance calculation. This yields four distinct Pareto-optimal schemes, each exhibiting varying degrees of improvement across the defined objectives. [ABSTRACT FROM AUTHOR]
Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 195026898
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  Data: Structural Optimization of Cylindrical Pressure Hulls via NSGA-II.
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Ya%22">Zhang, Ya</searchLink><relatesTo>1</relatesTo><i> zhangya_0426@163.com</i><br /><searchLink fieldCode="AR" term="%22Tao%2C+Zhicong%22">Tao, Zhicong</searchLink><relatesTo>2</relatesTo><i> tzc201129@163.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Hao%22">Wang, Hao</searchLink><relatesTo>2</relatesTo><i> 1204157459@qq.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Huixin%22">Li, Huixin</searchLink><relatesTo>2</relatesTo><i> 2339261662@qq.com</i><br /><searchLink fieldCode="AR" term="%22Zeng%2C+Zihao%22">Zeng, Zihao</searchLink><relatesTo>2</relatesTo><i> 627571028@qq.com</i>
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  Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Applied+Mathematics%22">IAENG International Journal of Applied Mathematics</searchLink>. Jul2026, Vol. 56 Issue 7, p2657-2666. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Structural+optimization%22">Structural optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Response+surfaces+%28Statistics%29%22">Response surfaces (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Latin+hypercube+sampling%22">Latin hypercube sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Hulls+%28Naval+architecture%29%22">Hulls (Naval architecture)</searchLink><br /><searchLink fieldCode="DE" term="%22Mechanical+buckling%22">Mechanical buckling</searchLink>
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  Label: Abstract
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  Data: To enhance the stability and safety of submersible pressure hull structures in deep-sea environments, this study first conducts a parametric analysis of an initial ring-stiffened cylindrical pressure hull design. The optimal Latin hypercube sampling method is employed to generate sample points and to evaluate the response of design variables to the optimization objectives. A high-fidelity fourth-order response surface model is then constructed, followed by the formulation of a multi-objective optimization model that considers structural mass, strength, and buckling stability as competing objectives. The NSGA-II genetic algorithm is subsequently applied to perform non-dominated sorting and crowding distance calculation. This yields four distinct Pareto-optimal schemes, each exhibiting varying degrees of improvement across the defined objectives. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 10
        StartPage: 2657
    Subjects:
      – SubjectFull: Structural optimization
        Type: general
      – SubjectFull: Multi-objective optimization
        Type: general
      – SubjectFull: Response surfaces (Statistics)
        Type: general
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Latin hypercube sampling
        Type: general
      – SubjectFull: Hulls (Naval architecture)
        Type: general
      – SubjectFull: Mechanical buckling
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      – TitleFull: Structural Optimization of Cylindrical Pressure Hulls via NSGA-II.
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            NameFull: Zhang, Ya
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            NameFull: Tao, Zhicong
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            NameFull: Wang, Hao
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            NameFull: Li, Huixin
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            NameFull: Zeng, Zihao
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            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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