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Frequency and mass optimization for an axially functionally graded GNP-reinforced conical shell with variable thickness.

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Title: Frequency and mass optimization for an axially functionally graded GNP-reinforced conical shell with variable thickness.
Authors: Zhao, Zhigang1 (AUTHOR), Gao, Jun2,3,4 (AUTHOR) policegaojun@163.com, Li, Feng1 (AUTHOR), Afshari, H.5 (AUTHOR)
Source: Applied Mathematics & Mechanics. Apr2026, Vol. 47 Issue 4, p859-882. 24p.
Subjects: Conical shells, Particle swarm optimization, Graphene, Shear (Mechanics), Functionally gradient materials, Mathematical optimization, Structural optimization, Thickness measurement
Abstract: This paper studies the optimization of mass and frequency for a polymeric conical shell reinforced with graphene nanoplatelets (GNPs). The volume fraction of the GNPs and the thickness of the shell change along the meridional direction. The modeling of the conical shell is conducted by the first-order shear deformation theory (FSDT), and the governing equations and boundary conditions are derived by Hamilton's principle. A semi-analytical solution is presented, including an analytical solution carried out in the circumferential direction and a numerical solution conducted in the meridional direction utilizing the differential quadrature method (DQM). To maximize the fundamental frequency and minimize the mass, the particle swarm optimization (PSO) is utilized, taking into account some constraints on the minimum thickness of the shell and the maximum volume fraction of the GNPs. The optimization process involves finding the optimal profiles of thickness and volume fraction of the GNPs. [ABSTRACT FROM AUTHOR]
Copyright of Applied Mathematics & Mechanics is the property of Springer Nature 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.)
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DbLabel: Engineering Source
An: 192688646
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  Data: Frequency and mass optimization for an axially functionally graded GNP-reinforced conical shell with variable thickness.
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  Data: <searchLink fieldCode="JN" term="%22Applied+Mathematics+%26+Mechanics%22">Applied Mathematics & Mechanics</searchLink>. Apr2026, Vol. 47 Issue 4, p859-882. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Conical+shells%22">Conical shells</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Graphene%22">Graphene</searchLink><br /><searchLink fieldCode="DE" term="%22Shear+%28Mechanics%29%22">Shear (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Functionally+gradient+materials%22">Functionally gradient materials</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+optimization%22">Structural optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Thickness+measurement%22">Thickness measurement</searchLink>
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  Data: This paper studies the optimization of mass and frequency for a polymeric conical shell reinforced with graphene nanoplatelets (GNPs). The volume fraction of the GNPs and the thickness of the shell change along the meridional direction. The modeling of the conical shell is conducted by the first-order shear deformation theory (FSDT), and the governing equations and boundary conditions are derived by Hamilton's principle. A semi-analytical solution is presented, including an analytical solution carried out in the circumferential direction and a numerical solution conducted in the meridional direction utilizing the differential quadrature method (DQM). To maximize the fundamental frequency and minimize the mass, the particle swarm optimization (PSO) is utilized, taking into account some constraints on the minimum thickness of the shell and the maximum volume fraction of the GNPs. The optimization process involves finding the optimal profiles of thickness and volume fraction of the GNPs. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Applied Mathematics & Mechanics is the property of Springer Nature 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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        Value: 10.1007/s10483-026-3373-7
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 859
    Subjects:
      – SubjectFull: Conical shells
        Type: general
      – SubjectFull: Particle swarm optimization
        Type: general
      – SubjectFull: Graphene
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      – SubjectFull: Shear (Mechanics)
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      – SubjectFull: Functionally gradient materials
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      – SubjectFull: Mathematical optimization
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      – SubjectFull: Structural optimization
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      – SubjectFull: Thickness measurement
        Type: general
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      – TitleFull: Frequency and mass optimization for an axially functionally graded GNP-reinforced conical shell with variable thickness.
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            NameFull: Zhao, Zhigang
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            NameFull: Gao, Jun
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            NameFull: Li, Feng
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              Text: Apr2026
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              Y: 2026
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