Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation
Thermoelastic stresses induced in filament wound composite pressure vessels by temperature changes significantly influence the resulting load of the pressure vessel. This study presents the analytical approaches based on classical lamination theory and netting theory, which can be used for computing...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Philosophical Magazine Letters |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/09500839.2025.2476499 |
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| author | Dominik Vondráček Zdeněk Padovec Tomáš Mareš Nirupam Chakraborti |
| author_facet | Dominik Vondráček Zdeněk Padovec Tomáš Mareš Nirupam Chakraborti |
| author_sort | Dominik Vondráček |
| collection | DOAJ |
| description | Thermoelastic stresses induced in filament wound composite pressure vessels by temperature changes significantly influence the resulting load of the pressure vessel. This study presents the analytical approaches based on classical lamination theory and netting theory, which can be used for computing these thermoelastic stresses in the basic parts of the pressure vessel, such as the cylinder part, the end dome, and the junction area between them. Two material configurations were considered – glass-epoxy and carbon-epoxy. Concerning the knowledge of the thermoelastic stresses in analysed essential parts of the vessel, the Hoffman failure index analysis was performed. Using this failure index analysis, the critical places of the pressure vessel can be easily detected. Using data-driven evolutionary algorithms, the invariance of the pressure vessel geometry concerning the thermoelastic stresses was verified. Knowing the critical places of the pressure vessel may improve the designer’s decision during the development and design process. |
| format | Article |
| id | doaj-art-e480ce897a9a43119ed79884dd808c09 |
| institution | OA Journals |
| issn | 0950-0839 1362-3036 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Philosophical Magazine Letters |
| spelling | doaj-art-e480ce897a9a43119ed79884dd808c092025-08-20T02:29:59ZengTaylor & Francis GroupPhilosophical Magazine Letters0950-08391362-30362025-12-01105110.1080/09500839.2025.2476499Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisationDominik Vondráček0Zdeněk Padovec1Tomáš Mareš2Nirupam Chakraborti3Department of Mechanics, Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech RepublicDepartment of Mechanics, Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech RepublicDepartment of Mechanics, Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech RepublicDepartment of Mechanics, Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech RepublicThermoelastic stresses induced in filament wound composite pressure vessels by temperature changes significantly influence the resulting load of the pressure vessel. This study presents the analytical approaches based on classical lamination theory and netting theory, which can be used for computing these thermoelastic stresses in the basic parts of the pressure vessel, such as the cylinder part, the end dome, and the junction area between them. Two material configurations were considered – glass-epoxy and carbon-epoxy. Concerning the knowledge of the thermoelastic stresses in analysed essential parts of the vessel, the Hoffman failure index analysis was performed. Using this failure index analysis, the critical places of the pressure vessel can be easily detected. Using data-driven evolutionary algorithms, the invariance of the pressure vessel geometry concerning the thermoelastic stresses was verified. Knowing the critical places of the pressure vessel may improve the designer’s decision during the development and design process.https://www.tandfonline.com/doi/10.1080/09500839.2025.2476499Composite pressure vesselfilament windingthermoelastic stressesdata-driven evolutionary algorithmsdeep learning |
| spellingShingle | Dominik Vondráček Zdeněk Padovec Tomáš Mareš Nirupam Chakraborti Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation Philosophical Magazine Letters Composite pressure vessel filament winding thermoelastic stresses data-driven evolutionary algorithms deep learning |
| title | Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation |
| title_full | Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation |
| title_fullStr | Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation |
| title_full_unstemmed | Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation |
| title_short | Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation |
| title_sort | analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many objective optimisation |
| topic | Composite pressure vessel filament winding thermoelastic stresses data-driven evolutionary algorithms deep learning |
| url | https://www.tandfonline.com/doi/10.1080/09500839.2025.2476499 |
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