Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability
The computer aided internal optimisation (CAIO) method produces an optimised fibre layout for parts made from fibre-reinforced plastics (FRP), starting from an initial shell geometry and a given load case. Its main principle is iterative reduction of shear stresses by aligning fibre main axes with p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2020-01-01
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| Series: | Design Science |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S2053470120000013/type/journal_article |
| _version_ | 1811156421497061376 |
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| author | Harald Voelkl Michael Franz Daniel Klein Sandro Wartzack |
| author_facet | Harald Voelkl Michael Franz Daniel Klein Sandro Wartzack |
| author_sort | Harald Voelkl |
| collection | DOAJ |
| description | The computer aided internal optimisation (CAIO) method produces an optimised fibre layout for parts made from fibre-reinforced plastics (FRP), starting from an initial shell geometry and a given load case. Its main principle is iterative reduction of shear stresses by aligning fibre main axes with principal normal stress trajectories. Previous contributions, ranging from CAIO’s introduction over testing to extensions towards multi-layer FRP laminates, highlighted its lightweight design potential. For its application to laminate design approaches, alterations have been proposed; however, questions remain open. These questions include which convergence criteria to use, how to handle ambiguous principle normal stress trajectories, influence of using multi-layer CAIO optimisation instead of the initial single-layer CAIO and how dire consequences of slightly deviating fibre orientations from the optimised trajectories are. These challenges are discussed in depth and guidelines are given. This paper is an enhanced version of a distinguished contribution at the first symposium ‘Lightweight Design in Product Development’, Zurich (June 14–15, 2018). |
| first_indexed | 2024-04-10T04:51:17Z |
| format | Article |
| id | doaj.art-35a7c6090d2447e4a2a37531d12fbf73 |
| institution | Directory Open Access Journal |
| issn | 2053-4701 |
| language | English |
| last_indexed | 2024-04-10T04:51:17Z |
| publishDate | 2020-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Design Science |
| spelling | doaj.art-35a7c6090d2447e4a2a37531d12fbf732023-03-09T12:32:01ZengCambridge University PressDesign Science2053-47012020-01-01610.1017/dsj.2020.1Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicabilityHarald Voelkl0https://orcid.org/0000-0002-1681-4936Michael Franz1Daniel Klein2Sandro Wartzack3https://orcid.org/0000-0002-0244-5033Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Engineering Design, Martensstrasse 9, 91058Erlangen, GermanyFriedrich-Alexander-University Erlangen-Nuremberg (FAU), Engineering Design, Martensstrasse 9, 91058Erlangen, GermanyFriedrich-Alexander-University Erlangen-Nuremberg (FAU), Engineering Design, Martensstrasse 9, 91058Erlangen, GermanyFriedrich-Alexander-University Erlangen-Nuremberg (FAU), Engineering Design, Martensstrasse 9, 91058Erlangen, GermanyThe computer aided internal optimisation (CAIO) method produces an optimised fibre layout for parts made from fibre-reinforced plastics (FRP), starting from an initial shell geometry and a given load case. Its main principle is iterative reduction of shear stresses by aligning fibre main axes with principal normal stress trajectories. Previous contributions, ranging from CAIO’s introduction over testing to extensions towards multi-layer FRP laminates, highlighted its lightweight design potential. For its application to laminate design approaches, alterations have been proposed; however, questions remain open. These questions include which convergence criteria to use, how to handle ambiguous principle normal stress trajectories, influence of using multi-layer CAIO optimisation instead of the initial single-layer CAIO and how dire consequences of slightly deviating fibre orientations from the optimised trajectories are. These challenges are discussed in depth and guidelines are given. This paper is an enhanced version of a distinguished contribution at the first symposium ‘Lightweight Design in Product Development’, Zurich (June 14–15, 2018).https://www.cambridge.org/core/product/identifier/S2053470120000013/type/journal_articlelightweight designfibre trajectory optimisationCAIOfibre-reinforced plastics |
| spellingShingle | Harald Voelkl Michael Franz Daniel Klein Sandro Wartzack Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability Design Science lightweight design fibre trajectory optimisation CAIO fibre-reinforced plastics |
| title | Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability |
| title_full | Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability |
| title_fullStr | Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability |
| title_full_unstemmed | Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability |
| title_short | Computer Aided Internal Optimisation (CAIO) method for fibre trajectory optimisation: A deep dive to enhance applicability |
| title_sort | computer aided internal optimisation caio method for fibre trajectory optimisation a deep dive to enhance applicability |
| topic | lightweight design fibre trajectory optimisation CAIO fibre-reinforced plastics |
| url | https://www.cambridge.org/core/product/identifier/S2053470120000013/type/journal_article |
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