$$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection
Abstract Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The $$CO_2$$ C O 2 footprint of a solar-powered High Altitude Long...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-39221-3 |
| _version_ | 1797769536115572736 |
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| author | Edouard Duriez Víctor Manuel Guadaño Martín Joseph Morlier |
| author_facet | Edouard Duriez Víctor Manuel Guadaño Martín Joseph Morlier |
| author_sort | Edouard Duriez |
| collection | DOAJ |
| description | Abstract Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The $$CO_2$$ C O 2 footprint of a solar-powered High Altitude Long Endurance (HALE) drone is optimized here, where the structural materials used is one of the design variables. Optimization is performed using a modified version of OpenAeroStruct, a framework based on OpenMDAO. Our EcoHale framework is validated on a classical HALE testcase in the MDO community (FBhale) constructed using high-fidelity codes compared to our low-fidelity approach. The originality of our work is to include two specific disciplines (energy and environment) to adapt to a new problem of $$CO_2$$ C O 2 minimization. The choice of eco-materials is performed in the global MDO loop from a choice of discrete materials . This is achieved through a variable relaxation, enabling the use of continuous optimization algorithms inspired from multimaterial topology optimization. Our results show that, in our specific case of electric drone, the optimal material in terms of $$CO_2$$ C O 2 footprint is also the optimal material in terms of weight. It opens the door to new researches on digital microarchitectured materials that will decrease the $$CO_2$$ C O 2 footprint of the drone. |
| first_indexed | 2024-03-12T21:09:31Z |
| format | Article |
| id | doaj.art-eb711fd291e9416a81e9cf01c39f3ae7 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-12T21:09:31Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-eb711fd291e9416a81e9cf01c39f3ae72023-07-30T11:16:10ZengNature PortfolioScientific Reports2045-23222023-07-0113111410.1038/s41598-023-39221-3$$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selectionEdouard Duriez0Víctor Manuel Guadaño Martín1Joseph Morlier2ICA, Université de Toulouse, ISAE-SUPAERO, MINES ALBI, UPS, INSA, CNRSUniversité de Toulouse, ISAE-SUPAEROICA, Université de Toulouse, ISAE-SUPAERO, MINES ALBI, UPS, INSA, CNRSAbstract Multidisciplinary Design Optimization (MDO) enables one to reach a better solution than by optimizing each discipline independently. In particular, the optimal structure of a drone varies depending on the selected material. The $$CO_2$$ C O 2 footprint of a solar-powered High Altitude Long Endurance (HALE) drone is optimized here, where the structural materials used is one of the design variables. Optimization is performed using a modified version of OpenAeroStruct, a framework based on OpenMDAO. Our EcoHale framework is validated on a classical HALE testcase in the MDO community (FBhale) constructed using high-fidelity codes compared to our low-fidelity approach. The originality of our work is to include two specific disciplines (energy and environment) to adapt to a new problem of $$CO_2$$ C O 2 minimization. The choice of eco-materials is performed in the global MDO loop from a choice of discrete materials . This is achieved through a variable relaxation, enabling the use of continuous optimization algorithms inspired from multimaterial topology optimization. Our results show that, in our specific case of electric drone, the optimal material in terms of $$CO_2$$ C O 2 footprint is also the optimal material in terms of weight. It opens the door to new researches on digital microarchitectured materials that will decrease the $$CO_2$$ C O 2 footprint of the drone.https://doi.org/10.1038/s41598-023-39221-3 |
| spellingShingle | Edouard Duriez Víctor Manuel Guadaño Martín Joseph Morlier $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection Scientific Reports |
| title | $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection |
| title_full | $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection |
| title_fullStr | $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection |
| title_full_unstemmed | $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection |
| title_short | $$CO_2$$ C O 2 footprint minimization of solar-powered HALE using MDO and eco-material selection |
| title_sort | co 2 c o 2 footprint minimization of solar powered hale using mdo and eco material selection |
| url | https://doi.org/10.1038/s41598-023-39221-3 |
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