Aissa, M, Chahine, C, Arsenyeva, A et al. (25 more authors) (2017) Multidisciplinary Design Optimisation Research Contributions from the AMEDEO Marie Curie Initial Training Network. In: Proceedings of the 11th ASMO-UK/ISSMO/NOED2016 International Conference on Numerical Optimisation Methods for Engineering Design. 11th ASMO-UK/ISSMO/NOED2016 International Conference on Numerical Optimisation Methods for Engineering Design, 18-20 Jul 2016, Munich, Germany. ASMO-UK , pp. 1-32. ISBN 9780853163480
Abstract
This paper reviews the key research activities and results produced during the AMEDEO (Aerospace Multidisciplinarity-Enabling Design Optimisation) Marie Curie Initial Training Network (ITN). AMEDEO brought together optimisation researchers and practitioners from European universities, research organisations, multinationals and SMEs to develop innovative Multidisciplinary Design Optimisation (MDO) methods for the design of energy-efficient aircraft. A range of new results are presented in the areas of: 1) efficient High Performance Computing techniques for MDO, 2) efficient metamodel-based robust MDO frameworks, 3) the application of advanced MDO methods to aircraft engine design and 4) novel applications of MDO to the design of composite aeronautical structures. The future challenges that need to be overcome to embed MDO methods more effectively within commercial design cycles in the aerospace industry are also briefly discussed.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Aug 2017 10:27 |
Last Modified: | 30 Aug 2017 12:27 |
Published Version: | http://www.asmo-uk.com/11th_asmo_uk/papers/asmo-uk... |
Status: | Published |
Publisher: | ASMO-UK |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:120594 |