A clustered and surrogate-based MDA use case for MDO scenarios in AGILE project

dc.contributor.author Lefebre, T.
dc.contributor.author Bartoli, N.
dc.contributor.author Dubreuil, S.
dc.contributor.author Panzeri, M.
dc.contributor.author Lombardi, R.
dc.contributor.author Lammen, W.F.
dc.contributor.author Mengmeng, Z.
dc.contributor.author Gent, I. van
dc.contributor.author Ciampa, P.D.
dc.date.accessioned 2020-05-18T09:44:14Z
dc.date.available 2020-05-18T09:44:14Z
dc.date.issued 2018
dc.description The research presented in this paper has been performed in the framework of the AGILE project (Aircraft 3rd Generation MDO for Innovative Collaboration of Heterogeneous Teams of Experts) and has received funding from the European Union Horizon 2020 Programme (H2020-MG-2014-2015) under grant agreement no 636202. The authors are grateful to the partners of the AGILE consortium for their contribution and feedback. en_US
dc.description.abstract In this paper methodological investigations regarding an innovative Multidisciplinary Design and Optimization (MDO) approach for conceptual aircraft design are presented. These research activities are part of the ongoing EU-funded research project AGILE. The next generation of aircraft MDO processes is developed in AGILE, which targets significant reductions in aircraft development cost and time to market, leading to cheaper and greener aircraft solutions. The paper introduces the AGILE project structure and recalls the achievements of the first year of activities where a reference distributed MDO system has been formulated, deployed and applied to the design and optimization of a reference conventional aircraft configuration. Then, investigations conducted in the second year are presented, all aiming at making the complex optimization workflows easier to handle, characterized by a high degree of discipline interdependencies, multi-level processes and multi-partner collaborative engineering activities. The paper focuses on an innovative approach in which knowledge-based engineering and collaborative engineering techniques are used to handle a complex aircraft design workflow. Surrogate models replacing clusters of analysis disciplines have been developed and applied to make workflow execution more efficient. The paper details the different steps of the developed approach to set up and operate this test case, involving a team of aircraft design and surrogate modelling specialists, and taking advantage of the AGILE MDO framework. To validate the approach, different executable workflows were generated automatically and used to efficiently compare different MDO formulations. The use of surrogate models for clusters of design competences have been proved to be efficient approach not only to decrease the computational time but also to benchmark different MDO formulations on a complex optimization problem. en_US
dc.identifier.citation 19th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Atlanta, Georgia en_US
dc.identifier.uri http://hdl.handle.net/10921/1540
dc.identifier.uri https://doi.org/10.2514/6.2018-3252
dc.language.iso en en_US
dc.publisher AIAA en_US
dc.relation info:eu-repo/grantAgreement/EC/H2020/636202
dc.relation.ispartofseries AIAA;2018-3252
dc.rights info:eu-repo/semantics/openAccess
dc.subject.other Aeronautics
dc.subject.other Mathematical and computer sciences
dc.title A clustered and surrogate-based MDA use case for MDO scenarios in AGILE project en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
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