Robustness of optimisation algorithms for transonic aerodynamic design

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dc.contributor.authorSánchez Moreno, Francisco
dc.contributor.authorMacManus, David G.
dc.contributor.authorTejero, Fernando
dc.contributor.authorMatesanz García, Jesús
dc.contributor.authorSheaf, Christopher T.
dc.date.accessioned2022-07-13T15:04:09Z
dc.date.available2022-07-13T15:04:09Z
dc.date.issued2022-07-01
dc.description.abstractIn design optimisation problems, it is essential to ensure the convergence to the optimal design space with the lowest variability possible. In this respect, the optimisation algorithm plays a key role as it drives the exploration of the design space. This paper presents a statistical assessment of two genetic algorithms (NSGA-II and IBEA) and a particle swarm optimiser (OMOPSO) for the transonic aerodynamic design of compact nacelles for future aero-engines. OMOPSO is the most suitable optimisation algorithm due to the lowest variability to find an optimised design with a reasonable convergence rate of the optimisation.en_UK
dc.identifier.citationSanchez-Moreno F, MacManus D, Tejero F, et al., (2022) Robustness of optimisation algorithms for transonic aerodynamic design. In: 9th European Conference for Aeronautics and Space Sciences (EUCASS-3AF 2022), 27 June - 1 July 2022, Lille, Franceen_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18161
dc.language.isoenen_UK
dc.publisherUnknownen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.titleRobustness of optimisation algorithms for transonic aerodynamic designen_UK
dc.typeConference paperen_UK

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