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dc.title | Aerodynamic efficiency optimization of Clark Y aerofoil using SU2 application | en |
dc.contributor.author | Vogeltanz, Tomáš | |
dc.relation.ispartof | MENDEL 2016 | |
dc.identifier.issn | 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-802145365-4 | |
dc.date.issued | 2016 | |
dc.citation.spage | 79 | |
dc.citation.epage | 86 | |
dc.event.title | 22nd International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Chaos, Bayesian Methods, Intelligent Image Processing, Bio-Inspired Robotics, MENDEL 2016 | |
dc.event.location | Brno | |
utb.event.state-en | Czech Republic | |
utb.event.state-cs | Česká republika | |
dc.event.sdate | 2016-06-08 | |
dc.event.edate | 2016-06-10 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Brno University of Technology | |
dc.subject | Aerofoil optimization | en |
dc.subject | Clark Y | en |
dc.subject | Computational Fluid Dynamics | en |
dc.subject | Hicks-Henne function | en |
dc.subject | Inviscid flow | en |
dc.subject | Low-speed flow | en |
dc.subject | Open-source | en |
dc.subject | SU2 | en |
dc.description.abstract | In this paper, the aerodynamic efficiency optimizations of the Clark Y aerofoil by using the SU2 software suite are performed. We used a low-speed inviscid flow with the Mach number of approximately 0.0441 (15 m/s) for the optimization. To determine whether we found completely optimized aerofoils, we had to analyse the optimized aerofoils at surrounding angles of attack after the optimization. Moreover, we extended the analysis to obtain information whether the aerofoils can also be effectively used at higher velocities (up to 30 m/s). We executed and analysed five optimizations with the different number of design variables: 8, 18, 38, 78, and 158. Firstly, the aerodynamics of aerofoil is briefly described and the most important parameters are explained. In the following section, the SU2 software used for the optimizations is outlined and the optimization method is introduced. Finally, the results of the efficiency optimizations are presented, compared, and analysed. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1007119 | |
utb.identifier.obdid | 43874928 | |
utb.identifier.scopus | 2-s2.0-85014903076 | |
utb.source | d-scopus | |
dc.date.accessioned | 2017-08-01T08:27:14Z | |
dc.date.available | 2017-08-01T08:27:14Z | |
utb.contributor.internalauthor | Vogeltanz, Tomáš | |
utb.fulltext.affiliation | Tomáš Vogeltanz Tomas Bata University in Zlín Department of Informatics and Artificial Intelligence nám. T.G. Masaryka 5555, 760 01 Zlín Czech Republic vogeltanz@fai.utb.cz | |
utb.fulltext.dates | - | |
utb.fulltext.sponsorship | This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme project No. LO1303 (MSMT-7778/2014) and also by the Internal Grant Agency of Tomas Bata University under the project No. IGA/CebiaTech/2016/002. |