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Mixed Fidelity Aerodynamic and Aero-Structural Optimization for Wings
KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0002-3859-9480
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
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2018 (English)In: 2018 International Conference on High Performance Computing & Simulation, 2018, p. 476-483Conference paper, Published paper (Refereed)
Abstract [en]

Automatic multidisciplinary design optimization is one of the challenges that are faced in the processes involved in designing efficient wings for aircraft. In this paper we present mixed fidelity aerodynamic and aero-structural optimization methods for designing wings. A novel shape design methodology has been developed - it is based on a mix of the automatic aerodynamic optimization for a reference aircraft model, and the aero-structural optimization for an uninhabited air vehicle (UAV) with a high aspect ratio wing. This paper is a significant step towards making it possible to perform all the core processes for aerodynamic and aero-structural optimization that require special skills in a fully automatic manner - this covers all the processes from creating the mesh for the wing simulation to executing the high-fidelity computational fluid dynamics (CFD) analysis code. Our results confirm that the simulation tools can make it possible for a far broader range of engineering researchers and developers to design aircraft in much simpler and more efficient ways. This is a vital step in the evolution of wing design processes as it means that the extremely expensive laboratory experiments that were traditionally used when designing the wings can now be replaced with more cost effective high performance computing (HPC) simulation that utilize accurate numerical methods.

Place, publisher, year, edition, pages
2018. p. 476-483
Keywords [en]
Multidisciplinary design optimization (MDO); Computational fluid dynamics (CFD); High performance computing
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-232360DOI: 10.1109/HPCS.2018.00081ISI: 000450677700064Scopus ID: 2-s2.0-85057381095ISBN: 978-1-5386-7877-0 (print)OAI: oai:DiVA.org:kth-232360DiVA, id: diva2:1234013
Conference
Conference: HPC and Modeling & Simulation for the 21st Century, At Orléans, France
Funder
Swedish e‐Science Research Center
Note

QC 20180808

Available from: 2018-07-20 Created: 2018-07-20 Last updated: 2018-12-10Bibliographically approved

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Zhang, MengmengGong, JingBarth, MichaelaAxner, Lilit
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CiteExportLink to record
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Citation style
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Output format
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