Reduced order modelling for static and dynamic aeroelastic predictions with multidisciplinary approach

Melike Nikbay*, Pinar Acar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We implement reduced order modelling techniques for aeroelastic predictions of the HIRENASD and S4T wings in order to represent CFD based high-fidelity solutions efficiently. Model reduction techniques such as non-intrusive Polynomial Chaos Expansion and Proper Orthogonal Decomposition are applied to both static and dynamic aeroelastic cases. The high-fidelity solutions are obtained by fluid structure interaction analysis using a 3D Euler unsteady aerodynamic solver and structural modal solution from a finite element solver. The model order reduction strategy is based on a multidisciplinary approach since both structural and aerodynamic input parameters are employed. The model order reduction is performed not only to represent the high-fidelity computational analyses when small variations of input parameters are considered but also to characterize the flutter responses of the S4T wing in a broad range of input values over the entire flight regime for Mach numbers between 0.60 and 1.20. The efficient aeroelastic analyses performed using the developed reduced order models agreed well with the high-fidelity computational analyses.

Original languageEnglish
Article numberA005
Pages (from-to)455-469
Number of pages15
JournalCEAS Aeronautical Journal
Volume6
Issue number3
DOIs
Publication statusPublished - Sept 2015

Bibliographical note

Publisher Copyright:
© Deutsches Zentrum für Luft- und Raumfahrt e.V. 2015.

Funding

The authors would like to thank to Istanbul Technical University Scientific Research Projects Center (BAP) for the research fund under the project titled “Computational Aeroelasticity Investigations for NATO-RTO-AVT-203 and Aeroelastic Prediction Workshop”. The authors would like to thank to Dr. Zhichao Zhang for his excellent technical support and ZONA Technology Inc. for the assistance to provide ZEUS licenses. Moreoever, the first author would like to thank to team members of NATO-STO-AVT-203 “Joined Exercise on Aeroelastic Prediction” and NATO-STO-AVT-191 “Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design” Task Groups, especially to Dr. Jennifer Heeg and Dr. Atlee Cunningham for their valuable collaborations. The last but not the least, the first author would like to thank to NATO Scientific and Technology Organization Applied Vehicle Technology (AVT) Panel Executive Secretariat and AVT Panel National Coordination Office in Turkish Ministry of National Defense R&D Center for their support.

FundersFunder number
Istanbul Technical University Scientific Research Projects Center
British Association for PsychopharmacologyNATO-RTO-AVT-203

    Keywords

    • Aeroelasticity
    • Fluid-structure interaction
    • HIRENASD
    • Multidisciplinary
    • Polynomial chaos expansion
    • Proper orthogonal decomposition
    • Reduced order modelling
    • S4T

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