Variable-Fidelity and Reduced-Order Models for Aero Data for Loads Predictions

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Variable-Fidelity and Reduced-Order Models for Aero Data for Loads Predictions

Görtz, Stefan / Zimmermann, Ralf / Han, Zhong-Hua

This paper summarizes recent progress in developing metamodels for efficiently predicting the aerodynamic loads acting on industrial aircraft configurations. We introduce a physics-based approach to reduced-order modeling based on proper orthogonal decomposition of snapshots of the full-order CFD model, and a mathematical approach to variable-fidelity modeling that aims at combining many low-fidelity CFD results with as few high-fidelity CFD results as possible using bridge functions and variants of Kriging and Cokriging. In both cases, the goal is to arrive at a model that can be used as an efficient surrogate to the original high-fidelity or full-order CFD model but with significantly less evaluation time and storage requirements. Both approaches are demonstrated on industrial aircraft configurations at subsonic and transonic flow conditions.

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Document information

Title :

Variable-Fidelity and Reduced-Order Models for Aero Data for Loads Predictions

Additional title:

Notes Numerical Fluid Mech.

Contributors:

Kroll, Norbert (editor) / Radespiel, Rolf (editor) / Burg, Jan Willem (editor) / Sørensen, Kaare (editor) / Görtz, Stefan (author) / Zimmermann, Ralf (author) / Han, Zhong-Hua (author)

Published in:

Computational Flight Testing ; Chapter : 8 ; 99-112

Notes on Numerical Fluid Mechanics and Multidisciplinary Design ; 123

Publication date :

2013-01-01

Size :

14 pages

ISBN :

978-3-642-38877-4 , 978-3-642-38876-7

ISSN :

1860-0824 , 1612-2909

DOI :