Interpolation on manifolds of CFD-based fluid and finite element-based structural reduced-order models for on-line aeroelastic predictions

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Abstract/Contents

Abstract
The critical impact of aeroelastic phenomena on the design and performance of aircraft calls for their accurate numerical prediction. Until the advent of modern computational capabilities, methods based on the linear theory of aeroelasticity were used, leading to reasonable predictions, except in the transonic flight regime. This regime being critical for high-performance jets, expensive wind tunnel testing remains the only option, before flight testing, for flutter clearance of new aircraft. The simultaneous development of advance Computational Fluid Dynamics (CFD) methods and high performance numerical algorithms has then suggested that CFD-based methods could become an alternative tool. While CFD-based aeroelastic computations have accurately predicted the correct behavior of full aircraft in the subsonic, transonic and supersonic regimes, the associated high computational cost has prevented these methods to be integrated in routine analysis. This is even the case for flutter which can be treated as a linearized problem, and therefore is less extensive to solve than nonlinear problems. Reduced-Order Models (ROMs) have then seen a growing interest in the aeroelastic community because their lower dimensionality implies reduced computational costs. Unfortunately, routine analysis and flutter clearance involve parameter variations and most if not all ROMs lack robustness with respect to parameter changes. Therefore, performing computations with ROMs calls for reconstructing a new ROM every time a new configuration is considered. However, such a reconstruction can be a computationally intensive process since the high-fidelity model is involved. Together, these two issues underline the need for a new strategy for adapting pre-computed ROMs to new sets of physical or modeling parameters. In this dissertation a database of reduced-order information associated to fast interpolation-based techniques are considered. ROMs and their corresponding reduced-order bases are quantities that typically belong to nonlinear, matrix manifolds. As such, classical interpolation methods fail, as they are not able to enforce the constraints characterizing those manifolds. The first part of this thesis consists in first identifying the quantities of interest to be interpolated as well as their associated constraints and then designing a suitable interpolation method enforcing the constraints. Applications to the fast aeroelastic prediction of the behavior of two full aircraft configurations (F-16 Block 40 and F-18/A) are then presented. The contributions of this thesis also include a procedure for adapting structural ROMs to shape parameter variations. An approach based on a database of reduced-order fluid bases and reduced-order structural models coupled with this method of interpolation on a manifold is then shown to greatly reduce the computational cost for aeroelastic predictions of a full F-16 Block 40 aircraft while retaining good accuracy. The proposed method enables test operation calls for new, "last minute'' flight configurations and thus paves the way for on-line, routine usage of reduced-order modeling including during flight testing.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2010
Issuance monographic
Language English

Creators/Contributors

Associated with Amsallem, David
Associated with Stanford University, Department of Aeronautics and Astronautics
Primary advisor Farhat, Charbel
Thesis advisor Farhat, Charbel
Thesis advisor Lall, Sanjay
Thesis advisor Papanicolaou, George
Advisor Lall, Sanjay
Advisor Papanicolaou, George

Subjects

Genre Theses

Bibliographic information

Statement of responsibility David Amsallem.
Note Submitted to the Department of Aeronautics and Astronautics.
Thesis Thesis (Ph. D.)--Stanford University, 2010.
Location electronic resource

Access conditions

Copyright
© 2010 by David Amsallem
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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