Fully Coupled Fluid-Structure Algorithms for Aeroelasticity and Forced Vibration Induced Flutter

Leyland, Pénélope; Carstens, V.; Blom, F. J.; Tefy, Tiana

doi:10.1080/12506559.2000.10511484

Cited by 15 publications

(12 citation statements)

References 13 publications

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“…In Eq. (23), C N is a constant depending only on N [·] and the input statistics. 5 Separability in the sense of Nuttall means that the conditional expectation of u satisfies…”

Section: Correlation Methodsmentioning

confidence: 99%

“…40 Thus, at a given M ∞ , a full-order flutter simulation consists in increasing V , effectively the feedback gain, until oscillation appears in the solution. 21,23,25 However, this is computationally onerous. Since the structural dynamics are linear, a faster, system-theoretic method consists in obtaining a reduced-order linear model of the aerodynamic input-output system, and analyzing the resulting closed-loop eigenvalues as V varies.…”

Section: Modeling Of Flutter Dynamicsmentioning

confidence: 98%

“…Numerous works have dealt with flutter modeling, thus we shall give a brief description here. For a detailed exposé see, for example, Leyland et al 23 The structural dynamics can be written in modal equations of motion, of the following normalized form:…”

Section: Modeling Of Flutter Dynamicsmentioning

confidence: 99%

See 2 more Smart Citations

Flutter-Boundary Prediction Using System Identification-Based Reduced-Order Aeroelasticity Analysis

Lai¹,

Lum²

2012

53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

2
0
1
0

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The paper is concerned with the prediction of flutter boundary using computational aeroelastic techniques and system identification-based reduced-order aeroelasticity analysis. The method consists in constructing a continuous time state-space model of the closed-loop aeroelastic system using numerical simulation results, and followed by performing eigenvalue analysis of the resulting state-space model to determine the flutter boundary. The work presented here is developed based upon our previous work. 20, 26 In the present paper, we consider CFD data for the training of ROM and nonlinear flutter dynamics represented by a Hammerstein model comprising a cubic static nonlinearity followed by a matrix ARMA linear block, and develop the correlation least-squares method of identification. Prediction of the flutter boundary of the AGARD 445.6 wing by eigenvalue analysis yields results that are very close to experimentally obtained flutter parameters, and are an improvement over method based on only linear models.

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“…In Eq. (23), C N is a constant depending only on N [·] and the input statistics. 5 Separability in the sense of Nuttall means that the conditional expectation of u satisfies…”

Section: Correlation Methodsmentioning
confidence: 99%

Section: Modeling Of Flutter Dynamicsmentioning
confidence: 98%

See 1 more Smart Citation
Flutter-Boundary Prediction Using System Identification-Based Reduced-Order Aeroelasticity Analysis
Lai¹,
Lum²
2012
53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
2
0
1
0
View full text Add to dashboard Cite
The paper is concerned with the prediction of flutter boundary using computational aeroelastic techniques and system identification-based reduced-order aeroelasticity analysis. The method consists in constructing a continuous time state-space model of the closed-loop aeroelastic system using numerical simulation results, and followed by performing eigenvalue analysis of the resulting state-space model to determine the flutter boundary. The work presented here is developed based upon our previous work. 20, 26 In the present paper, we consider CFD data for the training of ROM and nonlinear flutter dynamics represented by a Hammerstein model comprising a cubic static nonlinearity followed by a matrix ARMA linear block, and develop the correlation least-squares method of identification. Prediction of the flutter boundary of the AGARD 445.6 wing by eigenvalue analysis yields results that are very close to experimentally obtained flutter parameters, and are an improvement over method based on only linear models.
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“…It is "nonintrusive", i.e., allows for a "blackbox" implementation of the physics components which can be done with existing ("legacy") codes. This operational expediency comes at a cost of reduced accuracy and stability when the physics components involved are "loosely coupled", leading to desynchronization of the state variables in the different components by one time step or a fraction of a time step [6]. Iterative coupling techniques can be used to achieve a tight coupling, which eliminates this time shift [7,8,6].…”

Section: Introductionmentioning
confidence: 99%

Conservative tightly-coupled simulations of stochastic multiscale systems
Taverniers
¹
,
Pigarov
²
,
Tartakovsky
³

2016
Journal of Computational Physics
4
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6
0
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Multiphysics problems often involve components whose macroscopic dynamics is driven by microscopic random fluctuations. The fidelity of simulations of such systems depends on their ability to propagate these random fluctuations throughout a computational domain, including subdomains represented by deterministic solvers. When the constituent processes take place in nonoverlapping subdomains, system behavior can be modeled via a domain-decomposition approach that couples separate components at the interfaces between these subdomains. Its coupling algorithm has to maintain a stable and efficient numerical time integration even at high noise strengths. We propose a conservative domaindecomposition algorithm in which tight coupling is achieved by employing either Picard's or Newton's iterative method. Coupled diffusion equations, one of which has a Gaussian white-noise source term, provide a computational testbed for analysis of these two coupling strategies. Fully-converged ("implicit") coupling with Newton's method typically outperforms its Picard counterpart, especially at high noise levels. This is because the number of Newton iterations scales linearly with the amplitude of the Gaussian noise, while the number of Picard iterations can scale superlinearly. At large time intervals between two subsequent inter-solver communications, the solution error for single-iteration ("explicit") Picard's coupling can be several orders of magnitude higher than that for implicit coupling. Increasing the explicit coupling's communication frequency reduces this difference, but the resulting increase in computational cost can make it less efficient than implicit coupling at similar levels of solution error, depending on the communication frequency of the latter and the noise strength. This trend carries over

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“…Energy conservation in ALE schemes 339 and strongly coupled (3), which is also called monolithic approach (see for example (Leyland et al, 2000)). Case (1) has often proven to be too expensive in terms of CPU time.…”

Section: Introductionmentioning
confidence: 99%

Total energy conservation in ALE schemes for compressible flows
Dervieux
¹
,
Farhat
²
,
Koobus
³

et al. 2010
European Journal of Computational Mechanics
5
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0
0
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The numerical prediction of interaction phenomena between a compressible flow model with a moving domain and other physical models requires that the work performed on the fluid is properly translated into total fluid energy variation. We present a numerical model relying on an Arbitrary Lagrangian-Eulerian (ALE) unstructured vertex-centered finite volume that satisfies this condition together with the Geometric Conservation Law. We apply this numerical scheme to the solution of a 3D fluid-structure interaction problem. The results are contrasted with those obtained by the energy non-conservative counterpart.RÉSUMÉ. La prédiction numérique de l'interaction entre un fluide dans un domaine mobile et un autre modèle nécessite que le travail appliqué à sa frontière soit traduit en une variation appropriée de son énergie interne. On présente un modèle numérique reposant sur une formulation Arbitraire Lagrange Euler (ALE) en volumes finis non structurés et centrés sommet satisfaisant cette propriété ainsi que la Loi de Conservation Géométrique. Le schéma est appliqué à un problème d'interaction fluide-structure 3D. Les résultats sont mis en contraste avec ceux obtenus par un schéma analogue non conservatif pour l'énergie totale.

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Fully Coupled Fluid-Structure Algorithms for Aeroelasticity and Forced Vibration Induced Flutter

Cited by 15 publications

References 13 publications

Flutter-Boundary Prediction Using System Identification-Based Reduced-Order Aeroelasticity Analysis

Flutter-Boundary Prediction Using System Identification-Based Reduced-Order Aeroelasticity Analysis

Conservative tightly-coupled simulations of stochastic multiscale systems

Total energy conservation in ALE schemes for compressible flows

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