Improved Computation of Balancing Transformations for Aeroservoelastic Models via Time Scale Conversion

Hammerand, Daniel C.; Gariffo, James M.; Roughen, Kevin M.

doi:10.2514/1.51071

Cited by 2 publications

(1 citation statement)

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“…One such method, based on proper orthogonal decompositions, was developed by Amsallem,et al 20,21 and Lieu et al 22 Another method, based on Roger's RFA, was developed by the authors, in collaboration with Hammerand, Roughen, and Baker. [23][24][25][26] In this paper, the flutter boundary of an aeroelastic model of the ONERA M6 wing is investigated across a range of aerodynamic and structural parameters, using an extension of the ROM methodology from Refs. 23-26. In particular, the studies presented here examine techniques to rapidly estimate aeroelastic stability for multiple values of a given parameter such as air density or wing thickness based on linearized representations of data obtained from a small number of full-order nonlinear analyses.…”

Section: Introductionmentioning

confidence: 99%

Efficient Prediction of Transonic Flutter Boundaries with Linearized Aeroservoelastic Reduced-Order Models

Gariffo

Bendiksen

2013

54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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A computational aeroelastic model based on the ONERA M6 wing configuration is studied over a range of transonic flight conditions and structural stiffness parameters. A reduced-order modeling (ROM) approach is used, consisting of linear state-space models based on nonlinear CFD results. The structural component of the models is generated by converting a finite-element model to modal form, while the aerodynamic component is generated via Roger's Rational Function Approximation (RFA). It is shown that although the state-space models are linear, they are effective at predicting conditions where the full nonlinear model shows instabilities, including instabilities unique to the transonic regime such as high-altitude flutter and single-degree of freedom flutter. Nomenclature[A] State matrix of a state-space model [A 0 ] Constant term in Roger's Rational Function Approximation [A 1 ] Linear term in Roger's Rational Function Approximation [A 2 ] Quadratic term in Roger's Rational Function Approximation [A A ] Aerodynamic state matrix [a] Matrix of actuator delay constants [B l ] Curve fit term corresponding to aerodynamic lag term l in Roger's Rational Function Approximation [B 0 A ] Aerodynamic input matrix corresponding to displacement input [B 1 A ] Aerodynamic input matrix corresponding to velocity input [B 2 A ] Aerodynamic input matrix corresponding to acceleration input {B A } N l × 1 vector fully populated with values of 1.0 [C] Output matrix of a state-space model [C A ] Aerodynamic output matrix [C d ] Nodal damping matrix from structural model C d Modal damping matrix c Wing chord length [D] Feedthrough matrix of a state-space model [D 0 A ] Aerodynamic feedthrough matrix corresponding to displacement input [D 1 A ] Aerodynamic feedthrough matrix corresponding to velocity input [D 2 A ] Aerodynamic feedthrough matrix corresponding to acceleration input {d} Nodal displacement vector from structural model {F } Force vector from structural model {F } Modal force vector F (k) Generalized aerodynamic force as function of reduced frequency f (t) Generalized aerodynamic force as function of time f Aeroservoelastic modal frequency

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