Method for experimental determination of flutter speed by parameter identification

Nissim, E.; Gilyard, Glenn B.

doi:10.2514/6.1989-1324

Cited by 36 publications

(23 citation statements)

References 5 publications

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“…As mentioned above, there are two general categories of methods to use flight flutter test data to predict the onset of aeroelastic instability. The way discussed hereafter is to identify the whole aeroelastic system by computing the equations of motion, using the method of Nissim and Gilyard [6], rather than attempting to extrapolate to the instability point from a curve fit of a chosen stability criterion such as the modal damping and the variation with the dynamic pressure.…”

Section: Adapted Methods Of Nissim and Gilyardmentioning

confidence: 99%

“…Following the ideas presented in [21], a system identification technique, referred to as the Nissim and Gilyard method, was devised in [6]. Adapted to the dimensionless notation used in the present work, the forced aeroelastic system is written as,…”

Section: Original Methods Of Nissim and Gilyardmentioning

confidence: 99%

“…indirect methods) aim to identify the equations of motion of the whole system (including matrices to describe the aerodynamic coupling) to predict the stability of the aircraft with varying flight speed. A prominent example is the Nissim and Gilyard method [6]. With the Nissim and Gilyard method the aeroelastic equations of motion are recast to allow forced excitation, and then, the system is excited with some known input signal (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Updating Computational Aeroelastic Models using Flight Flutter Test Data

Timme¹,

Badcock²

2011

International Journal of Aerospace and Lightweight Structures (

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A method is presented to identify a correction for the system matrices of a computational aeroelastic model based on information from flight test data. The correction matrices are identified using the method of Nissim and Gilyard adapted in this work to exploit the predictive capabilities of numerical aeroelastic tools while correcting for missing physics and systematic modelling errors. The simplified aerodynamics in the original Nissim and Gilyard method are discarded using computational fluid dynamics to evaluate the aerodynamic influence in the fluid/structure coupled system.

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Section: Adapted Methods Of Nissim and Gilyardmentioning

confidence: 99%

Section: Original Methods Of Nissim and Gilyardmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Updating Computational Aeroelastic Models using Flight Flutter Test Data

Timme¹,

Badcock²

2011

International Journal of Aerospace and Lightweight Structures (

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“…It has been clearly indicated that mathematical model including aerodynamic models must be verified using flight test data. in some relevant documents including GJB1395A-2009 [16] and CCAR-60 [17]. Furthermore, in the process of digital simulation, only a few feature points are selected to represent the aerodynamic parameters of the whole trajectory.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Data-Driven Modeling Method for Missiles

Guo

Han

2019

Symmetry

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This paper proposes a novel hybrid data-driven modeling method for missiles. Based on actual flight test data, the missile hybrid model is established by combining neural networks and the mechanism modeling method, considering the uncertainties and nonlinear factors in missiles. This method can avoid the problems in missile mechanism modeling and traditional data-driven modeling, and can also provide a solution for nonlinear dynamic system modeling problems in offline usage scenarios. Finally, the feasibility of the proposed method and the credibility of the established model are verified by simulation experiments and statistical analysis.

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“…The problem can only be partly solved by considering the fact that the linear part of N i is made up of a structural and an aerodynamic term. Aerodynamic stiffness terms depend on the square of the free-stream velocity [9,10]. Hence…”

Section: A More Complex Applicationmentioning

confidence: 99%

A method for identification of non-linear multi-degree-of-freedom systems

Dimitriadis

Cooper

1998

Proceedings of the Institution of Mechanical Engineers, Part G:

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System identification methods for non-linear aeroelastic systems could find uses in many aeroelastic applications such as validating finite element models and tracking the stability of aircraft during flight flutter testing. The effectiveness of existing non-linear system identification techniques is limited by various factors such as the complexity of the system under investigation and the type of non-linearities present. In this work, a new approach is introduced which can identify multi-degree-of-freedom systems featuring any type of non-linear function, including discontinuous functions. The method is shown to yield accurate identification of three mathematical models of aeroelastic systems containing a wide range of structural non-linearities.

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Method for experimental determination of flutter speed by parameter identification

Cited by 36 publications

References 5 publications

Updating Computational Aeroelastic Models using Flight Flutter Test Data

Updating Computational Aeroelastic Models using Flight Flutter Test Data

A Novel Hybrid Data-Driven Modeling Method for Missiles

A method for identification of non-linear multi-degree-of-freedom systems

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