Assessment of Critical Fuel Configurations Using Robust Flutter Analysis

Heinze, Sebastian

doi:10.2514/1.30500

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…Only aerodynamic uncertainty is treated in this study although, it is also possible to consider uncertainties in the structural model [15,16]. A standard panel-type aerodynamic model is used in this study; see Sec.…”

Section: Aerodynamic Uncertainty Modelingmentioning

confidence: 99%

Industrial Application of Robust Aeroelastic Analysis

Leijonhufvud¹,

Karlsson²

2011

Journal of Aircraft

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The recently developed -p method for robust aeroelastic analysis is applied to a case study concerning the aeroelastic analysis of a fighter aircraft equipped with a new wingtip missile. A process for using robust analysis for industrial applications is developed and discussed. The process combines robust analysis, flight flutter testing, and model validation in a way suitable for industrial purposes. Aerodynamic uncertainties in terms of pressure variations in the wingtip area are considered. First, a sensitivity analysis is performed to investigate how much effect uncertainties in different areas of the aerodynamic model have on the damping. The results from the sensitivity analysis are used to choose a suitable uncertainty model. Robust aeroelastic analysis is then performed, with the focus on possible damping variations at different flight conditions. Finally, a closely coupled procedure combining flight flutter testing, uncertainty model validation, and robust analysis is applied for successive expansion of the flight envelope and to show that the aircraft is free from aeroelastic instabilities.

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Section: Aerodynamic Uncertainty Modelingmentioning

confidence: 99%

Industrial Application of Robust Aeroelastic Analysis

Leijonhufvud¹,

Karlsson²

2011

Journal of Aircraft

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“…Basically, using for robust flutter analysis is a sophisticated search in the parameter space for the most critical perturbation. Unfortunately, the most critical perturbation as such is not a result of the upper-bound computation, but it can be estimated by other means [9,19]. In this work, the solver in MATLAB [20] was used for the analysis, using the default settings.…”

Section: Equivalent Feedback Formmentioning

confidence: 99%

“…The -k formulation also opened up new possibilities to model aerodynamic uncertainty, which is of primary importance in aeroelastic applications. Some additional developments in this direction can be found in [7][8][9][10].…”

mentioning

confidence: 99%

Robust Eigenvalue Analysis Using the Structured Singular Value: The µ-p Flutter Method

Borglund

2008

AIAA Journal

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This paper introduces a new technique for robust aeroelastic analysis that extends standard linear flutter analysis to take deterministic uncertainty and variation into account. The basic principle of the proposed -p method is to exploit structured-singular-value (or ) analysis to investigate if the system uncertainties can make the flutter determinant zero for a given flutter eigenvalue p. This makes it possible to compute regions of feasible eigenvalues in the complex plane as well as extreme eigenvalues that can be used to predict damping bounds and perform robust flutter analysis. The capability to predict damping bounds at subcritical flight conditions is a very attractive feature of the new method, as flight testing is rarely taken to the flutter point. The -p formulation also opens up new possibilities to bound the magnitude of the system uncertainties based on frequency and/or damping estimates from flight testing. In the final part of the paper, the -p framework is successfully applied to perform robust aeroelastic analysis of a low-speed wind-tunnel model. Nomenclature F= flutter matrix F u = upper linear fractional transformation g = damping K = stiffness matrix k = reduced frequency L = reference length M = mass matrix N = linear fractional transformation matrix P = system matrix p = eigenvalue Q = aerodynamic matrix V = airspeed w = input from uncertainty matrix z = output to uncertainty matrix = uncertainty matrix = uncertainty parameters = modal coordinates = structured singular value = modal force = air density = maximum singular value

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“…In the past few years, many scholars have done some research on the influence of wing fuel mass variations on the aeroelasticity. Heinze (Heinze, 2007) used μ-κ method to assess the influence of wing fuel variations on the flutter boundary in subsonic regime. It was shown that the variation of the structural mode shapes due to fuel mass variation play a significant role in flutter speed of the aircraft.…”

Section: Introductionmentioning

confidence: 99%

An efficient evaluation method for wing fuel mass variations effect on transonic aeroelasticity

Wang

Ronch

et al. 2022

AEAT

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Purpose This paper aims to develop an efficient evaluation method to more intuitively and effectively investigate the influence of the wing fuel mass variations because of fuel burn on transonic aeroelasticity. Design/methodology/approach The proposed efficient aeroelastic evaluation method is developed by extending the standard computational fluid dynamics (CFD)-based proper orthogonal decomposition (POD)/reduced order model (ROM). Findings The results of this paper show that the proposed aeroelastic efficient evaluation method can accurately and efficiently predict the aeroelastic response and flutter boundary when the wing fuel mass vary because of fuel burn. It also shows that the wing fuel mass variations have a significant effect on transonic aeroelasticity; the flutter speed increases as the wing fuel mass decreases. Without rebuilding an expensive, time-consuming CFD-based POD/ROM for each wing fuel mass variation, the computational cost of the proposed method is reduced obviously. It also shows that the computational efficiency improvement grows linearly with the number of model cases. Practical implications The paper presents a potentially powerful tool to more intuitively and effectively investigate the influence of the wing fuel mass variation on transonic aeroelasticity, and the results form a theoretical and methodological basis for further research. Originality/value The proposed evaluation method makes it a reality to apply the efficient standard CFD-based POD/ROM to investigate the influence of the wing fuel mass variation because of fuel burn on transonic aeroelasticity. The proposed efficient aeroelastic evaluation method, therefore, is ideally suited to deal with the investigation of the influence of wing fuel mass variations on transonic aeroelasticity and may have the potential to reduce the overall cost of aircraft design.

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Assessment of Critical Fuel Configurations Using Robust Flutter Analysis

Cited by 6 publications

References 15 publications

Industrial Application of Robust Aeroelastic Analysis

Industrial Application of Robust Aeroelastic Analysis

Robust Eigenvalue Analysis Using the Structured Singular Value: The µ-p Flutter Method

An efficient evaluation method for wing fuel mass variations effect on transonic aeroelasticity

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