Improved Methodologies for Maneuver Design of Aircraft Stability and Control Simulations

Jirasek, Adam; Jeans, Tiger L.; Martenson, Mathew; Cummings, Russell M.; Bergeron, Keith

doi:10.2514/6.2010-515

Cited by 16 publications

(14 citation statements)

References 36 publications

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“…The time domain models are based on the state space representation by matching time histories of measured data. Some examples of time domain ROMs include the unit sample response [15,57,49,18], Volterra theory [56,55,54,9], Radial Basis Functions (RBF) [29,19,7] and state-space modeling [20,32]. In this paper, the mathematical model of indicial functions, Radial Basis Functions, and state-space method are presented.…”

Section: Reduced-order Aerodynamic Modelsmentioning

confidence: 99%

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Challenges in the aerodynamics modeling of an oscillating and translating airfoil at large incidence angles

Ghoreyshi

Cummings

2013

Aerospace Science and Technology

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The challenges in the modeling of the unsteady lift of a two-dimensional NACA 0012 airfoil oscillating and translating at large incidence angles are investigated in this paper. Forced oscillation motions with two reduced frequency values of 0.1 and 1.0 were used. The CFD results show that a hysteresis loop was developed in the lift variation with angle of attack; shapes of the loops change significantly with reduced frequency value. A dynamic stall vortex was identified in the pitching and plunging motions with k = 0.1.This vortex delays the onset of flow separation over the upper surface to a higher incidence than would occur in steady conditions. The unsteady lift of the very fast motion is enhanced significantly due to the formation of a compression wave on the lower surface and an expansion wave on the upper surface. The results show clear limitations of unsteady aerodynamic theories for modeling motions at high incidences. Also, the CFD solution of indicial functions show a large oscillation at angles of attack beyond the stall angle, but the predictions of a model based on Radial Basis Function matches CFD values quite well.

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Section: Reduced-order Aerodynamic Modelsmentioning

confidence: 99%

“…The mesh consists of prisms and tetrahedra and was generated using SolidMesh 2D. Jirásek et al [29] performed the sensitivity study of the grid size and time step. The pitch axis and the moment reference point are set to 0.25c for all the results.…”

Section: Test Casementioning

confidence: 99%

Challenges in the aerodynamics modeling of an oscillating and translating airfoil at large incidence angles

Ghoreyshi

Cummings

2013

Aerospace Science and Technology

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“…These parameters account for timehistory effects and phase lag in the flow development. Equation (19) preserves the characteristics of the state-space model but no longer depends on system internal states [52]. Central to the generation of the reduced-order model is the computation of the function Φ.…”

Section: E Reduced-order Models Based On Surrogate-based Recurrencefmentioning

confidence: 99%

“…Examples of the frequency-domain ROMs are the indicial response method by Ballhaus and Goorjian [13] and Tobak et al [14,15] and a frequency-domain approach based on proper orthogonal decomposition (POD) by Hall et al [16]. Some examples of time-domain ROMs include the unit sample response by Gaitonde and Jones [17], Volterra theory by Silva and Bartels [18], radial basis functions (RBFs) [19], and state-space modeling [20]. These ROM techniques have been used extensively for flutter prediction, limit cycle oscillation, and gust-response modeling [21], but their application to S&C is still new.…”

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confidence: 99%

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Transonic Aerodynamic Load Modeling of X-31 Aircraft Pitching Motions

Ghoreyshi¹,

Cummings²,

Ronch³

et al. 2013

AIAA Journal

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The generation of reduced-order models for computing the unsteady and nonlinear aerodynamic loads on an aircraft from pitching motions in the transonic speed range is described. The models considered are based on Duhamel's superposition integral using indicial (step) response functions, Volterra theory using nonlinear kernels, radial basis functions, and a surrogate-based recurrence framework, both using time-history simulations of a training maneuver(s). Results are reported for the X-31 configuration with a sharp leading-edge cranked delta wing geometry, including canard/wing vortex interactions. The validity of the various models studied was assessed by comparison of the model outputs with time-accurate computational-fluid-dynamics simulations of new maneuvers. Overall, the reduced-order models were found to produce accurate results, although a nonlinear model based on indicial functions yielded the best accuracy among all models. This model, along with a time-dependent surrogate approach, helped to produce accurate predictions for a wide range of motions in the transonic speed range. = regression coefficients ε = kriging random process μ = air viscosity; kriging mean value ρ = density, kg∕m 3 σ 2 = covariance τ ij = viscous stress tensor components, Pa Φ i X = radial basis functions ω = circular frequency, rad∕s

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Computational approximation of nonlinear unsteady aerodynamics using an aerodynamic model hierarchy

Ghoreyshi

Jirasek

Cummings

2013

Aerospace Science and Technology

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, "Computational approximation of nonlinear unsteady aerodynamics using an aerodynamic model hierarchy" (2013 Modeling nonlinear unsteady aerodynamic effects in the simulation of modern fighter aircraft is still a very challenging task. A framework for approximating nonlinear unsteady aerodynamics with a Radial Basis Function neural network is provided. Training data were generated from a hierarchy of aerodynamic models. At the highest level, solutions of the discretized Reynolds-Averaged Navier-Stokes (RANS) equations provide the quantitative and qualitative solution of flow around aircraft, although the results are expensive in terms of computational resources. The Euler simulations are less expensive and provide qualitative data up to moderate angles of attack. The integration of these data is promising for generating accurate aerodynamic models at moderate computational cost. To illustrate the method, an airfoil undergoing pitching and plunging motion is considered. The primary and secondary aerodynamic model data are computed using RANS and Euler equations, respectively. A description for a mapping between the aerodynamic loads and the motion parameters based on the implicit function theorem is described. The mapping is then augmented by adding the secondary data to the input dataset. The selection of training data is then discussed. Once the network is trained, it can compute the unsteady aerodynamic loads from motion descriptions on the order of a few seconds. The framework is examined for different motions, and in all cases, the ROM predictions closely represent the actual aerodynamic responses. It is also demonstrated that the aerodynamic hierarchy aids in the rapid development of a reduced-order model.

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Improved Methodologies for Maneuver Design of Aircraft Stability and Control Simulations

Cited by 16 publications

References 36 publications

Challenges in the aerodynamics modeling of an oscillating and translating airfoil at large incidence angles

Challenges in the aerodynamics modeling of an oscillating and translating airfoil at large incidence angles

Transonic Aerodynamic Load Modeling of X-31 Aircraft Pitching Motions

Computational approximation of nonlinear unsteady aerodynamics using an aerodynamic model hierarchy

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