Flight Test Maneuvers for Efficient Aerodynamic Modeling

Morelli, Eugene A.

doi:10.2514/1.c031699

Cited by 72 publications

(34 citation statements)

References 17 publications

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“…Prediction using global aerodynamic models identified from T-2 flight data explanatory variable subspace and therefore could be used in place of wind tunnel testing that requires extensive grids of test points to generate the aerodynamic database. The approach described here could be extended to more than the three control surfaces used in this demonstration 16 , further increasing the productivity and efficiency of the flight test maneuver and the global aerodynamic modeling process.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In past work [13][14][15][16][17] , inputs such as those shown in Figure 2 were applied at a selected flight condition. The pilot flew the aircraft to the reference flight condition, then activated an automated excitation system that added inputs like those shown in Figure 2 to the trim control deflections coming from the pilot and feedback control system.…”

Section: B Maneuver Design For Efficient Global Aerodynamic Modelingmentioning

confidence: 99%

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Efficient Global Aerodynamic Modeling from Flight Data

Morelli

2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: B Maneuver Design For Efficient Global Aerodynamic Modelingmentioning

confidence: 99%

Efficient Global Aerodynamic Modeling from Flight Data

Morelli

2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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“…Through a combination of excitation design and recursive frequency domain processing, real-time system identification techniques have been developed and validated on AirSTAR. 9,10,11 These techniques have been refined to provide an aerodynamic database using only a small amount of flight data and minimal perturbations from normal trimmed conditions. Therefore, these techniques can provide flight-dynamics models over extended envelopes, where test data is scarce.…”

Section: Research Historymentioning

confidence: 99%

Subscale Flight Testing for Aircraft Loss of Control: Accomplishments and Future Directions

Cox

Cunningham

Jordan

2012

AIAA Guidance, Navigation, and Control Conference

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Subscale flight-testing provides a means to validate both dynamic models and mitigation technologies in the high-risk flight conditions associated with aircraft loss of control. The Airborne Subscale Transport Aircraft Research (AirSTAR) facility was designed to be a flexible and efficient research facility to address this type of flight-testing. Over the last several years (2009-2011) it has been used to perform 58 research flights with an unmanned, remotelypiloted, dynamically-scaled airplane. This paper will present an overview of the facility and its architecture and summarize the experimental data collected. All flights to date have been conducted within visual range of a safety observer. Current plans for the facility include expanding the test volume to altitudes and distances well beyond visual range. The architecture and instrumentation changes associated with this upgrade will also be presented.

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“…7,10 Excitations are added just before software actuator limiters on control surface deflection angle and rate to maintain low correlation amidst pilot inputs and feedback control. A linear system under this excitation will yield the steady-state responses…”

Section: A Multi-sine Excitation Designmentioning

confidence: 99%

Real-Time Frequency Response Estimation Using Joined-Wing SensorCraft Aeroelastic Wind-Tunnel Data

Grauer

Heeg

Morelli

2012

AIAA Atmospheric Flight Mechanics Conference

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A new method is presented for estimating frequency responses and their uncertainties from wind-tunnel data in real time. The method uses orthogonal phase-optimized multisine excitation inputs and a recursive Fourier transform with a least-squares estimator. The method was first demonstrated with an F-16 nonlinear flight simulation and results showed that accurate short period frequency responses were obtained within 10 seconds. The method was then applied to wind-tunnel data from a previous aeroelastic test of the JoinedWing SensorCraft. Frequency responses describing bending strains from simultaneous control surface excitations were estimated in a time-efficient manner.

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Flight Test Maneuvers for Efficient Aerodynamic Modeling

Cited by 72 publications

References 17 publications

Efficient Global Aerodynamic Modeling from Flight Data

Efficient Global Aerodynamic Modeling from Flight Data

Subscale Flight Testing for Aircraft Loss of Control: Accomplishments and Future Directions

Real-Time Frequency Response Estimation Using Joined-Wing SensorCraft Aeroelastic Wind-Tunnel Data

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