Physics-Based Rapid Aeroelastic Model Updating In Support Of Aircraft Flight Testing

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,999.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
FA9302-08-M-0004
Award Id:
86797
Agency Tracking Number:
F073-142-0527
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1500 Bull Lea Road, Suite 203, Lexington, KY, 40511
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
790637867
Principal Investigator:
PatrickHu
Scientist
(859) 699-0441
patrick.g.hu@advanceddynamics-usa.com
Business Contact:
PatrickHu
President
(859) 699-0441
patrick.g.hu@advanceddynamics-usa.com
Research Institute:
n/a
Abstract
The objective of the proposed research aims to develop Reduced Order Models (ROMs) (i.e. POD, HB, combined POD and HB) based upon flight data to better predict the aircraft aeroelastic response at next flight condition, e.g. higher Mach number. By incorporating flight test data and using the highest fidelity computational models in reduced order form we will obtain computational solutions that are the most accurate possible with the current state of the art and do so sufficiently rapidly predict the behavior at the next flight condition in an aeroelastic flight test. Many of the methods that have been developed over the years for simpler aeroelastic models that use, for example, doublet lattice aerodynamics can be adopted for this purpose. However we also propose to explore new approaches appropriate to high fidelity computational models in Phase I with a down selection to the best methods in Phase II. We will use the available wind tunnel flutter data for the AGARD 445.6 wing for our assessment in Phase I. However, we will also explore methods that would require more experimental data than is available for the AGARD wing. For the AGARD wing, the data available are principally the flutter boundary per se and the flutter frequency. If we also had data for preflutter transfer functions, for example, that would allow a more extensive incorporation of experimental data in modifying and enhancing the computational model for flight test prediction.

* information listed above is at the time of submission.

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