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Ground Test Data Validation Using a Subscale F/A-22 Engine Inlet Empirical Model

[+] Author Affiliations
Randall L. Bickford

Expert Microsystems, Inc., Orangevale, CA

Donald J. Malloy

Aerospace Testing Alliance, Arnold AFB, TN

Jeffrey F. Monaco

Barron Associates, Inc., Charlottesville, VA

David S. Kidman

Propulsion Integration Branch, Edwards AFB, CA

Paper No. GT2006-90165, pp. 85-99; 15 pages
  • ASME Turbo Expo 2006: Power for Land, Sea, and Air
  • Volume 2: Aircraft Engine; Ceramics; Coal, Biomass and Alternative Fuels; Controls, Diagnostics and Instrumentation; Environmental and Regulatory Affairs
  • Barcelona, Spain, May 8–11, 2006
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-4237-1 | eISBN: 0-7918-3774-2
  • Copyright © 2006 by ASME


The US Air Force’s two main aeropropulsion test centers, Arnold Engineering Development Center and the Air Force Flight Test Center, are developing a common suite of modeling and simulation tools employing advanced predictive modeling technologies. These modeling and simulation tools incorporate real-time data validation, system identification, parameter estimation, model calibration, and automated model updating as new test results or operational data become available. The expected benefit is improved efficiency and accuracy for online diagnostic monitoring of Air Force assets. This paper describes the integrated approach to real-time data validation. Implementation of a software package to enable efficient model handoff between test groups and centers and extension of the capability to aeropropulsion models is discussed. An F/A-22 inlet model is used to demonstrate the approach. Compact polynomial function models of the distortion and recovery flow descriptors and 40-probe pressure values are derived from quasi-steady and instantaneous subscale wind tunnel data. The total-pressure inlet distortion and recovery models are integrated in a real-time equipment health monitoring system designed to support test operations, and preliminary results are given. A companion paper describes the integrated approach to system identification, parameter estimation, and model updating.

Copyright © 2006 by ASME



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