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.

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