Dynamic inlet distortion predictions using a combined CFD/synthesis method.

摘要

A new procedure is developed to predict dynamic inlet distortion using a combined CFD and distortion synthesis method. A prediction of the steady state total pressure pattern at the Aerodynamic Interface Plane (AIP) is first obtained from a steady state numerical solution of the Reynolds averaged Navier-Stokes equations employing a two-equation turbulence model. A corresponding inlet turbulence pattern is then computed from the CFD data via a correlation linking measured inlet turbulence to a formulation of several mean flow parameters. This correlation is initially derived using flight data obtained from the NASA High Alpha Research Vehicle (HARV) flight test program. The method is further developed, and the accuracy of the predictions assessed, using wind tunnel data from a 26% scale T-45 inlet model. A distortion synthesis process is then performed whereby instantaneous pressure patterns are statistically generated using the CFD predicted steady state total pressures and the correlated average turbulence data as input. The generated unsteady data is screened to obtain the single pattern producing the maximum value of AIP pressure distortion as defined by an index selected to characterize the engines surge margin sensitivity. The predicted dynamic distortions are shown to agree qualitatively with the measured data for all cases studied and quantitatively accurate in the absence of large inlet lip boundary layer separations.