The direct approach of modeling the flow between all blade passages for each blade row in the compressor is too computationally intensive for practical design and analysis investigations with inlet distortion. Therefore a new simulation tool called the Turbine Engine Analysis Compressor Code (TEACC) has been developed. TEACC solves the compressible, time-dependent, 3D Euler equations modified to include turbomachinery source terms which represent the effect of the blades. The source terms are calculated for each blade row by the application of a streamline curvature code. TEACC was validated against experimental data from the transonic NASA rotor, Rotor 1B, for a clean inlet and for an inlet distortion produced by a 90-deg, one-per-revolution distortion screen. TEACC revealed that strong swirl produced by the rotor caused the compressor to increase in loading in the direction of rotor rotation through the distorted region and decrease in loading circumferentially away from the distorted region.

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Two primary aircraft propulsion subsystems are the inlet and the engine. Traditionally these subsystems have been designed, analyzed, and tested as isolated systems. The interaction between the subsystems is modeled primarily through evaluating inlet distortion in an inlet test and then simulating this distortion in engine tests via screens or similar devices. Recently, it has been recognized that significant improvements in both performance and operability can be realized when both the inlet and the engine are designed with full knowledge of the other. In this paper, a computational tool called Turbine Engine Analysis Compressor Code (TEACC) is used to evaluate the effect of inlet distortion on a three-stage military fan. This three-stage military fan is further connected to an F-16 inlet and forebody operating at an angle of attack and sideslip to demonstrate the effect of inlet distortion generated by flight maneuvers. The computational approach of simulating an integrated inlet-engine system is expected to provide additional insight over evaluating the components separately.