This paper summarizes participant results from AIAA's 3rd Propulsion Aerodynamics Workshop

What is it about?

This paper documents the Computational Fluid Dynamics (CFD) simulation results presented to the 3rd Propulsion Aerodynamics Workshop committee, and explores the effects of grid refinement, turbulence modelling, and topology for a challenging serpentine inlet test case. CFD results are compared against test data obtained from experiments performed at Georgia Tech.

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Why is it important?

Increasing demands on aircraft range and efficiency require engineers to understand the various mechanisms at work across the entire aerodynamic envelope, including the propulsion system. The desire for compact propulsion systems has led to inlets and diffusers of low length to diameter ratios, which often have flow turning to circumvent such internal features as cockpits, weapon bays, and/or landing gear. With flow turning in at least one plane, and often in two planes, undesirable secondary flows are generated and flow separation is common. Additionally, cross-sectional shape changes from the highlight of the inlet to the diffuser and finally to the engine face present opportunities for secondary flows and losses in total pressure. These adverse effects serve to reduce the available total pressure at the engine face which decreases engine performance. Even more problematic are the large variations (both radial and circumferential) in total pressure seen at the AIP, leading to various types of total pressure distortion. The prediction of separated flows, secondary flows, and dynamic unsteady content has been problematic in past studies in diffusers and ducts with flow turning. While not a new subject, there is a lack of comprehensive data on the subject. To help address the aforementioned issues, the Inlets, Nozzles, and Propulsion Systems Integration Technical Committee sponsored the 3rd Propulsion Aerodynamics Workshop (PAW) in July of 2016 in Salt Lake City, UT. Building on the successes of past PAW activities, the community continues to converge in terms of solver accuracy and consistency of model implementation while scatter in data and the number of "outliers" continues to reduce as the workshops evolve, due in part to community experience, increasing computational power allowing for higher fidelity models, and lessons learned from the workshops themselves.

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