Use of non-intrusive flow diagnostics for aero-engine inlet flow distortion measurements in an industrial wind-tunnel

Date published

2025-01-06

Free to read from

2025-04-11

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AIAA

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Conference paper

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Citation

Piovesan T, Zachos PK, MacManus D, et al., (2025) Use of non-intrusive flow diagnostics for aero-engine inlet flow distortion measurements in an industrial wind-tunnel. AIAA SCITECH 2025 Forum, 6-10 January 2025, Orlando, FL, USA. Paper number AIAA

Abstract

In crosswind conditions, aero-engine intakes experience unsteady flow distortions at the fan face, typically caused by the ingestion of ground vortices and flow separation. These distortions can negatively impact both intake performance and the compatibility of the downstream propulsion system. Understanding the aerodynamics of these flows is crucial for developing next-generation aircrafts with propulsion systems integrated more closely with the airframe. Optical measurement techniques provide detailed datasets in both space and time to support this understanding, but several challenges limit their widespread use in propulsion integration testing. This study demonstrates a novel application of non-intrusive flow diagnostics in an industrial setting for propulsion integration testing. Optical measurements were conducted within an aspirated intake configuration and, later, within a fully coupled fan-intake propulsion system representative of a modern high-bypass aero-engine. Several innovative solutions were developed to improve the integration of optical systems into industrial settings and enhance data acquisition efficiency. The analysis of the results yielded significant contributions about the unsteady interactions within civil intakes at crosswind and high incidence conditions, which are expected to have a notable impact on the development of future, closely integrated propulsion systems architectures able to meet the specified NetZero targets.

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Github

Keywords

4012 Fluid Mechanics and Thermal Engineering, 4007 Control Engineering, Mechatronics and Robotics, 40 Engineering

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Attribution-NonCommercial 4.0 International

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The work presented herein was conducted under the NIFTI project which received funding from the Clean Sky 2 Joint Undertaking (JU) under Grant Agreement No 866521