Total pressure distortion reconstruction methods from velocimetry data within an aero-engine intake at crosswind

Date published

2025-03-24

Free to read from

2025-05-23

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European Turbomachinery Society

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Conference paper

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Citation

Piovesan T, Zachos P, MacManus D. (2025) Total pressure distortion reconstruction methods from velocimetry data within an aero-engine intake at crosswind. 16th European Turbomachinery Conference (ETC16), 24-28 March 2025, Hannover, Germany

Abstract

The integration of Very High Bypass Ratio (VHBR) turbofan engines with short intakes may present challenges due to increased total pressure distortion, particularly under crosswind conditions. Current industrial practices rely on a limited number of intrusive pressure sensors arranged on rakes at the Aerodynamic Interface Plane (AIP), to characterise this total pressure distortion. However, non-intrusive measurement techniques provide a more effective way to capture the complex, unsteady flow fields within the intake, offering higher spatial resolution compared to conventional methods. In this study, velocity data obtained from Stereoscopic Particle Image Velocimetry (S-PIV) during wind tunnel tests of a short intake configuration were employed to reconstruct the instantaneous total pressure fields at the AIP within the intake. Two reconstruction methods were used: Direct Spatial Integration (DSI) of the momentum equation and the Poisson Pressure Equation (PPE). These methods were first applied to numerical data from RANS simulations. The results of the reconstruction of the total pressure field based on the S-PIV data were compared against rake measurements. The methods enabled a more comprehensive assessment of total pressure distortion, offering improvements over conventional sensor-based ap-proaches in identifying and characterising total pressure non-uniformities within an intake.

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Github

Keywords

Pressure-from-velocity reconstruction, short intake, crosswind, Stereoscopic Particle Image Velocimetry

DOI

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Attribution-NonCommercial-NoDerivatives 4.0 International

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This work was conducted under the NIFTI project which received funding from the Clean Sky 2 Joint Undertaking (JU) under Grant Agreement No 864911