Assessment of a frequency-domain linearized Euler solver for turbofan aft radiation predictions with comparison measurements

Özyörük, Yusuf and Tester, Brian J. (2010) Assessment of a frequency-domain linearized Euler solver for turbofan aft radiation predictions with comparison measurements. [in special issue: IUTAM Symposium on Computational Aero-Acoustics for Aircraft Noise Prediction] Procedia Engineering, 6, 153-162. (doi:10.1016/j.proeng.2010.09.017).

Abstract

This paper presents a frequency-domain computational aeroacoustics tool for predicting aft noise radiation through turbofan ducts and jets and its application to two realistic engine exhaust configurations which have been experimentally tested. The tool is based on the discretised axisymmetric form of the linearised Euler equations in conjunction with perfectly matched layer equations at the inlet and far-field boundaries using high-order finite differences. The resultant linear system of equations is inverted by the state-of-the-art parallel sparse solver MUMPS. The far-field prediction is carried out by integrating Kirchhoff’s formula in frequency domain. The code has already been verified extensively for idealized semi-infinite duct cases with comparisons to available analytical solutions with very good agreement. Therefore, we concentrate in this paper on numerical solutions to the experimental cases tested in the EC FP6 Project TURNEX (TUrbomachinery noise Radiated through the engine EXhaust) to assess and partially validate the present solver further. Comparisons of the computed results with the measured data reveal that the solver predicts the general noise radiation patterns and sound levels reasonably well, so long as the target in-duct azimuthal mode remains dominant as it radiates to the far-field. The agreement strongly suggests that, at least for the range of mean flows and acoustic conditions considered, the physical aeroacoustic radiation processes are fully captured through the frequency-domain solutions to the linearised Euler equations.

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