Abstract
A benchmark dedicated to RANS-informed analytical methods for the prediction of turbofan rotor–stator interaction broadband noise was organised within the framework of the European project TurboNoiseBB. The second part of this benchmark focuses on the impact of the acoustic models. Twelve different approaches implemented in seven different acoustic solvers are compared. Some of the methods resort to the acoustic analogy, while some use a direct approach bypassing the calculation of a source term. Due to differing application objectives, the studied methods vary in terms of complexity to represent the turbulence, to calculate the acoustic response of the stator and to model the boundary and flow conditions for the generation and propagation of the acoustic waves. This diversity of approaches constitutes the unique quality of this work. The overall agreement of the predicted sound power spectra is satisfactory. While the comparison between the models show significant deviations at low frequency, the power levels vary within an interval of ±3 dB at mid and high frequencies. The trends predicted by increasing the rotor speed are similar for almost all models. However, most predicted levels are some decibels lower than the experimental results. This comparison is not completely fair—particularly at low frequency—because of the presence of noise sources in the experimental results, which were not considered in the simulations.
Highlights
Research and development activities regarding the design of turbomachinery components of commercial aero-engines call for reliable and efficient methods to predict the noise emission
It should be noted that differences between simulations and experimental values should be interpreted very carefully as the acoustic models are sensitive to the RANS input and the way the integral length scale is calculated, as shown in Part I [1]
The authors argue that accounting for the swirl may not be essential to achieve a reasonable prediction of rotor–stator interaction (RSI) broadband noise levels. (This statement does not hold for the prediction of RSI tones since they can be composed of only a few propagative modes.) This finding conflicts with the results presented by Moreau [5] about the extension of Posson’s model to sheared swirling flow
Summary
Research and development activities regarding the design of turbomachinery components of commercial aero-engines call for reliable and efficient methods to predict the noise emission. Hybrid RANS-informed analytical methods can help to reach that objective. RANS simulations are powerful methods, which are standardly applied in the field of engineering. A dedicated post-processing of the RANS results can be applied to reconstruct the input needed by analytical models of fan noise. If the method works, an acoustic prediction could be achieved as a by-product of a RANS simulation. Two main questions arise regarding that approach—(i) Is RANS able to properly predict the input for the acoustic models, in particular the crucial turbulence statistics needed for broadband noise prediction? (ii) Are analytical models, which tend to strongly simplify reality, sensitive enough to capture the effects of the sough-after design modifications Two main questions arise regarding that approach—(i) Is RANS able to properly predict the input for the acoustic models, in particular the crucial turbulence statistics needed for broadband noise prediction? (ii) Are analytical models, which tend to strongly simplify reality, sensitive enough to capture the effects of the sough-after design modifications
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