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Communication Dans Un Congrès Année : 2022

Direct noise predictions of fan broadband noise using LES and analytical models

Résumé

In the present study, we analyze the broadband noise of an ultra high bypass ratio fan/OGV stage developed at Ecole Centrale de Lyon. Wall-modeled large eddy simulations (LES) of a periodic fan/OGV sector are performed at approach conditions on an unstructured grid that is well refined for direct noise propagation. Comparisons between wall-resolved and wallmodeled computations are performed using a 2.5D simplified configuration of the fan/OGV stage, and show a good agreement. This justifies the use of wall-modeled simulations for the full-span configuration. A good agreement is found between LES and RANS aerodynamic results. However, some differences can be found in the tip gap region and near the hub, where large coherent structures appear. Additionally, a small recirculation bubble can be observed from approximately 60% of the fan blade span in the LES. In this study, the broadband noise is directly computed from the fully-compressible LES solver and compared with predictions from available analytical models. The input data for the analytical models, such as mean and turbulent flow statistics, are obtained from the LES computation. A good agreement is found for the predicted sound power levels between direct LES noise predictions and the LES-informed analytical models. This confirms the capability of the LES numerical setup to directly predict far-field noise. However, some discrepancies can be observed at low frequencies. These might be attributed to the additional noise sources that are present in the LES, which are not considered by the analytical models.
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Dates et versions

hal-03697923 , version 1 (17-06-2022)

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Jean Al-Am, Vincent Clair, Alexis Giauque, Jérôme Boudet, Fernando Gea-Aguilera. Direct noise predictions of fan broadband noise using LES and analytical models. 28th AIAA/CEAS Aeroacoustics 2022 Conference, Jun 2022, Southampton, United Kingdom. ⟨10.2514/6.2022-2882⟩. ⟨hal-03697923⟩
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