Wind turbines play a major role in the European Green Deal for clean energy transition. Noise is a critical aspect among open technological issues, as it determines the possibility of onshore installations near inhabited places and the possible detrimental effects on wildlife when offshore. This paper assesses the accuracy of different approaches to predicting the sound pressure level (SPL) of a wind turbine. The 2.75 MW Neg Micon NM80 horizontal axis wind turbine (HWAT) was simulated in OpenFOAM, modeling the turbine with the actuator line method (ALM) implemented in the turbinesFoam library. Two different inflow conditions were considered: a stationary inflow with a typical atmospheric boundary layer profile and a time-dependent inflow derived from a precursor channel with fully turbulent conditions. The surrogate model for noise prediction used for this work is based on the synthetic/surrogate acoustics models (SAMs) of Amiet and Brooks-Pope-Marcolini (BPM). This approach allows for blade motion modeling and the prediction of the SPL of the URANS postprocessing results. The SPL spectrum obtained was then compared to the results from the other aeroacoustic solvers of IEA Task 39 participants, showing the best performance in the fully turbulent case. The results demonstrate that coupling between the ALM and surrogate acoustics provides more accurate results than the blade element momentum (BEM) approach.

Surrogate modeling of the aeroacoustics of an NM80 wind turbine / De Girolamo, Filippo; Tieghi, Lorenzo; Delibra, Giovanni; Francesco Barnabei, Valerio; Corsini, Alessandro. - In: INTERNATIONAL JOURNAL OF TURBOMACHINERY, PROPULSION AND POWER. - ISSN 2504-186X. - 8:4(2023), pp. 1-14. (Intervento presentato al convegno 15th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics 2023, ETC 2023 tenutosi a Budapest; Hungary nel 24-28/04/2023) [10.3390/ijtpp8040043].

Surrogate modeling of the aeroacoustics of an NM80 wind turbine

Lorenzo Tieghi;
2023-01-01

Abstract

Wind turbines play a major role in the European Green Deal for clean energy transition. Noise is a critical aspect among open technological issues, as it determines the possibility of onshore installations near inhabited places and the possible detrimental effects on wildlife when offshore. This paper assesses the accuracy of different approaches to predicting the sound pressure level (SPL) of a wind turbine. The 2.75 MW Neg Micon NM80 horizontal axis wind turbine (HWAT) was simulated in OpenFOAM, modeling the turbine with the actuator line method (ALM) implemented in the turbinesFoam library. Two different inflow conditions were considered: a stationary inflow with a typical atmospheric boundary layer profile and a time-dependent inflow derived from a precursor channel with fully turbulent conditions. The surrogate model for noise prediction used for this work is based on the synthetic/surrogate acoustics models (SAMs) of Amiet and Brooks-Pope-Marcolini (BPM). This approach allows for blade motion modeling and the prediction of the SPL of the URANS postprocessing results. The SPL spectrum obtained was then compared to the results from the other aeroacoustic solvers of IEA Task 39 participants, showing the best performance in the fully turbulent case. The results demonstrate that coupling between the ALM and surrogate acoustics provides more accurate results than the blade element momentum (BEM) approach.
2023
International Journal of Turbomachinery, Propulsion and Power
Budapest, Hungary
MDPI
De Girolamo, Filippo; Tieghi, Lorenzo; Delibra, Giovanni; Francesco Barnabei, Valerio; Corsini, Alessandro
Surrogate modeling of the aeroacoustics of an NM80 wind turbine / De Girolamo, Filippo; Tieghi, Lorenzo; Delibra, Giovanni; Francesco Barnabei, Valerio; Corsini, Alessandro. - In: INTERNATIONAL JOURNAL OF TURBOMACHINERY, PROPULSION AND POWER. - ISSN 2504-186X. - 8:4(2023), pp. 1-14. (Intervento presentato al convegno 15th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics 2023, ETC 2023 tenutosi a Budapest; Hungary nel 24-28/04/2023) [10.3390/ijtpp8040043].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/439829
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