Active noise control simulation of tonal turbofan noise in aero engines
Notice bibliographique
Résumé
Active Noise Control (ANC) of the tonal noise of a turbofan engine is introduced using active stator vanes and rings of loudspeakers as control actuators. It involves a unique coupling of two original analytical and numerical models for the primary and secondary sources respectively, and two different control strategies that attempt to independently control the propagative acoustic modes upstream and downstream for the first time. The primary noise source is based on the analytical model recently developed by De Laborderie that deals with rectilinear cascade responses due to wake-interaction applied in a strip theory framework. Good agreement with both numerical and experimental data is found on the blade pressure jumps. The secondary noise sources induced by the piezo-actuators embedded in the stator blade are shown to behave as compact dipoles that are radiating in an annular duct. The corresponding radiation can be obtained either numerically or analytically. Here the propagation is computed numerically using COMSOL. The noise control strategy can either Singular Values Decomposition (SVD) or Generalized Singular Values Decomposition (GSVD) without any knowledge on the physical form of the acoustic field. Simulation results are shown to achieve some significant tonal noise reduction and it is demonstrated that the GSVD is a great avenue to separate inlet and outlet radiation. Introduction Tonal noise from rotor/stator interaction in aircraft engines is predominant during landing and take-off phases of civil aircraft. Active Noise Control (ANC) is one of the solutions developed since the early 1990s to reduce tonal turbofan noise. Currently, most of published results rely on experimental data1,2, 3, 4, 5 but some analytical and numerical models were also developed.6,7, 8, 9 Sound Pressure Level (SPL) reductions from 3 to 20 dB at the Blade Passing Frequency (BPF) were obtained, most of them by using modal decomposition with feedforward control for low radial mode orders. Yet these configurations were too constrained in terms of weight and energy consumption to complete industrial implementation. Also, the available processing power was unsufficient at that time to reach the requested sampling rate for active control implementation. The next decade brought new advances in digital signal processing, especially the Field Programmable Gate Array (FPGA) hardware10 and new control algorithms like the Principal value Orthogonal Decomposition (POD). In 2006, ANC with aeroacoustic control sources provided a SPL reduction of up to 20.5 dB at the BPF.11 The latest advances were pursued in 2009 by the German Aerospace Center (DLR).12 An Ultra High Bypass Ratio (UHBR) turbofan was tested with a rotating rake for the modal decomposition, microphone rings as error sensors and loudspeaker rings as secondary sources, all among the stator vane cascade. Active control was implemented with a feedforward algorithm and POD for up to 32 dB in Sound Power Level (PWL) reduction for the azimuthal mode m = 6. ∗Research associate, GAUS, Mechanical Engineering Department, yann.pasco@usherbrooke.ca †Post-doctorate fellow, Mechanical Engineering Department, thomas.guedeney@usherbrooke.ca ‡MSc student, GAUS, Mechanical Engineering Department, arnaud.leung-tack@usherbrooke.ca §Professor, GAUS, Mechanical Engineering Department ¶Professor, Mechanical Engineering Department, AIAA Lifetime Member
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».