Turbulent boundary layer induced noise and vibration of a multi-panel walled acoustic enclosure
Bibliographic record
Abstract
Flow-induced noise in aircraft cabins can be predicted through analytical models or numerical methods.To date, analytical methods have been used for simple structures and cabins, where usually a single panel is vibrating due to the flow excitation, and coupled with an acoustic enclosure.The present work investigates the analytical prediction of turbulent boundary layer induced noise and vibration of a multi-panel system.The objective is to investigate the coupling between individual panels and the acoustic enclosure.Each panel is coupled with the acoustic enclosure, which consists of a large rectangular room, with five rigid walls and one flexible wall.The properties of the panels and acoustic enclosure represent a typical fuselage skin panel and a cabin section, respectively.It is shown that identical panels located at different positions have dissimilar contributions to the cabin interior noise, showing that the panel position is an important variable for the accurate prediction and suppression of cabin noise.Analytical predictions were obtained for both the space-averaged interior sound pressure level and local interior sound pressure level.The spaceaveraged sound pressure level is usually accepted to provide the necessary information for the noise prediction; however, in some real life applications, the local sound pressure may also be desirable. r é s u m éLe bruit à l'intérieur d 'es cabines d'es avions induite par écoulement externe peut être prédit par modèles analytiques ou méthodes numériques.À ce jour, les méthodes analytiques ont été utilisés pour structures et chambre simples, où, normalement, un seul panneau est considéré à vibrer en raison de l'écoulement externe, et couplé avec la chambre acoustique.Cet article étudie la prévision analytique des vibrations et du bruit dans un système avec plusieurs panneaux.L'objectif est d'examiner le couplage entre panneaux individuels et la chambre acoustique, en considérant de l'emplacement du panneau comme une variable.La cabine acoustique est une grande chambre rectangulaire et les panneaux rectangulaires sont considérés simplement appuyés.Les propriétés des matériaux et les dimensions des panneaux et de chambre acoustique sont représentatives d'un panneau de fuselage typique d'un avion et un compartiment de la cabine, respectivement.Il est conclu que panneaux similaires situés dans des positions différentes de la cabine ont contributions différentes du bruit intérieur, montrant que la position du panneau est une variable importante pour une prévision précise de bruit et de suppression de bruit dans la cabine.Ont été obtenu des prévisions analytiques des valeurs localisées du niveau de pression sonore à l'intérieur, et la moyenne de ces valeurs en l'espace.Le niveau moyen de pression acoustique à l'intérieur est habituellement utilisé pour obtenir information de la prévision du bruit; cependant, dans certaines situations et applications réelles, la valeur du niveau de pression acoustique d'un point précis dans l'espace peut être souhaitable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".