Sound transmission paths through a statistical energy analysis model of mechanically linked aircraft double-walls
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sound transmission loss (TL) through mechanically linked aircraft double-walls is studied with a statistical energy analysis method. An overview of the method is given with details on acoustic and structural transfer path analysis. The studied structure is composed of a thick composite sandwich panel representative of a skin panel, lined with an acoustic insulation layer (glass wool), and structurally connected via vibration isolators to a thin composite sandwich lining panel representative of a trim panel. Two types of vibration isolators are considered: a soft and rigid mechanical link. Various experimental methods were used to assess the accuracy of this model. This study shows the robustness of the simple four-pole modeling of isolators, which depends mainly on the importance of correctly determining the experimental dynamic stiffness of typical aircraft vibration isolators. The prediction of the TL while acceptable was, however, found less satisfactory for the soft configuration. This is traced to the uncertainties on the used coupling loss factor. Finally, a transfer path analysis is performed to identify the contribution of each transmission path in the entire frequency range of interest. Results show that non-resonant airborne transmission dominates in low frequencies, the airborne radiation is significant in the critical frequency region of the panels, while the structure-borne radiation increases the noise transmitted in the mid- and high-frequency ranges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it