Using reciprocity principles and sensitivity functions for the vibroacoustic response of panels under random excitations
Bibliographic record
Abstract
The vibroacoustic characterization of panels submitted to random pressure fields is of great interest for the industry. The test means associated with those excitations (i.e., wind tunnel, reverberant room) are expensive and can hardly be controlled. An alternative method to experimentally characterize the behavior of a panel under random pressure fields is therefore proposed. The mathematical formulation of the problem allows describing the vibroacoustic behavior of a panel as a function of the cross spectral density function of the considered excitation and so-called “sensitivity functions.” These functions can be estimated experimentally using reciprocity principle, which can either be applied for characterizing the structural response by exciting the panel with a normal force at the point of interest or for characterizing the acoustic response (radiated pressure, acoustic intensity) by exciting the panel with a monopole and a dipole source. For validation purposes, the method is applied numerically and experimentally for the case of a diffuse acoustic field. Based on indicators such as the vibratory response and the transmission loss factor, the method is finally confronted to measurements in coupled anechoic-reverberant rooms facility following standards.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".