Vibration behavior of a microperforated plate within an acoustic nonlinear framework
Bibliographic record
Abstract
Microperforated plates (MPP) can add substantial damping in the low-frequency range. MPP are known to dissipate energy through thermo-viscous interactions between shearing adjacent fluid layers near the perforation solid walls. Under linear operating conditions, a previous work carried out by the authors showed that the added damping reaches a maximum at a characteristic frequency which solely depends on the perforation parameters. However, MPP is also suitable in environments subject to high levels of mechanical excitation and, consequently, high fluid velocity within the perforations. Two types of nonlinearities should then be considered: (1) an acoustic nonlinearity induced by high fluid velocity, and (2) a nonlinearity induced by large structural displacements. This work only explores the former. The acoustic nonlinearity is modelled by the Forchheimer resistivity correction, a function of the fluid-solid relative velocity in the perforations, introduced into the equations subsequently solved numerically. Experimental measurements using a laser vibrometer on a perforated cantilever beam validate the proposed model. Results show that, under high excitation levels and at the characteristic frequency, the maximum added damping can reach a maximum, depending on the MPP parameters, at a critical value of the relative fluid-solid velocity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".