Finite element modeling of metamaterial made of acoustic black hole profiles for achieving broadband sound absorption.
Bibliographic record
Abstract
To achieve broadband sound absorption, acoustic metamaterial composed of periodically arranged thin annular cavities, separated by rings and connected through a main central pore is studied using finite element method. The geometry of the main pore is varied by applying different decreasing hole profile functions. Each annular cavity has a thickness of 1 mm, and the radius of the rings decreases progressively from the inlet, following linear, exponential, quadratic and sinusoidal decay functions. Considering up to 40 annular cavities, each main pore profile results in a broad frequency band of sound absorption coefficient. The exponential pore profile exhibits five absorption peaks below 1200 Hz and an average absorption coefficient of about 0.9 above 2000 Hz. In contrast, the other pore profiles achieve an average sound absorption coefficient of about 0.98 above 1500 Hz. As the radius of the inlet ring decreases, the sound absorption coefficient and the frequency band decrease. The studied metamaterial is suitable for various applications aimed at reducing broadband noise.
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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 | 0.001 | 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".