Hybrid acoustic materials through assembly of tubes and microchannels: design and experimental investigation
Bibliographic record
Abstract
Purpose The purpose of this paper is the design and experimental investigation of compact hybrid sound-absorbing materials presenting low-frequency and broadband sound absorption. Design/methodology/approach The hybrid materials combine microchannels and helical tubes. Microchannels provide broadband sound absorption in the middle frequency range. Helical tubes provide low-frequency absorption. Optimal configurations of microchannels are used and analytical equations are developed to guide the design of the helical tubes. Nine hybrid materials with 30 mm thickness are produced via additive manufacturing. They are combinations of one-, two- and four-layer microchannels and helical tubes with 110, 151 and 250 mm length. The sound absorption coefficient of the hybrid materials is measured using an impedance tube. Findings The type of microchannels (i.e. one, two or four layers), the number of rotations and the number of tubes are key parameters affecting the acoustic performance. For instance, in the 500 Hz octave band (α 500 ), sound absorption of a 30 mm thick hybrid material can reach 0.52 which is 5.7 times higher than the α 500 of a typical periodic porous material with the same thickness. Moreover, the broadband sound absorption for mid-frequencies is reasonably high with and α 1000 > 0.7. The ratio of first absorption peak wavelength to structure thickness λ / T can reach 17, which is characteristic of deep-subwavelength behaviour. Originality/value The concept and experimental validation of a compact hybrid material combining a periodic porous structure such as microchannels and long helical tubes are original. The ability to increase low-frequency sound absorption at constant depth is an asset for applications where volume and weight are constraints.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".