Numerical analysis of acoustic resistance affected by the corner shape of a resonator orifice
Bibliographic record
Abstract
At the orifice of a Helmholtz resonator attached on a duct, acoustic resistance increases with the grazing flow speed. When the orifice corners are rounded, the increase in acoustic resistance due to the grazing flow is suppressed compared to when the orifices are right-angled. In this study, CFD analyses on the flow field including pressure fluctuation were performed for a resonator with right-angled orifice corners (NN model) and for a resonator with rounded orifice corners (RR model). The increase in acoustic resistance obtained from the CFD analysis qualitatively agrees with the previous experimental results; Acoustic resistances of both models are almost same when the grazing flow is slow. In contrast, when the grazing flow is fast, the acoustic resistance of the RR model is about half compared to that of the NN model. Moreover, Acoustic powers at cross sections normal to longitudinal direction of the duct were calculated by integrating acoustic intensity considering the effect of time averaged flow. The acoustic powers upstream and downstream of the resonator are both almost uniform, respectively, except the region in which the acoustic intensity is highly disordered. The difference in the acoustic powers at two sections upstream and downstream of the resonator coincides with the acoustic energy consumption rate calculated by using the acoustic resistance and particle velocity through the orifice. This shows that the acoustic resistance value estimated from the transfer function of sound pressures measured at two microphone positions is plausible.
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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 | 0.001 |
| 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 | 0.001 | 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".