The effect of upstream edge geometry on the acoustic resonance excitation in shallow rectangular cavities
Bibliographic record
Abstract
The flow-excited acoustic resonance phenomenon is created when the flow instability oscillations are coupled with one of the acoustic modes of a confined duct, which in turn generates acute noise problems and/or excessive vibrations. In this study, the effect of the upstream edge geometry on attenuating these undesirable effects is investigated experimentally for flows over shallow rectangular cavities with two different aspect ratios of L/D = 1 and 1.67, where L is the cavity length and D is the cavity depth, for Mach number up to 0.45. The acoustic resonance modes of the cavity are self-excited due to the development of free shear layers over the cavity mouth. Twenty four different upstream cavity edges are investigated in this study, including round edges, chamfered edges, vortex generators, and spoilers with different sizes and configurations. The results for each upstream cavity edge are compared with the base case where sharp edge is used. Most of the spoiler edges are found to be effective in suppressing the pressure amplitude of the excited acoustic resonance. Hot-wire measurements that were taken along the lateral direction downstream of the spoilers reveal the existence of secondary vortices generated by the spoilers, orthogonal to the cavity shear layer, which results in suppressing the resonance. The performance of each spoiler depends on its specific geometry (i.e. thickness, height, and angle) and the size and strength of the orthogonal vortices that can be generated. A summary of the results is presented in this paper.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".