Bibliographic record
Abstract
Self-excitation of acoustic resonance in axisymmetric cavities can lead to a complex flow–acoustic coupling, which may result in severe noise generation. In this work, a large eddy simulation is performed to model the different flow–sound coupling mechanisms during the self-excitation of various excitable acoustic modes in an axisymmetric shallow cavity configuration with an aspect ratio of L/d = 1 over the lock-in region. The compressible Navier–Stokes equations are solved at a resolution sufficient to capture the flow and the acoustic dynamics. The excitation of three acoustic modes of different aerodynamic characteristics over the range of the tested flow velocities was observed. These modes are a stationary diametral mode, a spinning diametral mode, and a longitudinal mode. The initiation and separation of vortices over the cavity mouth accompanying the self-excitation of each mode involve different dynamics. If two antisymmetric series of vortical crescents separate successively at the leading edge, a stationary acoustic mode is excited. The formation of a continuously rotating helical vortex, connecting the leading edge and the trailing edge, leads to the excitation of the diametral spinning mode. The excitation of the longitudinal mode is associated with symmetric rings of vortices. Complex patterns of flow velocities and Reynolds stresses in the circumferential direction are observed for the diametral modes but not for the longitudinal mode. In all cases, the excitation of acoustic resonance requires a synchronization of the vortex separation and impingement processes, which is necessary for efficient feedback to sustain the flow–sound coupling mechanism.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.805 | 0.743 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".