The Effect of Fluid-Resonant Coupling in High-Speed Impinging Planar Jet Flows
Bibliographic record
Abstract
This study investigates the effect of fluid-resonant coupling, i.e. the coupling between unstable modes of an impinging jet with resonant acoustic modes occurring between the nozzle and the impingement surface, on the self-excited oscillations of high-speed impinging planar jet. In order to investigate this phenomenon, a series of experiments have been performed using a high-speed impinging planar jet with varying nozzle thickness (h) and impingement distance (xo), for a single Mach number in the compressible flow regime. The test results reveal that the jet oscillation is controlled by a fluid-dynamic mechanism for small impingement distances, where the unstable mode of the jet is controlled by the impingement ratio. At larger impingement distances, the response is dominated by a fluid-resonant mechanism, in which the various hydrodynamic modes of the jet couple with different resonant acoustic modes occurring between the nozzle and the impingement surface. Within the fluid-resonant regime the system produces acoustic tones that are excited predominantly as a function of the impingement distance, with the nozzle thickness and impingement ratio having only minor effects on the tone frequency. Flow visualization images show that the same unstable mode is excited for multiple nozzle thicknesses at a constant impingement distance, despite the wide variations in associated impingement ratio.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".