Large Eddy Simulation of Jet Noise Suppression by Impinging Microjets
Bibliographic record
Abstract
Sound suppression by impinging microjets was modeled using Large Eddy Simulation (LES). A Mj = 0:9, unheated jet, at ReDj = 400; 000 was considered. A higher-order, inhouse code was used to solve the compressible Navier-Stokes equations in the neareld. The eects of a circumferential array of microjets were modeled through source terms added to the Navier-Stokes equations. It was observed that the penetration of microjets in the core jet plume induced secondary instabilities in the shear layer which trigger a transition to turbulence close to the nozzle. The fareld sound was calculated using the Ffowcs Williams-Hawkings surface integral methodology. The microjet injection resulted in a reduction of about 4 dB in overall sound pressure levels in almost all observer locations. The power spectral density of fareld sound pressure was reduced by approximately 4 to 6 dB in very low frequency regions compared to those of the base round jet. The dierence between the spectra of the base round jet and those of the microjet setup decreased with increasing frequency. It was also observed that the microjet spectra show higher energy content beyond the cross-over frequencies corresponding to St 0:8, and St 3, for = 30 , and 90 , respectively. These trends are in very good agreement with those observed in experiments.
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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 | 0.000 | 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".