Wake model effects on the prediction of turbulence-interaction broadband noise in a realistic compressor stage
Bibliographic record
Abstract
The effects of the wake modelling on the prediction of the broadband noise generated by the impingement of the turbulent wakes on a stationary blade row are studied. The analysis focuses on the description of the wake shape that is usually approximated by a Gaussian curve for acoustical purposes. The prediction of the broadband noise is achieved using an analytical acoustic model dedicated to turbomachinery configurations. The characteristics of the model regarding the wake treatment are described. In order to provide a realistic reference for the wake shape, a low-speed axial compressor stage is analyzed using numerical RANS simulation. The unsteady flow-field structure is presented. The simulation is validated using a comparison with experimental data, with special attention paid for the wake numerical prediction. The shape of the rotor wakes is thoroughly described. The comparison between the simulated wake and the corresponding Gaussian approximation is detailed, showing differences between the two approaches. The broadband predictions yielded by the two wake models are finally compared. The use of the Gaussian approximation of the wakes shape for broadband noise prediction purposes is validated in the studied realistic configuration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".