Compressor Stage Broadband Noise Prediction using a Large-Eddy Simulation and Comparisons with a Cascade Response Model
Bibliographic record
Abstract
The present work addresses the rotor-stator interaction broadband noise prediction. The objectives are first to develop a numerical acoustic method and second to deepen the understanding of this noise mechanism to improve an existing analytical model. The two steps of the numerical method consist in performing a Large-Eddy Simulation of an actual rotor-stator stage in order to directly extract the broadband pressure fluctuations on the stator vanes. Then the latter are used as equivalent noise sources in Goldstein acoustic analogy in the frequency domain. An axial flow compressor stage is used as a test case. The mean and unsteady components of the flow are analyzed. The turbulent properties of the flow needed in the analytical model are extracted from the LES. The unsteady pressure on the vanes predicted by the LES exhibits very different behaviors depending on the position on the vane that are attributed to several mechanisms such as turbulent wake interaction or boundary layer transition. The spanwise coherence length representing a crucial parameter for the analytical model is also investigated from the numerical vane response, showing a longer value than the one usually considered in the analytical model. The acoustic power spectra predicted by both approaches are compared and the effect of the spanwise coherence length is studied.
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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".