Broadband interaction noise predictions for an axial compressor stator
Bibliographic record
Abstract
The broadband interaction noise of the axial compressor stator-only configuration in the Aeroacoustic Wind Tunnel (AWT) at the Leibniz University Hannover is investigated in this work. Posson’s analytical model, which uses a threedimensional rectilinear cascade response model coupled with an in-duct acoustic analogy for the subsequent acoustic propagation, is employed to estimate the noise from impinging gusts. First, a model validation with experimental results of NASA’s Source Diagnostic Test (SDT) AIAA benchmark is presented. For the subsequent compressor stator investigations, the model inputs are derived from numerical pre-tests using steady RANS simulations. Assuming homogeneous isotropic turbulence, two different models by Liepmann and Von Kármán are applied to calculate the velocity turbulence spectrum and radial correlation length. Finally, the acoustic results are evaluated by comparing the sound power spectra upstream and downstream of the compressor stator vane. The resulting differences can be related to variations in axial velocities and integral turbulent length scale for all four operating conditions. The obtained broadband interaction noise estimations of the test rig serve as a baseline for following experimental noise measurements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".