Prediction of “buzz-saw” noise propagation under nonuniform axial and radial flows
Bibliographic record
Abstract
In the past few decades, “buzz-saw” noise was mostly measured and predicted along the shroud wall. Uniform or nonuniform axial flows were applied to the predictions. Besides, the strength of the “buzz-saw” noise was widely assumed to be identical along the radius. However, nonuniform background flows and distinct radial distributions of shock strength are observed in almost all transonic fans. A possible way to solve these problems is to couple the shock trajectory with the evolution of the shock wavefront. In case the state of background flow field varies slowly, the shock trajectory is depicted by geometric acoustics. Meanwhile, the evolution of the wavefront can be solved by the governing equation of the weak-shock. Under this framework, a method is proposed to tackle the prediction of the “buzz-saw” noise under nonuniform axial and radial flows. This method is first validated by the test data from the literature. Then, it is applied to predict the near-field noise generated by the ideal and four modified versions of NASA rotor 67. The results indicate that the nonuniform radial and axial flows introduced by the wall boundary have strong effects on the distribution of the “buzz-saw” noise. Additionally, the eccentric-force problem is revealed as a side effect of blade sorting, which is an efficient method to suppress the “buzz-saw” noise. A bi-pyramid blade sorting strategy is proposed to suppress the eccentric force introduced by other blade sorting strategies.
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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".