Aerodynamic-Aeroacoustic Investigation of Rotating Stall in Conventional and Skewed Rotors
Bibliographic record
Abstract
An experimental investigation and a numerical simulation of aerodynamic-aeroacoustic performance of an axial-flow fan at the rotating stall condition are reported in this paper. The wake profiles of rotors were measured using two-channel, hot wire probes. The Reynolds-averaged Navier-Stokes equations of the flow field were numerically solved. The two rotors studied included a conventional and a skewed-swept rotor with the objective being to determine the influence of skew and sweep on the sound levels and rotating stall characteristic. In both cases, a single stall cell was observed in fully developed stall conditions. The experimental results showed a significant difference in stall cell hysteresis, size, circumference and spanwise position, and cell propagation velocity between the two rotors. The stall cell in the skewed rotor propagated faster than the one in the conventional rotor. A fully developed stall cell was observed near the mid-span in the skewed rotor whereas it was situated near the hub in the conventional rotor. The noise level in the skewed rotor at the stall condition was more than 2 dBA lower than in the conventional rotor. Sound frequency spectra were obtained and analyzed in the near and far fields between the skewed and conventional radial rotors at rotating stall point and at design point. Significant differences in the sound directivity between the two types of rotors at steady and unsteady operating conditions were observed throughout the measured sound region. Results showed that the numerical models predicted at the rotating stall condition with good accuracy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".