Sub-harmonic broadband humps and tip noise in low-speed ring fans
Bibliographic record
Abstract
A joint experimental and numerical study has been achieved on a low-speed axial ring fan in clean inflow. Experimental evidence shows large periodic broadband humps at lower frequencies than the blade passing frequencies and harmonics even at design conditions. These sub-harmonic humps are also found to be sensitive to the fan process and consequently to its tip geometry. Softer fans yield more intense humps more shifted to lower frequencies with respect to the fan harmonics. Unsteady turbulent flow simulations of this ring fan mounted on a test plenum have been achieved by four different methods that have been validated by comparing with overall performances and detailed hot-wire velocity measurements in the wake. Noise predictions are either obtained directly or are obtained through Ffowcs Williams and Hawkings' analogy, and compared with narrowband and third-octave power spectra. All unsteady simulations correctly capture the low flow rates, the coherent vortex dynamics in the tip clearance and consequently the noise radiation dominated by the tip noise in the low- to mid-frequency range. Yet, only the scale-adaptive simulation and the lattice Boltzmann method simulations which can describe most of the turbulent structures accurately provide the proper spectral shape and levels, and consequently the overall sound power level.
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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 | 0.001 | 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".