ACAT1 Fan Stage Broadband Noise Prediction Using Large-Eddy Simulation and Analytical Models
Bibliographic record
Abstract
The present paper deals with the assessment of the turbulent flow through and the noise radiation of the ACAT1 fan stage, which was tested in the framework of the European project TurbonoiseBB. It aims at analyzing and predicting the broadband noise resulting from the impact of the fan wakes onto the outlet guide vane (OGV) at approach condition. This is achieved via a large-eddy simulation (LES) of the full fan-OGV stage that is in good agreement with the mean flow measurements. Some disparities regarding the turbulent content of the flow are, however, highlighted. The main flow features and the broadband noise sources are examined. The noise is then estimated using two different hybrid approaches: LES-informed analytical models, using Hanson’s and Posson’s cascade models, and a numerical approach coupling the LES with the free-field Ffowcs Williams and Hawkings (FW-H) analogy, and Goldstein’s in-duct acoustic analogy. The shape of the noise spectra provided by the analytical models is relatively similar to that of the sound measurements, whereas some discrepancies on the absolute noise levels may appear depending on the analytical model and the turbulence length scale estimate. The numerical approach reveals that accounting for the duct effect through Goldstein’s analogy provides noise levels much closer to the measurements than those obtained with the free-field analogy, which significantly overestimates the broadband noise. Both the analytical and the numerical approaches suggest that additional significant noise sources might be present in both the experiment and the simulation.
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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".