Identification of Noise Sources in a Realistic Turbofan Rotor Using Large Eddy Simulation
Bibliographic record
Abstract
Abstract Large Eddy Simulation (LES) is performed using the NASA Source Diagnostic Test database at approach conditions (62% of the design speed). The simulation is performed in a periodic domain containing one single blade. The aerodynamic and acoustic results are compared with the experiment. Ffowcs Williams and Hawkings’ (FWH) analogy is used to compute the far-field noise from the solid surface of the rotor blade. The analogy is computed for the full blade and for its tip region to see the contribution of the latter. The dynamic mode decomposition is performed at different iso-radii of the computational domain. The contribution of the tip region to the far-field noise is observed around the first blade passing frequency (2.8 kHz) and 4 kHz due to the mixing process of the leading-edge and tip vortices. The rest of the blade contributes more at frequencies above 7 kHz which corresponds to the trailing-edge noise. The high-amplitude modes are observed at 75% and 90% of the spanwise length. These modes contribute to the corresponding frequency humps in the far-field spectrum.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".