Computational Aeroacoustic Prediction of Propeller Noise Using Grid-Based and Grid-Free CFD Methods
Bibliographic record
Abstract
Two CFD codes are used to simulate noise data for a tandem cylinder experiment and two scaled NASA SR-2 propeller tests.The first code, STAR CCM+, is a grid-based commercial CFD code while the second code, SmartRotor, is an in-house grid-free CFD code which uses a panel method coupled with a discrete vortex method.Good comparison to experiment is achieved, with STAR CCM+ predicting the vortex shedding of the tandem cylinder case within 3 Hz and 10 dB while also predicting first propeller harmonics within 20 and 11 dB for the first and second propeller simulations, respectively.SmartRotor predicted first propeller harmonics within 6 and 37 dB for the first and second experiments, respectively.A parametic study on the influence of blade count on propeller noise was then performed using both codes to simulating the noise of 7-, 8-, and 10-bladed propellers finding quieter operation with increasing blade count.v Convergence Criteria .......
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".