Bibliographic record
Abstract
In order to meet noise specifications for future foreseen aircraft propulsion systems, such as for ultrahigh bypass ratio turbofans and contra-rotating open rotors, the dominant turbomachinery noise mechanisms need to be modeled accurately at an early design stage. Two novel methods are presented here, which could significantly improve the existing analytical noise models. For the high-solidity ultrahigh bypass ratio, a mode-matching technique based on a modal expansion of acoustic and vortical variables in each subdomain of a blade row is shown to accurately reproduce sound generation and propagation in two-dimensional bifurcated channels and in three-dimensional annular unstaggered flat-plate cascades. For the low solidity contra-rotating open rotors, several extensions to Amiet’s compressible isolated airfoil theory are coupled with Curle’s and Ffowcs Williams and Hawkings’ acoustic analogy in the frequency domain within a strip theory framework, to yield both far-field tonal and broadband noise. Including sweep in both tonal and broadband noise models is shown to significantly improve the comparison with experiments on a stationary swept airfoil in a uniform turbulent stream and on a realistic contra-rotating open rotor geometry at approach conditions.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".