Direct noise simulation of a canonical high lift device and comparison with an analytical model
Bibliographic record
Abstract
The noise of a canonical main-element/flap high-lift device (HLD) is computed directly using compressible wall-resolved Large Eddy Simulation. An experimental database for the chosen configuration allows us to successfully validate the chosen numerical approach. Both the noise sources and the far-field acoustic pressure are shown to be well predicted. Although the two elements trailing-edge noise can be observed in the near field, the flap remains as the dominant source in the far-field. The simplicity of the studied configuration enables the comparison of the validated numerical results with a recently developed analytical model that takes into account the diffraction of the flap noise by the main-element. A two-dimensional (2D) (with and without Kutta condition) and a three-dimensional (without Kutta correction) analytical formulations are compared with the numerical results. All formulations compare favorably with the numerical reference in terms of noise levels and directivities. However, the 2D formulation with a Kutta correction provides the best quantitative agreement as expected from the narrow span of the numerical domain. The recently developed analytical model is therefore a good predictive tool for HLD, showing that it can properly account for the diffraction effect of the main element on the flap main noise source.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".