Aeroacoustic Analysis of a Low-Subsonic Axial Fan
Bibliographic record
Abstract
A mesh convergence study of direct aero-acoustic simulations of a typical automotive engine cooling rotor is performed. The simulations are performed using the Lattice Boltzmann Method (LBM) that has been extensively used in the recent years for low speed fan applications. The influence of the mesh refinement on the global performances, the pressure distribution over the blade and in the wake and tip gap zones is investigated using the large experimental database available. The direct acoustic predictions for the different numerical setups is compared with acoustic measurements and a Ffowcs Williams and Hawking’s analogy is applied to identify the noise source contributions from the rotor parts. With the three setups investigated the convergence is achieved on the global performances and the sound power spectra. Still some discrepancies between the setups appear in the unsteady pressure loading of the blades and the wake flow. The blades are seen as the main noise contributors particularly the cusp region near the hub and the tip region with the tip flow recirculation.
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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) | 0.000 | 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) | 0.002 | 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".