Numerical Investigations Of Aerodynamic Noise Due To Flow Past A Bluff Body
Bibliographic record
Abstract
Landing gears (LG) are primarily designed to support all the loads of an aircraft during landing, taxiing, and taking off.To ease inspection and maintenance, the aerodynamic design is not refined, where many components are exposed to the air flow generating what so-called aeroacoustics noise.To understand the underline physics and investigate both the flow field and its associated acoustic field, a two-dimensional (2D) case of flow past a circular cylinder was simulated using ANSYS Fluent.Two different Reynolds numbers, Re, 150 and 90,000 were examined.For low Re, two distinct numerical conditions steady and unsteady flow were simulated and compared to examine the effect of the time dependency on the associated acoustic field.For high Re, the acoustic field was computed using the built-in Ffowcs William and Hawkings (FW-H) acoustic analogy solver in Fluent.The results show the importance of considering the time variable to extract the corresponding flow data.The far-field noise prediction highly depends on the location of the near-filed data and its associated integral source terms (surface/volume).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".