Modeling of Three-dimensional Unsteady Wake Past a Large Migratory Bird during Flapping Flight
Bibliographic record
Abstract
This preliminary study aimed to model the aerodynamic behavior of a large migratory bird during a forward flapping flight. Computational Fluid Dynamics (CFD) was used to model the flow around and in the wake of a Canada Goose flying at an altitude of 1000m and a speed of 13.9m/sec. Flapping of the wings was modeled through dynamic meshing and subroutines implemented in a computational code using the Finite Volumes method. Monitoring of the flow quantities during the unsteady calculation revealed a close relationship between the wing-flapping dynamics and the cyclic variation of the forces acting on the bird. Post-processing of the 3D results revealed a complex flow pattern mainly composed of two contra-rotating vortices developing at the wingtip. In a perpendicular plane to the main flow direction, we demonstrated that the bird's wake can be divided into two distinct zones: the downwash zone and the upwash zone. The latter is used by birds flying in formation to reduce their energy expenditure. We have also shown that when the bird flaps its wings, the trail of upwash left by the wingtips moves up and down in a wave-like motion. Further studies, which will include several birds, will be necessary to understand all the aerodynamic implications related to the flight of migratory birds in formation.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".