On association of lift generation, wake topology and kinematics of oscillating foils
Bibliographic record
Abstract
The association of lift generation and evolution of wake topology behind an oscillating foil with combined heaving and pitching motion is investigated numerically at a range of bluereduced frequency (0.16 [Formula: see text] 0.48), phase offset (0[Formula: see text] [Formula: see text] 315[Formula: see text]) and Reynolds number (1000 [Formula: see text] 4000). The pitch-dominated kinematics that coincide with the range of [Formula: see text] 120[Formula: see text] and [Formula: see text] 225[Formula: see text] suggests that leading edge vortices are suppressed while trailing edge vortices dominate the wake with increasing reduced frequency. This corresponds to a transition in wake topology from a [Formula: see text] to a reverse Von Kármán wake mode. Contrarily, heave dominated kinematics (120[Formula: see text] [Formula: see text] 225[Formula: see text]) did not exhibit any wake topology transition with increasing [Formula: see text]. The temporal lift variation associated with heave-dominated regime further revealed a symmetric feature in terms of the time taken to attain peak lift generation within an oscillation cycle. This temporal symmetry was, however, lost as kinematics transitioned from heave- to pitch-dominated regime. Analyzing the wake evolution and lift features at quarter phase of an oscillation cycle revealed the existence of a correspondence between the two processes during the heave- and pitch-dominated kinematics.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".