Effects of Reynolds number and average angle of attack on the laminar scaling of oscillating foils
Bibliographic record
Abstract
The variation in thrust generation with respect to Reynolds number was numerically evaluated for an oscillating foil with combined pitching and heaving motion at a range of reduced frequencies, amplitudes, and phase offsets. Laminar scaling (Re−0.5) was found accurate for a reasonable range of average angle of attack (α¯<20°). However, quantitative evaluation of laminar scaling using statistical measures indicates that its capability in predicting thrust variation weakens at higher reduced frequencies and amplitudes. This coincides with an increase in α¯ above 20°. Evaluation of the pressure and viscous forces revealed a dominance of the former toward total thrust generated at high frequencies for all cases, which also coincided with lower coefficient of determination (R2) for laminar scaling. The chordwise variation of pressure and skin friction coefficient provided further evidence indicating that pressure, in contrast to the skin friction, did not achieve an asymptotic trend with increasing Reynolds number, especially at higher frequencies and for all phase offsets. Qualitative evaluation of the developing leading edge vortex structure at increasing reduced frequencies and Reynolds numbers also supported the quantitative assessment of chordwise pressure variations. Empirical incorporation of Reynolds number into the complete scaling model was hence completed, which further validates the laminar scaling (Re−0.5) of propulsive thrust generation in oscillating foils with a coupled motion.
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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) | 0.000 | 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 | 0.000 | 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 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".