Effect of Chordwise Flexibility and Depth of Submergence on an Oscillating Plate Underwater Propulsion System
Bibliographic record
Abstract
This work was dedicated to the experimental study of oscillating plate propulsors undergoing a combination of heave translation and pitch rotation. The oscillation kinematics are inspired by swimming mechanisms employed by fish and other marine animals. The primary focus was on the propulsive characteristics of such oscillating plates, which were studied by means of direct force measurements in the thrust-producing regime. Experiments were performed at constant Reynolds number and constant heave amplitude. By varying the Strouhal number, the depth of submergence and the chordwise flexibility of the plate, it was possible to investigate corresponding changes in the generated thrust and the hydromechanical efficiency. It was possible to establish a set of parameters, including the driving frequency of the system, the ratio of rigid to flexible segment length of the plate, and the range of Strouhal numbers that led to a peak efficiency of approximately 80%. The experiments involving plates with various ratios of rigid to flexible segment lengths showed that greater flexibility increased the propulsive efficiency and thrust compared to an identical motion of the purely rigid plate. By submerging the plate at different depths, it was observed that the proximity of the propulsor to the bottom of the channel led to overall increase in the thrust coefficient.
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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 | 0.000 |
| 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".