Bibliographic record
Abstract
This study examined the impact of surface vibrations on the propulsion enhancement and the resistance reduction in the movement of parallel plates relative to each other. The research concentrated on monochromatic waves and laminar flows. The vibration wave's efficiency was evaluated by measuring the external force required to keep one of the plates moving at a fixed speed. It was found that waves moving in the opposite direction to the flow increased resistance, while the response of the flow to waves moving in the same direction as the flow is more complex and depends on the flow Reynolds number. In general, waves must be fast enough to decrease flow resistance, which creates a distinction between slow and fast waves, a helpful categorization for flows with a relatively low Reynolds number. As the Reynolds number increases, the possibility of resonances with the natural flow frequencies becomes a complication. Resonances are not possible with waves that travel faster than the plate speed and these supercritical waves usually decrease flow resistance. Slower (subcritical) waves can lead to more complex flow responses that tend to increase resistance. A complete elimination of resistance is possible if the waves are of a sufficiently short wavelength and travel at high speeds. This suggests that the mechanism has significant potential for the development of propulsion augmentation system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".