Bibliographic record
Abstract
Viscous flow drag represents the largest contingent of the entire drag that aerodynamic and hydrodynamic devices are subject to. Inspired by the functions of sharks skins, riblet surfaces have been studied and applied to wall structures to reduce turbulent flow drag. However, whilst structural similarity has been obtained it lacks true mimicry. This paper presents an approach of drag reduction using “Smart Surface”, a new propose composite surface that combines the riblet with an elastic coating. The “smart surface”, inspired by the self-adjustable skin of marine animals such as the dolphin, is designed to modify the traditional riblet technique and enable it to “sense” and interact with the flow by adjusting the wall structure according to the flow condition. Considering the factors of manufacture feasibility, durability and drag reduction performance in previous studies, the physical model of “Smart Surface” is designed. The preliminary establishment of corresponding prediction model has been discussed and calculated. Further work in the aspects of experimental and numerical study of this research is prospected. Key words: Drag reduction; Elastic coating; Riblet; Self-adjustable; Smart Surface
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".