Preliminary Evaluation of Drag Reduction Performance for Functional Surfaces with 60-degree Riblets Subjected to Taylor-Couette Flows
Bibliographic record
Abstract
This study outlines the initial development of a drag-reducing surface with a 60° triangular riblet-groove design.The research covers the design, microfabrication, and performance evaluation phases.The riblet-groove surface, designed with a lateral spacing of 57.8 µm and a depth of 50 µm, was based on optimized parameters from literature.Two acrylic drums were fabricated using high precision multi-axis single-point diamond turning technology, achieving excellent surface quality and form accuracy (< 2 µm).One drum had a flat surface, while the other featured the riblet-groove design.The functional performance was evaluated using a rheometer-based Taylor-Couette system, which recorded torque, angular position, and normal force synchronously and simultaneously in time domain.At high angular velocities, air naturally incorporated into the Taylor vortices, leading to an unexpected drag reduction of 39.7%, likely due to air bubbles trapped in the riblet valleys acting as a lubricant.Before air inclusion, the maximum drag reduction observed was 7.1%.Further research is needed to understand this significant improvement in drag reduction and explore its potential applications in aerospace, automotive, marine, energy, and biomedical industries.
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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) | 0.001 | 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".