Flow control of a wind-turbine airfoil with a leading-edge spherical dimple
Bibliographic record
Abstract
The flow separation occurred at an early angle of attack (AOA) in airfoil directs the researchers to focus on the methods of flow controlling. The present study incorporated a spherical dimple on the NACA (National Advisory Committee for Aeronautics) 4415 leading edge as a passive flow control device and compared the aerodynamic performances with the plain NACA 4415 airfoil. The dimple diameter (d) was varied from 1% to 6% of the chord length (0.01C-0.06C) to generate four numbers of the modified airfoil. A chord-based Reynolds number (Re) of 2 × 105 was selected for the present study. Shear-Stress Transport (SST) k-ω turbulence model with SIMPLE (semi-implicit method for pressure linked equations) scheme was chosen to solve the present problem computationally in ANSYS FLUENT 14.0. The results showed that the modification helped in delaying stall by 6° at the expense of 0.8% maximum lift coefficient with a dimple diameter of 0.01C. The modified airfoils experienced a primary low-velocity circular zone near the trailing edge and a secondary circulation zone at the dimple edges. In contrast, only one larger circulation zone was present near the plain airfoil trailing edge. The smallest dimple (d = 0.01C) showed a maximum lift enhancement ratio and lift to drag enhancement ratio of 14.8% and 7.86%, respectively.
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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 | 0.000 |
| 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) | 0.000 | 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".