Maximizing the Peak Lift-To-Drag Coefficient Ratio of Airfoils by Optimizing the Ratio of Thickness to The Camber of Airfoils
Bibliographic record
Abstract
The paper investigates the lift-to-drag coefficient ratio (CL/CD) efficiency of three airfoils, namely E387, RG15, and SD6060. The objective is to optimize the airfoils for maximum CL/CD efficiency and evaluate them using XFOIL software. The study focuses on these airfoils' performance at different Reynolds numbers (Re) from 500,000 to 1,000,000, with varying thickness-to-camber ratio percentages (t/c%). The results indicate that the E387-Opt airfoil improved the maximum CL/CD by 18.92% at Re 500,000, 23.77% at Re 600,000, 27.14% at Re 700,000, 32.44% at Re 800,000, 32.93% at Re 900,000, and 38.46% at Re 1,000,000. The RG15-Opt airfoil also demonstrated impressive performance, with a maximum CL/CD increase of 34.38% at Re 500,000, 36.75% at Re 600,000, 38.54% at Re 700,000, 41.58% at Re 800,000, 45.57% at Re 900,000, and 51.30% at Re 1,000,000. Finally, the SD6060-Opt airfoil showed even better results, with a maximum CL/CD increase of 37.07% at Re 500,000, 38.16% at Re 600,000, 42.44% at Re 700,000, 48.99% at Re 800,000, 53.10% at Re 900,000, and 56.91% at Re 1,000,000.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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 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".