Fast procedure for two dimensional airfoil design
Bibliographic record
Abstract
This paper presents a fast methodology for the design of two-dimensional low-speed airfoils. We propose a methodology in which the designer starts by imposing some basic airfoil geometrical characteristics, such as: the airfoil’s radius at the leading edge, the maximum height of the airfoil’s lower and upper sides, the slopes of the airfoil’s defining curves at the trailing edge and the trailing edge gaps. Based on the above quantities, the airfoil shape is defined by use of four Bezier curves. The control points of the defining curves can be used to optimize the shape of the airfoil; optionally, any of the defining airfoil geometrical parameters can also be fed to the optimizer. The Xfoil flow solver was used for the aerodynamical calculations, and Matlab’s fmincon was used as the optimizer. The procedure was validated by using the basic geometrical characteristics of a NACA 0012 airfoil to define a general initial airfoil. The optimizer’s objective was to minimize the distance between the lift coefficient of the initial airfoil and the lift coefficient of the NACA 0012 for a Mach of 0.2 and a Reynolds number of 6 6 10 ⋅ .
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".