Using an optimisation process for sailplane winglet design
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT A multi-objective optimisation process is used to design winglets for a high-performance sailplane. The primary optimisation objective is to maximise the average cross-country speed over a range of thermal strengths. Additional contributions to the cost functions are the limitation of the total drag during high-speed cruise and the additional root bending moment due to the winglet. Rather than being a pure design study, the purpose of the herein presented study is to demonstrate that a multi-objective optimisation approach is a suitable and efficient alternative to the more traditional, experienced-based design approach. The flight performance of the winglet designs are evaluated using a higher-order potential flow method. Results of the optimisation are hand-selected for further analysis. They are compared to a traditionally designed winglet for the same aircraft, designed with similar objectives in mind. The chosen final designs provide an increase in average cross-country speed of 1.5% at lower thermal strengths and 0.4% at higher thermal strengths when compared to the traditional design. When approximating the effects of trim drag due to wing loading and static margin, these performance gains fall to 0.6% and 0.1% respectively, more closely matching the performance of the traditionally designed winglet. The final designs, along with the traditional design, provide performance benefits across all airspeeds of the flight envelope of the base aircraft without winglets.
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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 | 0.000 | 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 it