Optimization of airfoils and wing planforms for airborne wind \nenergy applications
Bibliographic record
Abstract
This research work focuses on the optimization of airfoils and wings for the use in airborne wind energy applications, especially crosswind kite power systems. The thesis is divided into three major parts. Each part includes an optimization framework which is composed of four blocks: an airfoil or wing geometry builder, an aerodynamic solver, an optimizer, and a post-processor. These blocks interact with each other to solve the problem of maximizing/minimizing an aerodynamic objective function while at the same time maximizing/minimizing a structural objective function such as airfoil thickness or wing aspect ratio. It is thus inevitable to have a multi-objective framework that includes both objective functions. \n \nThe first part addresses airfoil optimization by minimizing the inverse aerodynamic efficiency and the negative maximum thickness ratio, which are conflicting objectives. Results with and without induced drag (from a finite aspect ratio wing) and tether drag effects show that optimal airfoils accounting for induced drag have a cusped trailing edge, while those considering tether drag have a flap-like trailing edge, both improving aerodynamic performance. \n \nThe second part focuses on wing planform optimization, aiming to minimize the inverse aerodynamic efficiency and aspect ratio simultaneously. The optimization framework is validated by minimizing the drag-to-lift ratio, resulting in wings with elliptic planforms. The planforms optimized for aerodynamic efficiency do not differ significantly from elliptic shapes. \n \n \nThe third part of the thesis deals with the optimization of box-wing airfoils. Box-wings consist of two wings connected by vertical fins at their tips, forming a box-like shape when viewed from the front. The analysis is performed for an infinite aspect ratio, i.e., two-dimensional configuration. The inverse of the total aerodynamic efficiency and the negative of the combined maximum thickness ratio of the two airfoils are minimized simultaneously. The numerical results indicate that the optimal configurations feature a thick lower (or forward) airfoil and a thin upper (or aft) airfoil. This suggests that the lower airfoil primarily serves a structural role, while the upper airfoil plays a crucial aerodynamic role.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".