Aeroelastic Design-Space Exploration for Gust-Energy Harvesting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research into gust interactions has shown significant potential for extracting energy from the atmosphere. Notably, improvements to gust-energy extractions have been shown to be possible through aeroelastic tailoring. The present work uses a design-space exploration to quantify specific structural parameters that provide the greatest energy gains from discrete and continuous gust fields. Using a genetic algorithm and full-factorial parametric sweep, wing configurations that are stiff in bending but flexible in torsion were identified to provide the best energy gains for sinusoidal and 1-cosine gusts. These designs were also subjected to a continuous von Kármán gust field, showing the same trends as the discrete profiles. The influence of the elastic and mass axis locations was shown to be much weaker on the energy gain than the stiffness parameters. Overall, energy gains relative to the steady-gliding flight performance of the aircraft of 15% were shown to be achievable through aeroelastic tailoring.
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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 | 0.001 |
| 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 | 0.001 |
| 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