Bibliographic record
Abstract
A tightly coupled fluid-structure interaction model is presented for studying the performance of flexible wings that encounter atmospheric gusts. The aerodynamic module uses a higher-order potential flow method, that provides numerical robustness and efficiency. The structural dynamics is modelled through an explicit finite difference method of the time-depenedent Euler-Bernoulli equations. Coupled together, these approaches offer numerical accuracy at a fraction of the computational time than is required for higher fidelity approaches. Previous research has suggested energy gains are possible from atmospheric gusts through aeroelastic tailoring. Case studies were performed using the aeroelastic model to investigate the merit of using aeroelastic tailoring as a passive means for performance improvement. Design trends were established that highlight configurations that achieve the best energy extraction from a gust. Reductions in wing drag of between 6.9% and 10.5% were observed, while gains of 0.25% between different aeroelastic configurations were presented. The forward sweeping of the elastic axis was deemed to have the greatest effect on energy extraction capabilities.
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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 | 0.000 | 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) | 0.001 | 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".