Aeroelastic modelling of tail fins for small wind turbines
Bibliographic record
Abstract
Abstract Many small upwind turbines use a tail fin to align the rotor with the wind. Despite the importance of a well-designed fin for efficient operation and in generating ultimate and fatigue loads, the aeroelastic modelling of tail fins is not well developed. This work extends the previous linearized analyses by including nonlinear effects and the difference between the yaw angle and the angle of attack. The analysis is based on unsteady slender body theory, but includes the vortex lift generated at high angles of attack and the effects of vortex bursting. The model predicts with reasonable accuracy the yaw behaviour of delta-shaped tail fins (without a rotor) released at 45° in a wind tunnel, provided allowance is made for the viscous friction in the yaw bearings. The difference in the response frequency between the linear and nonlinear model increases at the higher yaw angle of 80° for which no wind tunnel measurements are available. As a first step towards simplifying the nonlinear model, the difference in yaw angle predictions from the linear model is estimated. The maximum difference is a function of initial yaw angle and is large for yaw angles of magnitude greater than 45°.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".