In-blade angle of attack measurement and comparison with models
Bibliographic record
Abstract
The torque generated by a wind turbine blade is dependent on several parameters, one of which is the angle of attack. Several models for predicting the angle of attack in yawed conditions have been proposed in the literature, but there is a lack of experimental data to use for direct validation. To address this problem, experiments were conducted at the University of Waterloo Wind Generation Research Facility using a 3.4 m diameter test turbine. A five-hole pressure probe was installed in a modular 3D printed blade and was used to measure the angle of attack, a, as a function of several parameters. Measurements were conducted at radial positions of r/R = 0.55 and 0.72 at tip speed ratios of λ = 5.0, 3.6, and 3.1. The yaw offset of the turbine was varied from -15° to +15°. Experimental results were compared directly to angle of attack values calculated using a model proposed by Morote in 2015. Modeled values were found to be in close agreement with the experimental results. The angle of attack was shown to vary cyclically in the yawed case while remaining mostly constant when aligned with the flow, as expected. The quality of results indicates the potential of the developed instrument for wind turbine measurements.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".