Predicting Hub-Height Wind Speed for Small Wind Turbine Performance Evaluation Using Tower-Mounted Cup Anemometers
Why this work is in the frame
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Bibliographic record
Abstract
Industry standards for small wind turbine (SWT) performance evaluation require estimating hub-height wind speed using either a spatially offset meteorological mast or a cup anemometer extending from a lower elevation on the turbine tower. This paper investigates the use of vertical extrapolation to reduce the uncertainty associated with tower-mounted anemometer wind speed measurements. An experimental study has been performed involving a Bergey XL.1 SWT collocated with a meteorological mast. Results indicate that power law extrapolation can significantly reduce the uncertainty of hub-height wind speed predictions, especially if concurrent wind speed measurements are available at multiple elevations. Best practice methods have been provided. To identify the upper limit of anemometer placement, a porous disk wind tunnel test has been performed and compared with three-dimensional wind speed measurements obtained experimentally. To remain outside the rotor's region of influence, it is recommended that the topmost anemometer is positioned one rotor diameter below hub-height.
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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 | 0.001 | 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 | 0.001 |
| 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