Flow characterization in the near‐wake region of a horizontal axis wind turbine
Bibliographic record
Abstract
Abstract An experimental study is conducted to investigate the flow dynamics within the near‐wake region of a horizontal axis wind turbine using particle image velocimetry (PIV). Measurements were performed in the horizontal plane in a row of four radially distributed measurement windows (tiles), which are then patched together to obtain larger measurement field. The mean and turbulent components of the flow field were measured at various blade phase angles. The mean velocity and turbulence characteristics show high dependency on the blade phase angle in the near‐wake region closer to the blade tip and become phase independent further downstream at a distance of about one rotor diameter. In the near‐wake region, both the mean and turbulent characteristics show a systemic variation with the phase angle in the blade tip region, where the highest levels of turbulence are observed. The streamlines of the instantaneous velocity field at a given phase allowed to track a tip vortex which showed wandering trend. The tip vortices are mostly formed at r/R > 1, which indicates the wake expansion. Results also show the gradual movement of the vortex region in the axial direction, which can be attributed to the dynamics of the helical tip vortices which after being generated from the tip, rotate with respect to the blade and move in the axial direction because of the axial momentum of the flow. The axial velocity deficit was compared with other laboratory and field measurements. The comparison shows qualitative similarity. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 | 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 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".