An Experimental Assessment of Blockage and Reynolds Number Effects on Wind Turbine Wake Development
Bibliographic record
Abstract
An experiment was conducted to evaluate the initial wake expansion in scaled wind turbine tests as a means to guide future wake interference studies. Five scaled wind turbine rotors with different diameters were designed and tested in a closed-loop water channel to evaluate the effects of channel blockage and Reynolds number on the initial wake expansion behind a wind turbine in a 0.61 m × 0.81 m water channel. The initial wake expansion was assessed by using quantitative dye visualization to identify the propagation of tip vortices downstream of the rotor. The thrust coefficient developed by the scaled models was recorded using a six-component balance and was correlated to the downstream wake expansion. The rotors used in the blockage experiments were operated at a tip speed ratio (λ) of 6 and a Reynolds number based on the tip speed and tip chord of approximately 23,000. Dye visualization indicated that the initial wake expansion downstream of a rotor narrowed when the solid blockage was greater than 10% and that the vortex pairing behavior in the wake was modified due to the increase in blockage. The initial wake expansion downstream of a rotor corresponding to a blockage ratio of 25% was 3 times narrower than the expansion behind a rotor corresponding to a blockage ratio of 10% at an equivalent Reynolds number. The effect of the Reynolds number on the initial wake expansion was evaluated by testing a rotor corresponding to 10% blockage at Reynolds numbers that ranged from 3,620 to 30,100, based on the blade tip speed and tip chord, and at λ = 6. Dye visualization indicated that the initial wake expansion narrowed when the Reynolds number was lower than 10,000 but that the initial wake expansion was not strongly dependent on Reynolds number when the Reynolds number was between 20,000 and 30,100.
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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 | 0.002 |
| 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) | 0.002 | 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".