Experimental and numerical investigations of actuator disks for wind turbines
Bibliographic record
Abstract
Abstract The expenses of a wind turbine modeling in particular a wind farm modeling either numerically or experimentally cause to take the advantages of actuator disks (AD). Porous disks (PD) are used to simulate actuator disks in experiments especially for wake studies. A rotor of a wind turbine replaced by a PD can be modeled efficiently with less cost and process time. For a proper PD selection, some semi‐empirical equations are suggested for a range of solidity of 0.2‐0.6. These equations came from a number of tests. The PDs with different dimensions and solidity values were considered for the tests and models. The results of 2D and 3D numerical simulations and the experimental results show that at the solidity of 0.5, the coefficient of performance of a PD reaches approximately 16/27 which is equal to the Betz's limit; the relation between the coefficient of power and the solidity is fitted by a parabolic equation. The average error of the proposed equations for the power coefficient is reported 1.59%. Finally, based on the current results, some semi‐empirical equations are suggested to help the initial PD selection, and then, the cost of further studies may decrease.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".