A Numerical Investigation to Identify Dimensionless Parameters for Dual-Rotor Horizontal Axis Wind Turbines
Bibliographic record
Abstract
A numerical study was carried out to identify non-dimensional parameters for dual-rotor horizontal axis wind turbines (DRWTs). Based on some important DRWT parameters such as the rotor speeds, rotor diameters and the distance between the rotors, three dimensionless parameters were derived from the Buckingham Pi theorem. Hypothetical DRWT models were created using geometrically-scaled National Renewable Energy Laboratory (NREL) Phase VI rotor geometry and operating conditions in order to confirm the validity of these parameters. The performance of each turbine was simulated using DR_HAWT, an inhouse prediction tool for single and dual-rotor wind turbines created by the current authors. The variation in normalized output power as a function of the dimensionless parameters suggests that an improved performance of DRWTs can be obtained at lower diameter and gap ratios. The NREL Phase VI rotor equipped with a 5 m geometrically-scaled upwind rotor can generate about 88% of the combined power output of two equivalent single-rotors. In addition, the effect of having an auxiliary upwind rotor reduces the angle of attack along the inboard section of the downwind blade.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".