A Straight-Bladed Variable-Pitch VAWT Concept for Improved Power Generation
Bibliographic record
Abstract
The paper presents three modifications for an improved performance in terms of increased power output of a straight-bladed VAWT by varying its pitch. Modification I examines the performance of a VAWT when the local angle of attack is kept just below the stall value throughout its rotation cycle. Although this modification results in a very significant increase in the power output for higher wind speeds, it requires abrupt changes in the local angle of attack making it physically and mechanically impossible to realize. Modification II improves upon the first by replacing the local angle of attack by the blade static-stall angle only when the former exceeds the latter. This step eliminates the two jumps in the local effective angle of attack curve but at the cost of a slight decrease in the power output. Moreover, it requires a discontinuous angle of attack correction function which may still be practically difficult to implement and also result in an early fatigue. Modification III overcomes the limitation of the second by ensuring a continuous variation in the local angle of attack correction during the rotation cycle through the use of a sinusoidal function. Although the power output obtained by using this modification is less than the two preceding ones, it has the inherent advantage of being practically feasible.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".