NUMERICAL AND EXPERIMENTAL STUDY ON THE EFFECT OF OVERLAP ON SAVONIUS WIND TURBINE, 1-9.
Bibliographic record
Abstract
Wind as a renewable energy source is not yet fully exploited despite the permanent availability of this source.Moreover, in countries where renewable energy regulations are still absent, largescale applications are still not available.The only wind turbines implemented are small-scaled applications owed to individual contributions.In this context, the Savonius wind turbine seems to be the most suitable choice at this scale because of its relatively low noise level, ease of manufacturing and maintenance, and self-starting aspect even at low wind speeds.However, the major drawback of such a turbine is its relatively low efficiency.In this framework, this study aims at assessing the various design parameters (number of blades, height-to-diameter ratio, and overlap ratio) of a Savonius wind turbine in an attempt to increase its efficiency.This is realised via computational fluid dynamics simulations followed by experimental validation through wind tunnel testing.Results show that the optimum configuration consists of a two-blade S-rotor with around 18% overlap.Future improvements could include shielding the returning blade to increase the torque.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".