Experimental Investigation of Power Density Enhancement for a Small Wind Turbine Augmented With a Novel Deflector
Bibliographic record
Abstract
This paper explains a novel concept for wind power density enhancement through the use of specially shaped static wind deflector structures. The design and fabrication of the deflectors and the experimental results are explained. The general wind enhancement concept is further divided into two separate but related versions. The first deflector version discussed herein is a closed or constrained-flow device proposed for energy recapture from industrial-scale ventilation exhaust air. The second deflector version discussed herein is an open or unconstrained-flow device proposed for low wind velocity (< 4 m/s) applications and thus offers potential for wind power generation in built-up urban environments. Experiments associated with the two design adaptations were performed on a test-duct and in a wind tunnel, respectively. The test results showed velocity increases (factors of 3 and 1.7 respectively). The test-duct results for the constrained-flow device also showed turbine power output enhancement by a factor of approximately 20. Neglecting other losses, such a ratio would provide a theoretical power improvement of about 5 times over the base flow velocity. The term Wind Powered Deflector (WPD) was coined to describe the devices discussed herein.
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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 | 0.001 |
| 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".