Bibliographic record
Abstract
The work detailed in this paper is focused on updating and refining a coning rotor wind turbine concept. The coning rotor combines the load shedding properties of flapping hinges with gross change in rotor area, via large coning angles, to affect increased energy capture at nominally constant system cost. Previous studies have indicated that the large cost of energy reductions is possible, compared to the state-of-the-art machines then, particularly for abundant but presently uneconomic low-wind sites. Almost ten years later, the fundamentals of the design remain sound, but bear reevaluation relative to current machines, both exploiting modern power electronics and control technology. The coning rotor was never optimized in its own right, so an integrated design tool suitable for human and computer refinement of the design has been developed. Incorporated into the tool is a corrected blade element momentum method that more properly accounts for coned rotor aerodynamics. A discussion of the development of coning rotors is presented, along with a comparison to present operational strategies. Results obtained for nondimensionalized rotors and specific machine optimization studies are presented, followed by a discussion of further issues to be addressed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".