A Methodology for Sizing Rotorcraft De-icing Systems Based on Ice Adhesion Strength
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-3855.vid Aircraft have long been plagued by ice formation on critical surfaces, which can have catastrophic consequences. Helicopters are prone to the effects of icing and equipping their main rotor blades with an ice protection system (IPS) may be difficult due to the rotating frame and the large de-icing power requirements compared to the total available power on the helicopter. A methodology is presented for calculating the heating requirements from an electro-thermal IPS to maintain a clean rotor blade surface. The influence of ice adhesion strength is considered making the model applicable to novel IPS which incorporate icephobic coatings. Results for a Eurocopter AS332 Super Puma show the majority of icing conditions requiring a total power between 15 to 30 kW for full ice shedding and a reduction in power of 20 to 77% in light and moderate icing conditions when considering the reduction in shedding force from an icephobic coating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".