Investigation of tolerance for icing of remotely piloted aircraft systems (RPAS) rotors / propellers: phase 5
Bibliographic record
Abstract
An outdoor test rig to enable the operation of a Remotely Piloted Aircraft System (RPAS) in an icing environment has been designed, built and calibrated at the Montreal Road campus of the National Research Council of Canada (NRC). This rig had an available test area of 3.05 m x 3.05 m and was 5.1 m high. An array of spray nozzles installed at the top of the test rig provided a cloud that, when operated at sub-zero outdoor temperatures throughout January and February 2023, enabled simulation of in-flight icing conditions. The spray cloud was calibrated to provide water concentration and drop size distributions consistent with Appendix C, freezing drizzle and freezing rain conditions. Six RPAS were tested and showed that the time in which flight in icing could be maintained was as low as 22 seconds for some of the smaller systems examined. Where sufficient data was available, it is shown that above a certain liquid water content (LWC), the time at which the system could sustain flight in icing plateaus and no further increase in water content results in a reduction in the operational envelope. It was also found that the operational limits of the RPAS were independent of the median volumetric diameter (MVD). Generally, despite operating outside the manufacturers’ specified environmental limitations, it was found that the systems tested during this study were able to maintain varying levels of flight in icing conditions.
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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 | 0.002 |
| 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) | 0.001 | 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".