Development of a Test Rig for the Assessment of Remotely Piloted Aircraft Systems (RPAS) in Icing
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">As the everyday use of flying small to medium size Remotely Piloted Aircraft System (RPAS) continues to evolve, so does the need to fly them in icing environments. To investigate an RPAS’ ability to fly in these conditions, an outdoor test rig has been developed at the National Research Council Canada (NRC) in which a range of RPAS have been tested in icing environments. This rig has an available test area of 3.05 m × 3.05 m, and is 5.1 m high. An array of spray nozzles installed at the top of the test rig provides a cloud that, when operated at sub-zero temperatures, enables simulation of in-flight icing conditions. The spray cloud is calibrated to provide water concentration and drop size distributions consistent with Appendix C, freezing drizzle and freezing rain conditions. Six RPAS were tested and their performance under icing conditions has been monitored via video and, where available, data provided by the on-board acquisition system was downloaded to enable flight information such as motor power and positional stability to be examined. It is shown that above a certain LWC, the time at which the systems 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).</div></div>
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".