NRC Particle Detection Probe: Results and Analysis from Ground and Flight Tests
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">High altitude ice crystals are causing in-service events in excess of one per month for commercial aircraft. The effects include air data probes malfunctioning (pitot pressure and total air temperature in particular), and uncommanded engine power loss or flameout events. The National Research Council Canada (NRC) has developed a particle detection probe (PDP) that mounts on the fuselage of aircraft to sense and quantify the ice crystals in the environment. The probe is low-power and non-intrusive. This paper presents the results of ground and flight testing of this probe. Results are presented for ground testing in a sea level ice crystal wind tunnel and an altitude icing tunnel capable of generating both ice crystal and super-cooled liquid. The PDP was operated on several flight campaigns and the results of two will be presented. The first was on board a NRC Convair 580 aircraft in French Guiana (FG) and the second was on an Airbus operated A340 research aircraft in Darwin and Reunion Island. The flight campaigns included fully glaciated, mixed phase and fully liquid conditions. Results will be presented and compared across operating conditions at typical altitudes for commercial aircraft. Aircraft installation effects on the PDP measurements will also be examined. NRC has developed preliminary algorithms that provide reliable detection of ice crystal environment along with the ability to estimate the concentration of ice particles being encountered by the aircraft. However, the algorithms themselves are considered proprietary and therefore will not be discussed.</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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".