Anti-Icing Endurance Time Tests of Two Certified SAE Type 1 Aurcraft Deicing Fluids
Bibliographic record
Abstract
This report presents the results of Anti-Icing Endurance Time (AET) tests performed with unsheared samples of two certified SAE Type I aircraft deicing fluids from September 5 to October 15, 1999, at the Anti-Icing Materials International Laboratory (AMIL). Over 100 tests, including 25 calibration and 50 fluid tests, were conducted at various temperatures and icing intensities, under the six environmental conditions addressed in the holdover time (HOT) guidelines published by the SAE as part of the ARP 4737: frost (3), freezing fog (6), snow (6), freezing drizzle (4), light freezing rain (4) and rain on a cold-soaked wing (2). The results obtained demonstrate the feasibility of performing the six AET testing procedures within the prescribed accuracy and repeatability Indeed, environmental parameters in AET calibration and fluid tests were kept within the target values with variations within the allowable drifts. Moreover, AET results showed an expected inverse relationship between endurance times and precipitation rate; the shortest and longest failure times being obtained respectively under the highest and lowest icing rates. The AET test results were also compared and discussed with HOT data obtained in a parallel test set performed in July 1999 by APS Aviation (APS) at the Canadian National Research Council (NRC) facility. These tests include freezing fog, snow, freezing drizzle, and light freezing rain tests at -10 deg C, and rain on a cold-soaked wing at +1 deg C. However, their testing methods are somewhat different. AMIL failure times are systematically found to be 1 to 2 minutes shorter than APS's measured values for mean variation up to 30%, depending on test conditions. These lower failure times can be partially attributed to differences in procedures used during the test performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".