Icing Test and Measurement Capabilities of the NRC’s Gas Turbine Laboratory
Bibliographic record
Abstract
The National Research Council’s Gas Turbine Laboratory provides industry leading icing facilities that allow manufacturers to develop, validate and certify new products for flight in adverse conditions. This paper shows how NRC measurement techniques are used across the facilities, and presents a literature-review of recently developed capabilities. The overview includes new details on some facilities, and future capabilities that are in development or planned for the near future. Methods developed at the NRC for characterizing inclement conditions are discussed and include the Isokinetic Probe, Particle Shadow Velocimetry, the Particle Detection Probe, and a size-binned real-time thermodynamic evaporation model. These are used to deliver accurate icing water content in facilities like the sea-level ice crystal generator, the Rotating Icing Rig, the Research Altitude Testing Facility, and liquid water test facilities in Ottawa and in Thompson, Manitoba at the Global Aerospace Centre for Icing and Environmental Research (GLACIER).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".