Validation and Instrumentation of a Small Modular Multi-Stage Axial Compressor for Ice Crystal Icing Research
Bibliographic record
Abstract
The National Research Council of Canada (NRC) has undergone the development of a Small Axial Compressor Rig for modelling altitude ice accretion in aircraft engines. The rig consists of two axial compressor stages measuring approximately 150mm in diameter, an extension duct to allow residence time for partial melting of ice crystals and a test piece. The axial compressor stages are intended to provide realistic engine conditioning such as fracture, pressure rise, temperature rise and centrifuging of glaciated ice crystals entering the rig. The rig was designed for use in altitude icing wind tunnels such as the NRC’s altitude icing wind tunnel (AIWT), research altitude test facility (RATFac.), and those of other organization such as NASA Glenn and Technical University of Braunshweig. Previous development work [1] provided partial validation of the aerodynamic performance of just the first compressor stage at 90% power. Recent development work has concluded the aerodynamic validation of both the first and the second stages and performance was found to be satisfactory for purpose. A prediction of the ice accretion behavior of the rig based on validated performance is provided. Details of the instrumentation scheme including measurement technique for the radial distribution of ice crystal downstream of the compressor stages, and measurement of particle sizes before and after each stage are also presented.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".