Development of a Unique Icing Spray System for a New Facility for Certification of Large Turbofan Engines
Bibliographic record
Abstract
The Global Aerospace Centre for Icing and Environmental Research (GLACIER) facility has been constructed in Thompson, Manitoba, Canada. This project involves the construction and operation of a facility which will provide icing certification tests for large gas turbine engines, as well as performance, endurance and other gas turbine engine qualification testing. MDS Aero Support, in partnership with the National Research Council of Canada (NRC), Pratt and Whitney Canada, and Rolls Royce Canada, has developed a globally unique outdoor engine test and certification facility. The prime purpose of this facility is for icing certification of aviation gas turbine engines, initially for Rolls-Royce and Pratt & Whitney, two of the three largest gas turbine manufacturers in the world. The facility will provide the aviation industry with the required environmental conditions (by virtue of its location), and capability to meet the growing demands for icing certifications and other adverse cold weather conditions. It will also cater to other performance, endurance and specialty testing outside of the icing season. As a generic engine test facility, it includes the infrastructure and test systems necessary for the introduction of both current and future gas turbine engines. The facility is operated by MDS AeroTest which is a subsidiary of MDS Aero Support, while the icing technology and hardware that is part of the entire GLACIER facility is supplied, owned and operated by NRC on a full cost recovery basis. This paper describes the new icing facility and provides insight into the design criteria used to create the unique icing spray system developed to meet the large engine testing requirements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".