Bibliographic record
Abstract
<div class="htmlview paragraph">The Gas Turbine Laboratory of the National Research Council of Canada (NRC) has been involved in icing certification testing of gas turbine engines for over 60 years. It has become evident from flight incident reports in recent years, that ice crystals can have serious effects on the performance of the core of a gas turbine. This has led to the proposal of a new certification requirement for turbofan engines.</div> <div class="htmlview paragraph">This paper describes the test facilities and procedures, as well as the analysis and verification methods, which have been used recently to develop a new ice crystal generating system. The paper describes the ice crystal production and delivery systems, as well as the design and development version for business jet sized engines. In addition, a description of some component testing using ice crystals on a heated flat plate is included to demonstrate that the facility can replicate rapid ice crystal build-up on surfaces which are significantly above the melting point. Such phenomena have been detected in compressor cores, which have been subjected to high rates of ice crystal ingestion.</div> <div class="htmlview paragraph">Finally a discussion of some of the future plans for the use of ice crystal generators integrated into a new cascade rig and an altitude chamber sufficient to accommodate testing located at the Gas Turbine Laboratory is included.</div>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 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".