Can-Annular Combustion Chamber Surface Temperature Measurements and Damage Signatures at Operationally Representative Conditions
Bibliographic record
Abstract
An experimental program which investigated the surface temperature distribution of a contemporary gas turbine combustion liner is presented. An array of 65 embedded surface mounted thermocouples was installed on a Rolls Royce/Allison T56 combustion liner and exposed to combustion conditions in the Combustion Chamber Sector Rig (CCSR) at the Royal Military College of Canada. The CCSR was operated at two test points to simulate idle and cruise modes of operation. Corresponding exhaust temperature measurements were taken in the test combustion chamber exhaust plane with a sweeping thermocouple rake. These efforts were the latest in a multi-year program to investigate the impact of service wear related geometric deformations of combustion liners and damaged/fouled fuel nozzles on the exit temperature profile from typical combustion chambers. It has been previously ascertained that real-world geometric anomalies in the T56 combustion chambers, particularly in the transitional zone, can modify the exhaust temperature profile to a sufficient degree so as to risk hot section damage due to excessive heat exposure. The collection and analysis of surface temperature data represents a useful extension of the knowledge base of the T56 combustion system within the context of the overall program and is paramount to upcoming numerical modelling efforts aimed at assessing hot section damage risks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".