Detailed Ignition Sequence Studied with a Fast Infrared Camera
Bibliographic record
Abstract
In an effort to better understand the interaction between the many parameters affecting ignition in a typical gas turbine combustor, a detailed study was made possible with a new facility available at Universite Laval in collaboration with the companies Telops, Defence Research and Development Canada - Valcartier and Pratt & Whitney Canada. The installation is primarily focused on characterizing ignition process of different biofuel mixtures compared with the reference Jet-A fuel. The experimental setup is configured with a 75 mm (3 in) sapphire infrared optical access window looking directly into the combustion chamber. A Telops high speed and high performance infrared (IR) camera was used to characterize the ignition process. Large pulsations are observed before a steady combustion finally gets established for a successful ignition. It was possible to estimate the velocity of the expanding ignition volume that compared to typical flame speed measurements. Few IR videos and photos will be presented to visualize the full phenomena that would not be visible otherwise to the naked eye. Good correlation with temperature was also established to reflect the strong virtue of IR cameras to measure accurately emitted energy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".