OH-PLIF Measurements for Micromixed Flames in a Multi-Injector Burner at Elevated Pressures and Temperatures
Bibliographic record
Abstract
Abstract A multi-injector combustion system consisting of seven premix/micromix injectors is studied in the high-pressure Optically Accessible Combustion Rig (OACR) which is commissioned for the first time at the National Research Council Canada (NRC). The clustered design mimics the packaging expected in industrial applications where hundreds of such injectors will be needed to provide the desired power output. The pressure vessel and test facility allow for an investigation of the combustion system up to 922 K and 20 bar inlet temperature and pressure, respectively. It provides conditions closer to gas turbine operation to investigate the impact of pressure on micromixed flames and provide pressure scaling, such as for emissions and flame characteristics, to be used for extrapolating to full gas turbine load. Three of the five optical windows of the OACR are used in the current experimental configuration to monitor the flames with direct imaging and perform non-intrusive OH-planar laser-induced fluorescence (OH-PLIF), for the first time in this rig. The current work focuses on the combustion of pure hydrogen in micromixed flames to commission the added hydrogen capabilities of the test cell and the laser diagnostics. Globally-lean hydrogen flames operating at the same preheated air temperature, target flame temperature, and pressure drop across the injectors are investigated at pressures of 2.5, 5, 7, 10, and 15 bar to isolate the impact of pressure on combustion. Increasing pressure is found to significantly deteriorate the quality of raw OH-PLIF images, down to a mean signal-to-noise ratio of 1.7 at 15 bar. Spatial filtering corrects for horizontal intensity striations believed to be caused by combustor cooling in the high-pressure environment, before a qualitative exponential relationship is used to correct for laser attenuation in the high-pressure environment and through multiple flames. The laser sheet slicing across the centerline axis of three inline nozzles mostly captures the main flame body in the turbulent wake of the micromix jets of the complex tridimensional structures. Little changes in flame structures are observed with increasing pressure, with the 15 bar condition moving slightly downstream from the nozzle exit. The results suggest that injector concept screening at lower pressure while maintaining the other operating conditions similar may be possible before pursuing additional elevated-pressure testing.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".