EXPERIMENTS IN DILUTED PREMIXED TURBULENT STAGNATION FLAMES FOR GAS-TURBINE ENGINE APPLICATIONS
Bibliographic record
Abstract
In general, turbulent combustion in gas-turbine engines occurs under conditions at which the smallest turbulent eddies are assumed to be smaller than the flame thickness but larger than the inner-layer thickness: the so-called thin reaction-zone regime. This study demonstrates a bench-top experimental technique to investigate turbulent combustion properties in this important regime, where the burning velocity of a flame is assumed to be a function of the mixture's laminar flame speed, turbulence intensity, diffusion coefficients, and the mean flame curvature. Experimental observation of turbulent counterflow flames in this thin reaction zone will be used to investigate properties of turbulent combustion and to test the applicability of turbulent burning velocity predictions. High-blockage plates upstream of a high-contraction ratio contoured nozzle are used to generate high-turbulence intensities of 20−40% in premixed methane-air flames. The experimental method makes use of two laser diagnostic techniques: (a) particle image velocimetry to measure flow velocity and turbulence intensity; (b) planar Rayleigh scattering to measure progress variable and flame-front curvature. The measured burning velocities in the thin reaction-zone regime are then determined and compared to those predicted by a previously proposed correlation and by the flamelet model. Further, the burning velocities of methane-air flames are investigated with carbon dioxide dilution to investigate the effect of varying laminar flame speed independent of turbulence intensity. Intense turbulence will bring this study into the scope of gas-turbine engines and a compact experimental apparatus allows both higher experimental resolution and simulation at lower computational cost.
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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".