Passive Control of Combustion Instability in a Low Emissions Aeroderivative Gas Turbine
Bibliographic record
Abstract
This paper describes the conceptual ideas, the theoretical validation, the laboratory testing and the field trials of a recently patented fuel-air mixing device for use in high-pressure ratio, low emissions, gaseous-fueled gas turbines. By making the fuel-air mixing process insensitive to pressure fluctuations in the combustion chamber, it is possible to avoid the common problem of positive feedback between mixture strength and the unsteady combustion process. More specifically, a mixing duct has been designed such that fuel-air ratio fluctuations over a wide range of frequencies can be damped out by passive design means. By scaling the design in such a way that the range of damped frequencies covers the frequency spectrum of the acoustic modes in the combustor, the instability mechanism can be removed. After systematic development, this design philosophy was successfully applied to a 35:1 pressure ratio aeroderivative gas turbine yielding very low noise levels and very competitive NOx and CO measurements. The development of the new premixer is described from conceptual origins through analytic and CFD evaluation to laboratory testing and final field trials. Also included in this paper are comments about the practical issues of mixing, flashback resistance and autoignition.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".