Experimental Characterization of the Damping of Fuel-Air Ratio Fluctuations Using Transfer Function Analysis
Bibliographic record
Abstract
This paper presents the theoretical and experimental framework used to characterize the capability of premixers used in Dry Low Emission (DLE) gas turbines to dampen fuel-to-air ratio (FAR) oscillations and thus serve as a passive control device for combustion noise. Based on a convection-diffusion volume model, transfer function analysis in the frequency-domain was used to describe the interaction between convection and turbulent diffusion mechanisms. The study showed that the best achievable damping was obtained when the ratio of convection to turbulent diffusion effects (expressed in terms of Peclet number) was unity. For this particular condition, the spreading of Residence Time Distribution (RTD) is optimal hence decreasing the coherence between incoming and outgoing perturbations. For large Peclet numbers, mixing mechanisms are not sufficient to dampen incoming FAR fluctuations and for very small Peclet numbers FAR perturbations can be communicated almost instantaneously to the premixer outlet, without attenuation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".