Assessment of the LES-FGM framework for capturing stable and unstable modes in a hydrogen / methane fuelled premixed combustor
Bibliographic record
Abstract
The main objective of this paper is to assess the capability of compressible Large Eddy Simulations (LES) to capture azimuthal combustion instability . The thickened flame model coupled with Flamelet Generated Manifold (FGM) tabulated chemistry is used as the combustion model. LES of an annular combustor is performed for five cases featuring stable and unstable combustion of hydrogen-methane mixtures. The unstable modes feature azimuthal instabilities and this annular combustor is used to test the LES-FGM framework. A consistent methodology is applied across all cases. It is found that LES predicts azimuthal modes for stable cases but these modes are weak and intermittent with pressure fluctuation amplitudes within the order of experimental noise. In addition, the unstable cases capture azimuthal modes that have approximately the same frequency as that of the experiment though the amplitudes of the modes are over-predicted. This suggests that the described LES-FGM framework is able to predict the onset of thermoacoustic instabilities and their qualitative changes with addition of hydrogen.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".