Analysis of Auto-Ignition Chemistry in Aeroderivative Premixers at Engine Conditions
Bibliographic record
Abstract
Abstract The minimization of auto-ignition risk is critical to the design of premixers of high power aeroderivative gas turbines as an increased use of highly reactive future fuels (for example, hydrogen or higher hydrocarbons) is anticipated. Safety factors based on ignition delays of homogeneous mixtures are generally used to guide the choice of a residence time for a given premixer. However, auto-ignition chemistry under aeroderivative conditions is fast (0.5–2 ms) and can be initiated within typical premixer residence times. The analysis of what takes place in this short period necessarily involves the study of low-temperature auto-ignition precursor chemistry, but precursors can change with fuel and local reactivity. Chemical explosive modes (CEMs) are a natural alternative to study this as they can provide a measure for auto-ignition risk by considering the whole thermochemical state in the framework of an eigenvalue problem. When transport effects are included by coupling the evolution of the chemical explosive modes to turbulence, it is possible to obtain a measure of spatial auto-ignition risk where both chemical (e.g., ignition delay) and aerodynamic (e.g., local residence time) influences are unified. In this article, we describe a method that couples large eddy simulation (LES) to newly developed, reduced auto-ignition chemical kinetics to study auto-ignition precursors in an example premixer representative of real life geometric complexity. A blend of pure methane and di-methyl ether (DME), a common fuel used for experimental auto-ignition studies, was transported using the reduced mechanism (38 species/238 reactions) under engine conditions at increasing levels of DME concentrations until exothermic auto-ignition kernels were formed. The resolution of species profiles was ensured by using a thickened flame model where dynamic thickening was carried out with a flame sensor modified to work with multistage heat release. This paper is outlined as follows: First, a reduced mechanism is constructed and validated for modeling methane as well as DME auto-ignition. Second, sensitivity analysis is used to show the need for chemical explosive modes. Third, the thickened flame model modifications are described and then applied to an example premixer at 25 bar/890 K preheat. The chemical explosive mode analysis closely follows the large thermochemical changes in the premixer as a function of DME concentrations and identifies where the premixer is sensitive and flame anchoring is likely to occur.
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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 | 0.000 |
| 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) | 0.001 | 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".