An experimental and kinetic modeling study of the auto-ignition of natural gas blends containing C1–C7 alkanes
Bibliographic record
Abstract
Ignition delay time measurements for multi-component natural gas mixtures were carried out using a rapid compression machine at conditions relevant to gas turbine operation, at equivalence ratios of 0.5–2.0 in ‘air’ in the temperature range 650–1050 K, at pressures of 10–30 bar. Natural gas mixtures comprising C1–C7 n-alkanes with methane as the major component (volume fraction: 0.35–0.98) were considered. A design of experiments was employed to minimize the number of experiments needed to cover the wide range of pressures, temperatures and equivalence ratios. The new experimental data, together with available literature data, were used to develop and assess a comprehensive chemical kinetic model. Replacing 1.875% methane with 1.25% n-hexane and 0.625% n-heptane in a mixture containing C1–C5 components leads to a significant increase in a mixture's reactivity. The mixtures containing heavier hydrocarbons also tend to show a strong negative temperature coefficient and two-stage ignition behavior. Sensitivity analyses of the C1–C7 blends have been performed to highlight the key reactions controlling their ignition behavior.
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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) | 0.001 | 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 | 0.001 | 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".