Ignition Studies of C1–C7 Natural Gas Blends at Gas-Turbine-Relevant Conditions
Bibliographic record
Abstract
Abstract New ignition delay time measurements of natural gas mixtures enriched with small amounts of n-hexane and n-heptane were performed in a rapid compression machine to interpret the sensitization effect of heavier hydrocarbons on auto-ignition at gas-turbine relevant conditions. The experimental data of natural gas mixtures containing alkanes from methane to n-heptane were carried out over a wide range of temperatures (840–1050 K), pressures (20–30 bar), and equivalence ratios (φ = 0.5 and 1.5). The experiments were complimented with numerical simulations using a detailed kinetic model developed to investigate the effect of n-hexane and n-heptane additions. Model predictions show that the addition of even small amounts (1–2%) of n-hexane and n-heptane can lead to an increase in reactivity by ∼40–60 ms at compressed temperature (TC) = 700 K. The ignition delay time (IDT) of these mixtures decreases rapidly with an increase in concentration of up to 7.5% but becomes almost independent of the C6/C7 concentration beyond 10%. This sensitization effect of C6 and C7 is also found to be more pronounced in the temperature range 700–900 K compared to that at higher temperatures (>900 K). The reason is attributed to the dependence of IDT primarily on H2O2(+M) ↔ 2ȮH(+M) at higher temperatures while the fuel-dependent reactions such as H-atom abstraction, RȮ2 dissociation, or Q˙OOH + O2 reactions are less important compared to 700–900 K, where they are very important.
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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 | 0.001 |
| 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 | 0.000 | 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".