The Ignition of C1–C7 Natural Gas Blends and the Effect of Hydrogen Addition in the Low and High Temperature Regimes
Bibliographic record
Abstract
Abstract New ignition delay time (IDT) measurements for two natural gas (NG) blends composed of C1 – C7 n-alkanes, NG6 (C1:60.625%, C2:20%, C3:10%, C4:5%, nC5:2.5%, nC6:1.25%, nC7:0.625%) and NG7 (C1:72.635%, C2:10%, C3:6.667%, C4:4.444%, nC5:2.965%, nC6:1.976%, nC7:1.317%) by volume with methane as the major component are presented. The measurements were recorded using a high-pressure shock tube (HPST) for stoichiometric fuel in air mixtures at reflected shock pressures (p5) of 20–30 bar and at temperatures (T5) of 987–1420 K. The current results together with rapid compression machine (RCM) measurements in the literature show that higher concentrations of the higher n-alkanes (C4 – C7) ∼1.327% in the NG7 blend compared to the NG6 blend result in the ignition for NG7 being almost a factor of two faster than NG6 at compressed temperatures of (TC) ≤ 1000 K. This is due to the low temperature chain branching reactions that occur for higher alkane oxidation kinetics in this temperature range. On the contrary, at TC > 1000 K, NG6 exhibits ∼20% faster ignition than NG7 primarily because about 12% of the methane in the NG7 blend is primarily replaced by ethane (∼10%) in NG6, which is significantly more reactive than methane at these higher temperatures. The performance of NUIGMech1.2 in simulating these data is assessed and it can reproduce the experiments within 20% for all the conditions considered in the study. We also investigate the effect of hydrogen addition to the auto-ignition of these NG blends using NUIGMech1.2 which has been validated against the existing literature for natural gas/hydrogen blends. The results demonstrate that hydrogen addition has both an inhibiting and promoting effect in the low- and high-temperatures regime, respectively. Sensitivity analyses of the hydrogen/NG mixtures are performed to understand the underlying kinetics controlling these opposite ignition effects. At low temperatures, H-atom abstraction by ȮH radicals from C3 and larger fuels are the key chain-branching reactions consuming the fuel and providing the necessary fuel radicals which undergo low temperature chemistry (LTC) leading to ignition. However, with the addition of hydrogen to the fuel mixture, the competition for ȮH radicals by H2 via the reaction H2+ȮH↔Ḣ+H2O reduces the progress of the LTC of the higher hydrocarbon fuels thereby inhibiting ignition. At higher temperatures, since Ḣ+O2↔Ö+ȮH is the most sensitive reaction promoting reactivity, the higher concentrations of H2 in the fuel mixture leads to higher Ḣ atom concentrations leading to faster ignition due to an enhanced rate of the Ḣ+O2↔Ö+ȮH reaction.
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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 | 0.000 |
| 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".