An experimental and kinetic modeling study of the auto-ignition of natural gas blends containing C1–C7 alkanes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it