Auto-ignition characteristics of diesel fuel in an O<sub>2</sub>–CO<sub>2</sub> mixture
Bibliographic record
Abstract
To study diesel fuel auto-ignition in an O 2 –CO 2 mixture, a TZ (temperature zone) model is proposed. The effect of O 2 and CO 2 on reaction rate is considered. The relationship between temperature and ignition delay time is obtained. Different reduced mechanisms based on steady-state assumptions are applied in three temperature zones (T ≤ 800 K, 800 K < T ≤ 1100 K, T > 1100 K). The TZ model is coupled to KIVA-3V code for simulation calculations. To support the simulations, a constant-volume combustion bomb test bench is set up to visualize diesel fuel auto-ignition in air (21%O 2 –79%N 2 ), a 53%O 2 –47%CO 2 mixture, and a 61%O 2 –39%CO 2 mixture. Ignition delay time and the flame image in these three conditions are compared and analyzed. Then the flame temperature contour and the flame lift-off length in a 53%O 2 –47%CO 2 mixture and a 61%O 2 –39%CO 2 mixture are analyzed. The results show that diesel fuel auto-ignition can be achieved in the tested O 2 –CO 2 mixture. The TZ model can predict the auto-ignition characteristics of diesel fuel in a 53%O 2 –47%CO 2 mixture and a 61%O 2 –39%CO 2 , with errors of 12% and 10%, respectively. In these two conditions, the ignition delay time and flame lift-off length are shorter than they are in air.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".