Shock tube study on auto-ignition characteristics of kerosene/air mixtures
Bibliographic record
Abstract
Ignition delay times are obtained for kerosene/air mixtures behind the reflected shock waves at temperatures between 1445 and 1650 K, at a pressure of 0.11 MPa and an equivalence ratio of 1.0. A nebulization device with Laval nozzle is used to nebulize kerosene and form an aerosol phase, which evaporates and diffuses rapidly behind the incident shock waves. Mixtures auto-ignite behind the reflected shock waves. An ICCD is used to visualize the kerosene/air mixture’s ignition characteristics. The mixture’s ignition intensity increases with increase in initial temperature. Continuous and irregular flames exist below 1515 K while plane and discontinuous flames exist over 1560 K. Ignition delay times decrease with increase in initial temperature. Experimental data shows good agreement with results reported previously in the literature. A new surrogate (consisting of 10% toluene, 10% ethylbenzene and 80% n-decane) is proposed for kerosene. Honnet et al.’s mechanism is used to simulate the ignition of kerosene with calculations agreeing well with the experimental data. The sensitivity of reaction H+O 2 ⇔OH+O, which shows the highest sensitivity to the ignition delay time, increases with an increase in temperature. The chain breaching reaction of CH 3 with O 2 accelerates the total reaction rate and the H-atom abstraction of n-decane controls the total reaction rate. The rate of production and instantaneous heat production indicate that two reactions, H+O 2 ⇔OH+O and O+H 2 ⇔OH+H, are the key reactions to the formation of OH radicals, as well as the main endothermic reaction. However, the reaction of R3 is the main heat release reaction during ignition. Flame structure analysis shows that initial pressure is increased slightly as CO and H 2 O will appear before main ignition.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".