Bibliographic record
Abstract
This paper presents an analysis of syngas combustion using 2D Direct Numerical Simulation (DNS) near Homogeneous Charge Compression Ignition (HCCI) conditions.The study examines combustion phasing achieved through varying levels of stratification which were generated within the domain to replicate different mixture distributions resulting from incomplete mixing of fuel and oxidizer streams.Simulations were categorized into two types: thermal stratification, which mimics the effect of wall cooling, and compositional stratification, which simulates the effects of evaporative cooling of cold fuel.The impact of these stratifications on the combustion dynamics was analyzed.The simulations were conducted under HCCI-relevant initial conditions (1070 K and 41 bar) using syngas as the fuel having an equimolar mixture of H2 and CO.A detailed chemical mechanism involving 21 species and 93 reactions was employed to simulate syngas autoignition.The study found that combustion phasing due to stratification resulted in two distinct combustion modes viz.volumetric ignition and deflagration.Results indicated that H2, being more reactive, was consumed earlier than CO.Thermal stratification led to smoother combustion with increased mixing or temperature fluctuations, while compositional stratification resulted in combustion behavior closer to homogeneous autoignition.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".