Pre-ignition characterization of partially-stratified natural gas injection
Bibliographic record
Abstract
The partially stratified charge (PSC) injection ignition strategy aims to improve thermal efficiency and reduce emissions of lean-burn spark-ignited internal combustion engines by extending the lean limit of operation. The object of the current study is to characterize the pre-ignition formation of the fuel plume in the vicinity of the PSC spark plug, using a complementary experimental and numerical approach. Visualization of the PSC plume was conducted using Schlieren motion photography in a constant volume pressure chamber at various injection pressures and signal durations. Inlet conditions were determined with 1-D and 2-D numerical models derived from experimental conditions. Subsequently, the 3-D numerical study was carried out with FLUENT using the SST k-ω turbulence model. It was found that the simulation results were adequate in representing the experimental data in terms of injection angle and jet penetration. As local fuel concentration of the spark region is vital to the stability of the combustion event, the result of this study will be instrumental in predicting the combustion quality under the PSC regime, leading to an optimized PSC system designs.
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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 | 0.000 |
| 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) | 0.001 | 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".