Influence of piston crown shape with different positions of spark plug and fuel injector, %EGR, and fuel system control on emissions from modified GDI engines compared with a base diesel engine
Bibliographic record
Abstract
In this study, the combustion chamber profiles were developed for spray, wall, and air-guided gasoline direct injection (GDI) engines. For each combustion chamber geometry of GDI engine, the piston crown surface was modified, from hemispherical bowl, to trapezoidal bowl, and a pent roof shape that included a scoop type bowl on one side (towards injector position) to impart better squish, swirl, tumble, and turbulence effects to improve the mixing characteristics. Also, the cylinder heads were modified for each combustion chamber geometry by changing the locations of the spark plug and fuel injector. Further, the fuel split injection timings with duration, ignition timing, and the percentage of exhaust gas recirculation were optimized to reduce an engine out emissions; especially soot and nitrogen oxides. Emission tests were conducted on the base diesel engine and the GDI engine with the three different combustion chamber geometries. It is clear from the results that the emission of nitrogen oxides in the wall-guided mode was reduced by 5% till 75% of the load when compared with spray-guided and air-guided combustion modes. Overall, the GDI engine with the wall-guided combustion chamber geometry produced better results at 150 bar fuel injection pressure when compared with the base diesel engine; nitrogen oxides emission was reduced from 377 to 77 ppm and soot emissions were reduced from 29.3 to 4.5 g/km at high torque.
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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) | 0.000 | 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 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".