The Potential for Reducing CO and NOx Emissions from an HCCI Engine Using H2O2 Addition
Bibliographic record
Abstract
The effects of hydrogen peroxide addition on iso-octane/air Homogeneous Charge Compression Ignition (HCCI) combustion have been investigated analytically. Particular attention was focused on the predications involving homogeneous gas-phase kinetics. Use was made of Peters' iso-octane mechanism in CHEMKIN and convective heat transfer was included in the analyses. This enabled the influences that H2O2 addition has on species concentration and ignition promotion and hence exhaust emissions to be determined. It was found that both CO and NOx emission levels could be ameliorated. The former effect is considered to be a result of the decomposition of H2O2 into OH intermediate species and hence reducing the time to ignition and the onset of combustion. With regards to the potential for reducing NOx, it was found that addition of H2O2 could lead to a reduction in the inlet air temperature required for the fuel/air mixture to attain auto-ignition at/near top dead centre, thereby, depressing the average cycle temperature and increasing the cycle time spent below the normal threshold temperatures required for NOx formation.
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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".