A Numerical Investigation on NO2 Formation in a Natural Gas–Diesel Dual Fuel Engine
Bibliographic record
Abstract
This research numerically simulates the formation and destruction of nitrogen dioxide (NO2) in a natural gas (NG)–diesel dual fuel engine using commercial CFD software converge coupled with a reduced primary reference fuel (PRF) mechanism consisting of 45 species and 142 reactions. The model was validated by comparing the simulated cylinder pressure, heat release rate (HRR), and nitrogen oxide (NOx) emissions with experimental data. The validated model was used to simulate the formation and destruction of NO2 in a NG–diesel dual fuel engine. The formation of NO2 and its correlation with the local concentration of nitric oxide (NO), methane, and temperature were examined and discussed. It was revealed that NO2 was mainly formed in the interface region between the hot NO-containing combustion products and the relatively cool unburnt methane–air mixture. The NO2 formed at the early combustion stage is usually destructed to NO after the complete oxidation of methane and n-heptane, while NO2 formed during the postcombustion process survives through the expansion process and exits the engine. The increased NO2 emissions from NG–diesel dual fuel engines was formed during the post combustion process due to higher concentration of HO2 produced during the oxidation process of the unburned methane at low temperature. A detailed analysis of the chemical reactions occurring in the NO2 containing zone consisting of NO2, NO, O2, methane, etc., was conducted using a quasi-homogeneous constant volume (QHCV) model to identify the key reactions and species dominating NO2 formation and destruction. The HO2 produced during the postcombustion process of methane was identified as the primary species dominating the formation of NO2 during the post combustion expansion process. The simulation revealed the key reaction path for the formation of HO2 noted as CH4 → CH3 → CH2O → HCO → HO2, with conversion ratios of 98%, 74%, 90%, 98%, accordingly. The backward reaction of OH + NO2 = NO + HO2 consumed 34% of HO2 for the production of NO2.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".