An Investigation of the Combustion in an IDI Diesel Engine with Low Concentrations of Added Hydrogen
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The dual-fuel engine represents in principle a simple flexible approach to employing gaseous fuels in conventional diesel engines. Compared to the use of hydrogen in spark ignition engines, there is relatively limited information about its effect when present as a supplementary fuel in suitably modified conventional compression ignition engines. This is especially for engines of the IDI type and when employing only low concentrations of hydrogen in the intake air while retaining the injection of large diesel fuel quantities.</div><div class="htmlview paragraph">In the present contribution, a 3D-CFD model based on KIVA 3, developed with a “reduced” detailed chemical kinetics of 294 elementary reaction steps with 79 chemical species for diesel fuel combustion which includes 20 steps for the oxidation of hydrogen, is outlined. The model which accounts for turbulence during combustion in engines with swirl pre-chambers was suitably verified experimentally and then employed to examine the combustion characteristics of a diesel engine with the addition of relatively small concentrations of hydrogen. The model was employed to investigate the effects of changes in a number of relatively not so easy to investigate and control experimentally parameters on the combustion processes and NOx emissions when adding low concentrations of hydrogen to the intake of an IDI diesel engine. The results showed that changes in the chamber surface temperatures, liquid fuel spray injection characteristics, and the presence of inert gas and chemically active intermediate products in the intake charge can have significant effects on engine combustion, performance and emissions.</div></div>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".