Characterization of Exhaust Gas Recirculation for Diesel Low Temperature Combustion
Why this work is in the frame
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Bibliographic record
Abstract
Exhaust Gas Recirculation (EGR) is common on most modern diesel engines resulting in significant reduction of NOx emissions. Heavy EGR application is an enabling technique for the advanced combustion modes operating in the low temperature combustion (LTC) regime, wherein simultaneous NOx and soot emission reduction can be attained. The primary effect of EGR is the dilution of the intake charge following the displacement of fresh air by the combustion products. However, the correlation between EGR and its effectiveness is non-linear due to the lean burn nature of boosted diesel engines. This correlation is further complicated when oxygenated fuels are used for combustion in the LTC mode. In this work, the intake oxygen concentration [O2]int is selected as a representative of EGR and its effectiveness in emission abatement is shown using an array of experimental results. An EGR characterization model is developed to quantify the dynamic interaction between [O2]int and engine operating variables, namely the intake boost, exhaust gas recirculation (EGR) amount, the fueling quantity and the fuel type. The model is validated on the research engine platform in steady state and transient tests. Finally, the control of EGR effectiveness is experimentally demonstrated to achieve ultra-low NOx emissions at different engine operating points.
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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) | 0.000 | 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 it