Energy Efficiency Improvement of Diesel Aftertreatment With Flow Reversal and Central Fuelling
Bibliographic record
Abstract
Empirical and theoretical studies are made between the inlet and central heating schemes in a flow reversal embedment of diesel aftertreatment converters in order to investigate the influences of gas flow, heat transfer, chemical reaction, oxygen concentration, and substrate properties. The periodic flow reversal converter is found effective to treat engine exhausts that are difficult to cope with conventional unidirectional flow converters. However, the previous work indicates that the exhaust temperature from modern diesel engines is commonly insufficient to sustain a high conversion or regeneration rate and thus supplemental heating techniques are commonly applied. A technique of fuelling at the central region of a flow-reversal embedment is found more energy-efficient to raise the temperature of the catalytic flow-bed and therefore to drastically reduce the supplemental heating to the substrate. An effective fuel delivery technique has been tested to improve the fuel dispersion of the central fuel delivery strategy at various engine-out exhaust temperatures, compositions, and flow rates.
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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".