Development of Metal Foam Based Aftertreatment System on a Diesel Passenger Car
Bibliographic record
Abstract
<div class="htmlview paragraph">An alternative metal foam substrate for exhaust aftertreatment applications has been recently presented and characterized. The present paper focuses on the potential of the metal foam technology as an efficient DOC and CDPF substrates on real-world conditions. The target platform is a mid-size passenger car and the methodology includes both modeling and experiments. The experimental testing starts from small-scale reactor characterization of the basic heat/mass transfer properties and chemical kinetics. The results show that the foam structure exhibits excellent mass-transport properties offering possibilities for precious metal and catalyst volume savings for oxidation catalyst applications. These results are also used to calibrate an advanced 2-dimensional model which is able to predict the transient filtration and reaction phenomena in axial and radial flow systems. Based on the model results, full-scale prototypes are designed and manufactured for application on 2.2 liters diesel engine for both DOC and CDPF functionalities. The prototypes are tested initially on the engine dyno and then on the chassis dyno on the European legislated driving cycle. Detailed instantaneous measurements of the gaseous and solid emissions show the potential of the system to meet the CO, HC and PM mass emission requirements for Euro 5 with a significant potential of volume and Precious Metals reduction. Finally, the real-world performance of the system is demonstrated on the road for a mileage of 22,000 km showing very slow pressure drop build-up as a result of superior passive regeneration potential.</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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".