Effects of Fuel Properties and Source on Emissions from Five Different Heavy Duty Diesel Engines
Bibliographic record
Abstract
Three joint Government/Industry program have been reviewed to evaluate the effect of fuel properties and source on exhaust emissions from three post 1994 model year heavy-duty diesel engines, a single cylinder research engine and a prototype multicylinder engine designed to meet the 2004 model year oxides of nitrogen limit. The three post 1994 engines tested (at Environment Canada's facility) were a Detroit Diesel Series 50, a Caterpillar 3406E and a Cummins N14. Exhaust emissions of NOx, PM, CO, HC, and CO2 were measured using the “hot” US EPA Heavy-duty Transient Test Procedure. The single cylinder Ricardo Proteus research engine (run at the National Research Council of Canada) and the multicylinder Caterpillar 3176 prototype engine (run at the Southwest Research Institute) were tested using the AVL 8 mode test cycle. Fifteen fuels were tested in total: three “reference” Commercial Low Sulphur diesel fuels and twelve experimental fuels. The experimental fuels were blended from refinery streams in two sets of six fuels. One set of fuels was blended from oil sands derived components, the other from conventional crude derived components. The fuels were paired between the two sets: two pairs at approximately 10%, two pairs at 20% and two pairs at 30% total aromatic content by mass. Other fuel properties (including cetane number, sulphur and distillation) were controlled within a relatively narrow range for each pair of fuels. Due to testing constraints both the post 1994 and 2004 prototype multicylinder programs were tested on subsets of the experimental fuel matrix. The emission results are presented and discussed including a comparison between the different engine types.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".