The Effects of Varying EGR Test Conditions on a Direct Injection of Natural Gas Heavy-Duty Engine with High EGR Levels
Bibliographic record
Abstract
Determining what exhaust gas recirculation (EGR) control parameters have the largest impact on engine performance and emissions is of critical importance when developing an EGR-equipped engine. These tests studied the effects of varying the net charge mass, the fresh air charge mass, the indicated power, and the oxygen equivalence ratio at various EGR fractions. The research was carried out on a direct-injection, natural gas fuelled, pilot-ignited four-stroke heavy-duty engine using Westport Innovations Inc.'s pilot-ignited, direct injection of natural gas technology. The testing was carried out using a prototype injector and the standard diesel-fuelled engine's combustion chamber. The results indicate that fuel efficiency, as well as emissions of Nitrogen Oxides (NOx) and Carbon Monoxide (CO) depend primarily on the EGR level, and not on the values of the EGR control parameters. Total Hydrocarbon (tHC) and particulate matter (PM) emissions were more dependant on the parameter combination, due primarily to changes in the combustion heat release rate and in the ignition delay time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".