A Cold Start and Pumpability Study of Fresh and Highly Sooted Engine Oils in 1999 Heavy Duty Diesel Emission Engines
Bibliographic record
Abstract
The new API CI-4 category defines oil quality suitable for 2002 EGR-equipped heavy duty diesel engines. Included in the category is the first used oil low temperature MRV (Mini-Rotary Viscosity) limit. Over the past 15 years heavy duty pumpability studies have been the focus of a number of studies but few have evaluated used engine oils, particularly at the high soot loadings expected in EGR-equipped engines. To gain a better understanding of rheological effect, Imperial Oil initiated fired pumpability tests of sooted and fresh oils. Three 1999 model year Class 8 heavy duty diesel trucks equipped with engines from three popular manufacturers were chosen for the study conducted in Imperial Oil's All-Weather Chassis Dynamometer. Fresh 15W-40's were compared to used 15W-40 oils taken from severe line-haul service where soot loadings were in the 6-7% range; limited testing was also conducted on a fresh 0W-40 formulation. Included in the study was a fresh 15W-40 formulated to have relatively high MRV viscosity at typical starting temperatures. Warm booster batteries and low cloud point diesel fuel were employed to enhance the probability of starting in conjunction with the original cold start systems installed on the engines. The intake manifold heating system on one of the engines was not effective as a starting aid and was replaced with an on-board ether injection system similar to the other two engines. Cold starts could be achieved in the range of -17°C to -25°C depending on engine type, viscosity grade and soot load; corresponding to cold cranking simulator viscosities in the 7000-9000 mPa-s range at these temperature extremes. Significant oil pressure was observed during engine cranking prior to ignition in most cases and none of the engines exhibited air-binding tendencies. However, notable differences were observed in oil pressurization times among the three engines. In general, pressurization times were found to increase with increasing MRV viscosities, with no apparent differences between fresh and used oil correlations. As expected, the 0W-40 formulation provided excellent cold starting performance and rapid oil pressurization in all three engines at the lowest test temperature.
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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 | 0.001 | 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".