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Record W4248174955 · doi:10.1520/stp14477s

Cold Starting and Pumpability Studies in Modern Engines — Results from the ASTM D02.07C Low Temperature Engine Performance Task Force Activities: Phase I Pumpability Testing

2000· book-chapter· en· W4248174955 on OpenAlexaff
KO Henderson, CJ May, EF De Paz, FW Girshick, RB Rhodes, S Tseregounis, LH Ying

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsPhase (matter)Materials scienceComputer scienceChemistry

Abstract

fetched live from OpenAlex

LTEP Phase 1 pumpability testing focused on overnight cooling evaluation of LTEP 1–7 reference oils. Generally, each engine/oil combination was cooled in 16 hours to the desired test temperature before motoring for the pumpability evaluation. All tests in which limiting pumping criteria was achieved indicated failure by flow limited behavior rather than by air-binding failures. Two approaches were investigated for relating the time to attain a pressure at two specified engine locations to the lubricant's properties. One was to develop correlations directly between pressurization time and the lubricant's temperature in the sump, and then use these correlations to calculate the minimum pumping temperature and the corresponding maximum pumpable viscosity. The other was to develop correlations between pressurization time and the lubricant's viscosity. The first approach compared times to reach a given pressure after the oil pump (Pump Out) or the oil distribution passage downstream from the filter (Near Galley) for the observed lubricant sump temperature. A first-order exponential decay was found to give the best overall correlation for all the engine/oil combinations. All four test engines exhibited a dependency of Near Galley pressurization time on sump temperature, except for combinations involving LTEP 1 oils and the 4.6 L engine, where data were limited by cold room capabilities. Near Galley pressurization was also found to be a more stringent criterion than Pump Out in most cases. Using a 60 second 10 kPa limit, minimum pumping temperatures (MPTs) were calculated for each engine/oil combination, along with a certainty level based upon degree of extrapolation. Based upon these MPTs, limiting ASTM D 3829 viscosity was approximately 93 Pa∙s. The results also indicated that, as in the startability studies, the viscosity limit for the 4.0 L I6 engine was compatible with those of the December 1994 SAE J300 Viscosity Classification Specification, while the other engines were more in line with the December 1995 J300 Viscosity Classification Specification limit. In the second approach to pumpability analysis, a correlation between oil viscosity and pressurization time for each engine at the Pump Out or Near Galley location was developed. A linear model relating lubricant viscosity to pressurization time was found to be adequate. Analysis was done to compare viscosities as measured by ASTM Test Method for Predicting the Borderline Pumping Temperature of Engine Oil (D 3829), Test Method for Determination of Yield Stress and Apparent Viscosity of Engine Oils at Low Temperature (D 4684) and Test Method for Low Temperature, Low Shear Rate, Viscosity/Temperature Dependence of Lubricating Oils Using, a Temperature-Scanning Technique (D 5133). The model equations provided tools to calculate the limiting viscosity for these engines. As with the first approach, the results indicated that the viscosity limit for the modern engine designs was more in line with the current April 97 J300 Viscosity Classification Specification limit. Additional work was conducted to model the time/oil pressure curves from the LTEP work. It was found that most of the pressurization curves could be modeled well using a logit function.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.264
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2000
Admission routes1
Has abstractyes

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