Low Temperature Operability Limits of Late Model Heavy Duty Diesel Trucks and the Effect Operability Additives and Changes to the Fuel Delivery System Have on Low Temperature Performance
Bibliographic record
Abstract
Engine manufacturers have raised concerns at recent industry meetings regarding the effect that 2 mm porosity filters will have on low temperature operability. An All Weather Chassis Dynamometer (AWCD) program was carried out to address this concern and to extend our general knowledge of low temperature additive performance in 1998/9 model year Heavy Duty Trucks. Known laboratory tests were also evaluated as to their ability to predict vehicle performance. Four trucks equipped with Cummins M11, Detroit Diesel Series 60, Caterpillar C12 (Southern), and Caterpillar C12 (Northern) engines were leased and fitted appropriately to measure their performance under low temperature conditions using Imperial Oil's AWCD in Sarnia, Ontario, Canada. Commercial Low Sulfur No. 2 and Low Sulfur No. 1 diesel fuels were purchased, and a series of blends were prepared representing fuels that would typically be sold during the winter. Two Low Temperature Operability Additives were used to generate response curves using standard European and North American laboratory tests. The primary laboratory tests used were cloud point, Cold Filter Plugging Point (CFPP) and Low Temperature Flow Test (LTFT). Treat rates were chosen to provide approximately 10°C of response below untreated base fuel cloud point. The treated and untreated fuels represented a range of performance from -17°C to -38°C. The fuels were then tested in the AWCD to determine the lowest operating temperatures for each fuel in each vehicle for comparison to the lab test results. Additionally, where appropriate, recommended fuel filters were replaced with a 2 mm porosity fuel filter to determine the impact of these filters on low temperature limits. In other cases, fuel heaters or Electronic Control Modules (ECM) were bypassed to determine their effect on vehicle low temperature performance. The results from this study indicate that vehicle low temperature severity is increasing compared to past studies. Bypassing the ECM had no impact on performance, but bypassing the fuel heater, as one would expect, had a negative effect on operation. The 2 mm filter had significant negative effect on low temperature performance depending on engine type and filter location in the fuel delivery system. Additives significantly lowered the operability temperature limits, but the increasing severity of engine and fuel system design suggests low temperature additive development must continue to focus on meeting the current and future engine and fuel delivery system design requirements. The LTFT, which was designed for heavy-duty truck application, provided the best prediction of low temperature performance when additives are used.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".