Combustion Studies with FACE Diesel Fuels: A Literature Review
Bibliographic record
Abstract
The CRC Fuels for Advanced Combustion Engines (FACE) Working Group has provided a matrix of experimental diesel fuels for use in studies on the effects of three parameters, Cetane number (CN), aromatics content, and 90 vol% distillation temperature (T90), on combustion and emissions characteristics of advanced combustion strategies. Various types of fuel analyses and engine experiments were performed in well-known research institutes. This paper reviews a collection of research findings obtained with these nine fuels. An extensive collection of analyses were performed by members of the FACE working group on the FACE diesel fuels as a means of aiding in understanding the linkage between fuel properties and combustion and emissions performance. These analyses included non-traditional chemical techniques as well as established ASTM tests. In a few cases, both ASTM tests and advanced analyses agreed that some design variables differed from their target values when the fuels were produced. This review summarizes six collective engine experimental studies performed with FACE fuels with various types of engines under a range of conditions. Engine experiments under various operating conditions were performed with a 0.517-liter HCCI single-cylinder engine (SCE) and 4-cylinder 1.9-liter high-speed direct-injection (HSDI) diesel engine at Oak Ridge National Laboratory (ORNL), 0.744-liter DI diesel SCE at Navistar, and 2.44-liter DI diesel SCE and Cooperative Fuel Research (CFR) engine at National Research Council Canada (NRCC). The engine operating conditions of the six experimental programs can be categorized into one conventional diesel combustion (CDC), two homogeneous-charge compression ignition (HCCI), and three low-temperature combustion (LTC) modes. All six programs agreed that CN exhibited the strongest impacts on both combustion and emissions among the three design variables. As expected lower CN fuels exhibited longer ignition delay, which provided longer mixing periods. However, effects of aromatics were rather inconsistent in the engine experiments. In the HCCI studies higher aromatics fuels exhibited higher soot but little effect on NOx. In the two LTC studies higher aromatics and lower CN fuels exhibited higher NOX, whereas the aromatic impact on soot production was negligible. T90 effects were similar to those of CN, but at a lesser magnitude. Higher T90 fuels exhibited longer ignition delay in all experiments.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".