The Impact of Fischer—Tropsch Diesel on the Oxidation Stability of Biodiesel (FAME) Blends
Bibliographic record
Abstract
Fischer—Tropsch (FT) distillates and first generation biodiesel are alternative fuels that can both be used directly as neat fuels in an internal combustion diesel engine or as blend stocks with conventional diesel fuel. Biodiesel is generally produced by the catalytic trans-esterification of triglycerides (vegetable oil) with methanol to form fatty acid methyl esters (FAME) and glycerol as a by-product. The FT process (or FT synthesis) is a catalyzed chemical reaction in which synthesis gas (syngas), a mixture of carbon monoxide and hydrogen, is converted into liquid hydrocarbons of various compositions. The oxidation and thermal stability of diesel fuel are very important properties since unstable diesel fuels can form soluble gums and or insoluble organic particulates that can clog the fuel filters and fuels system components. In the quest for increased efficiency of internal combustion compression ignition engines, the engines are increasingly downsized and turbo charged. These developments, together with the latest demands from modern injector systems, place a greater demand on the oxidative and thermal stability performance of a fuel due to the exposure of fuels to higher temperatures in comparison to historic engine and injector designs. Recirculation of heated fuel can also cause injector deposits originating from either gum or particulate formation. Biodiesel (FAME) and FT diesel have shown to be fully compatible as blend components with conventional crude derived diesel. FT diesel, produced from the low temperature FT (LTFT) process, generally has a lower density and viscosity and good cold flow properties. It is also a very stable fuel, which compensates for the high viscosity and density, poor cold flow properties, and unstable nature associated with biodiesel (FAME). This paper discusses the results obtained from a comparative study of the oxidation stability (using the Rancimat methodology) of FT (high temperature FT and LTFT) and petroleum diesel fuels, blended with up to 20 vol % of soya and rapeseed derived biodiesel (FAME).
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".