A Study of Mixed-FAME and Trace Component Effects on the Filter Blocking Propensity of FAME and FAME Blends
Bibliographic record
Abstract
Previous studies have investigated the impacts of biofuel usage on the performance, drivability and durability of modern diesel engines and exhaust after-treatment systems including test work with different types, concentrations and mixtures of bio fuel components. During this earlier work vehicle fuel filter blocking issues were encountered during a field trial using various types of EN 14214 compliant Fatty Acid Methyl Ester (FAME) blended into EN 590 diesel. This paper summarises a subsequent literature review that was carried out looking into potential causes of this filter blocking and further work that was then carried out to expand on the findings. From this, a laboratory study was carried out to assess the increase in fuel filter blocking tendency (FBT) when various FAMEs from mixed sources were blended into EN 590 diesel at different concentrations, including levels above those currently allowed in the European market. Results have indicated that there are certain ratios of FAME from different sources which interact antagonistically to form higher levels of filter deposits. Using this knowledge, experimental fuel formulations for a three-vehicle field trial were selected to assess engine and exhaust after-treatment system durability issues seen when blends made from mixed FAME sources are used. All three vehicles encountered fuel filter blocking issues during relatively early stages of the trial. Deposits from the blocked filters have been analysed which has confirmed steryl glucosides, amongst other species, to be a strong contributory factor, which is consistent with the findings of the literature review and a trace component laboratory investigation also carried out as part of this study. This paper finds that increased filter blocking tendency of mixed FAME blends is likely due to the complex interaction of trace components found in the various FAME types and is also strongly affected by storage temperatures, time in storage and properties of the base diesel.
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 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 | 0.001 | 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 | 0.000 | 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".