Towards nationwide implementation of 40% biodiesel blend fuel in Indonesia: a comprehensive road test and laboratory evaluation
Bibliographic record
Abstract
This research focused on evaluating the technical viability of using biodiesel with a blending ratio of 40% v/v, which is expected to be implemented soon in Indonesia. Two kinds of biodiesel blends were prepared, a blend of 60% diesel fuel and 40% biodiesel (B40) and a blend of 60% diesel fuel, 30% biodiesel, and 10% hydrogenated vegetable oil (HVO) (B30D10). The fuels were tested on EuroII vehicles without any engine modifications through a 50,000 km endurance road test. Laboratory tests were also performed at certain traveled distances to evaluate various engine parameters, including power, fuel economy, exhaust emissions, and used engine oil properties. Engine components were inspected upon the completion of the road test. Cold-start ability was also examined to confirm the suitability of the investigated biofuels at low-temperature operating conditions in Indonesia. The road test results showed that vehicles fuelled with B40 and B30D10 could reach a distance of 50,000 km without encountering any technical issues. The laboratory evaluation during the road test indicated that B30D10 had a higher power and fuel economy than B40, with a maximum difference of 2%. Furthermore, B30D10 emitted lower CO, HC, and PM emissions than B40 throughout the distance traveled, with maximum differences of 11.4%, 14.7%, and 22.6%, respectively, but led to 15% higher NOx. Engine component inspection and used engine oil analysis confirmed the fulfillment of the manufacturer's recommendations for both B40 and B30D10. Finally, B40 and B30D10 were suitable for operating at low ambient temperatures in Indonesia, confirming them as practical options to be implemented in the nationwide 40% biodiesel blend fuel.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".