The Effect of Ethanol-Diesel Blends on The Performance of A Direct Injection Diesel Engine
Bibliographic record
Abstract
The experiment was conducted on a conventional direct injection diesel engine. Performance test was carried out to evaluate the performance and emission characteristics of a conventional diesel engine that operates on ethanol-diesel blends. The test procedure was performed by coupling the diesel engine on the eddy current dynamometer. Fuel consumption was measured using the AVL Fuel Balance, and a hotwire anemometer was used to measure the air consumption. Some of the emission test devices were mounted on the exhaust pipe. The test of fuel variations started from 100% diesel fuel (D100) to 2.5% (DE2.5), 5% (DE5), 7.5% (DE7.5), and 10% (DE10) ethanol additions. Performance test was conducted at 1500 rpm with load variations from 0 to 60 Nm by increasing the load on each level by 10 Nm. The addition of 5% ethanol to diesel (DE5) increased the average pressure of combustion chamber indication to 48% as well as reduced the specific fuel consumption to 9.5%. There were better exhaust emission characteristics at this mixture ratio than diesel engine which used pure diesel fuel (D100), the reduction of CO to 37%, HC to 44% and opacity to 15.9%.
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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 | 0.000 | 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".