Effects of Injection Timing and EGR on Performance of CRDI Diesel Engine Fueled with Ceiba Pentandra Oil Methyl Ester (CPOME), 2-ethylhexyl nitrate and Diesel Blend
Bibliographic record
Abstract
Diesel engines are highly fuel efficient compared to gasoline engines but due to environmental concerns and the depleting amount of petroleum reserves, the need of biofuel is unavoidable in present world.Biodiesel can be easily prepared by renewable stocks and non-toxic as well as it can be used in pure state or by blending with diesel in a conventional diesel engine without any major engine modifications.In this experimental investigation, effect of injection timing advancement and exhaust gas recirculation on the performance and combustion characteristics of Ceiba Pentandra Oil Methyl Ester (CPOME), 2-ethylhexyl nitrate (EHN) and diesel blend were studied.A blend of 20% CPOME, 76% diesel and 4% EHN was prepared and compared with a blend of 80% diesel and 20% CPOME.Brake thermal efficiency (BTE), Brake specific fuel consumption (BSFC), Heat release rate (HRR), In-cylinder pressure and Rate of pressure rise were analyzed at 40% load for the injection timings of 25bTDC, 30 bTDC, 35bTDC and 40bTDC and various Exhaust Gas Recirculation (EGR) value of 5%,10%,15%.An injection timing of 40 bTDC results in reduced NOx emission, reduced Heat Release rate and Brake Thermal efficiency.Increase in BTE in 40 bTDC and 35 bTDC were recorded with introduction of EGR.The effect of EHN (cetane improver) is noticeable in both performance and combustion characteristics as it increases BTE by 5-10% in many cases.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".