Effects of injection parameters on CRDI-equipped stationary diesel engine fuelled with neat biodiesel mix derived from waste feedstocks
Bibliographic record
Abstract
This present work deals with the effects of injection parameters such as pilot-main injection mass ratio and dwell time on combustion, performance, and emission characteristics of a diesel engine. A single cylinder diesel engine is used in this research work with the flexibilities to modify different variables via open electronic control unit. Biodiesel mix (BDM) used in the present work is derived from waste feedstocks of used cooking oil and chicken fat. Throughout the experiment, engine load and speed were maintained constantly at 4.51 brake mean effective pressure and 1500 rpm, respectively. Different pilot mass ratios (10%, 20%, and 30%) and dwell times (20° crank angle (CA), 30° CA, and 40° CA) were tested and results were compared with conventional mode combustion. The results indicated that the pilot injections helped to reduce the ignition lag period and also shortened the combustion duration. The highest brake thermal efficiency of 34.78% was identified with the lowest pilot mass of 10%. According to the results, increased dwell time decreased the oxides of nitrogen emissions but increased the hydrocarbon emissions. The experiment revealed that BDM made of waste feedstocks could be an effective alternative for engine applications with optimized engine operating conditions.
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 | 0.000 | 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".