Effect of a New Design Electronic Control System on the Emissions Improve for Diesel Engine Operation by (Diesel + LPG)
Bibliographic record
Abstract
Diesel engines are important and widely used in many fields in industry, agriculture, transportation, and electricity, but the disadvantages of these engines are environmental pollution due to exhaust gas emissions as well as the high cost of diesel fuel. These defects made the topic an important research topic to search for less polluting and less expensive fuel to use it in diesel engines, and this makes LPG a good candidate for diesel supplements because it contains several technical advantages in this regard, being environment friendly and has a high heat value to increase energy production And also its price is cheap compared to diesel fuel. In this study, an electronic system was designed to control the LPG injector and a magnetic sensor was installed on top of a single-cylinder and air-cooled diesel engine head. Tested using at two-stage first diesel fuel D-100 and second stage, dual-fuel in three modes . The test was under loads (0%, 25%, 50%, 75% and 100%) at different speeds (1000, 1500 and 2000 rpm). A decrease in emission ratios (NOx, HC, CO, and CO2) is observed in all operating modes with LPG, and the best emission reduction mode is LPG-75. As for O2 gas, the results showed almost the same in diesel case.
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 | 0.000 | 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 | 0.001 |
| 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".