Real-Time Control of Maximum Heat Release Rate and Its Influence on Emission Dispersions in Diesel Engines
Bibliographic record
Abstract
Unexpected combustions dispersion due to variations in fuel quality, production tolerance, and aging of components results in the deterioration of engine performance and increases harmful emissions. Many researchers have studied real-time combustion monitoring and control to maintain performance even under undesirable or abnormal conditions. They have reported that the reduction of combustion dispersion is promising for the decrease of emissions dispersion. In this study, we control the maximum heat release (HR) to compensate for combustion dispersion and compared the relationship between before and after control. The maximum rate of heat release (ROHRmax) is an important parameter and is highly related to engine performance and emission level. The control experiments were carried out using a diesel engine at 1500 rpm and brake mean effective pressure (BMEP) of 400 kPa, while the engine parameters were varied. The varied parameters were fuel rail pressure, swirl valve, pilot injection timing, and duration. The experimental results showed that control of the ROHRmax has the potential for the reduction of the dispersions of particulate matter (PM) emission and combustion noise even in unexpected combustion environments.
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 | 0.000 |
| 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".