Experimental study of exhaust temperature variation in a homogeneous charge compression ignition engine
Bibliographic record
Abstract
Homogeneous charge compression ignition (HCCI) engines have low nitrogen oxide and particulate matter engine-out emissions but have higher unburned hydrocarbon and carbon monoxide emissions than the conventional spark ignition (SI) and diesel engines do. Only for sufficiently high exhaust gas temperatures can an exhaust after-treatment be used; thus a low exhaust gas temperature in certain operating conditions can limit the operating range in HCCI engines. The influences of the engine conditions on the exhaust gas temperature in a single-cylinder experimental engine are investigated at 340 steady state operating points. The variation in the exhaust gas temperature is also studied under transient conditions and during mode switching between SI and HCCI combustion. For the conditions tested, a significant number of data have an exhaust gas temperature below 300°C which is below the light-off temperature of typical catalytic converters on the market. Three different categories of engine variables are recognized and classified by how the exhaust temperature is affected by changing that variable. The first category is defined as the primary variables (e.g. the intake pressure and the fuel octane number) for which the location of ignition timing is the dominant factor in influencing the exhaust temperature. The other groups include compounding variables such as the engine speed and opposing variables such as the intake temperature, the coolant temperature, and the equivalence ratio. In addition, experimental results show that the exhaust temperature for HCCI engines is not strongly dependent on the engine load, unlike that for SI engines where the engine load is a main factor in determining the exhaust temperature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".