Characterizing the cyclic variability of ignition timing in a homogeneous charge compression ignition engine fuelled with <i>n</i> -heptane/iso-octane blend fuels
Bibliographic record
Abstract
The cyclic variations of homogeneous charge compression ignition (HCCI) ignition timing is studied for a range of charge properties by varying the equivalence ratio, intake temperature, intake pressure, exhaust gas recirculation (EGR) rate, engine speed, and coolant temperature. Characterization of cyclic variations of ignition timing in HCCI at over 430 operating points on two single-cylinder engines for five different blends of primary reference fuel (PRF), (iso-octane and n-heptane) is performed. Three distinct patterns of cyclic variation for the start of combustion (SOC), combustion peak pressure ( P max ), and indicated mean effective pressure (i.m.e.p.) are observed. These patterns are normal cyclic variations, periodic cyclic variations, and cyclic variations with weak/misfired ignitions. Results also show that the position of SOC plays an important role in cyclic variations of HCCI combustion with less variation observed when SOC occurs immediately after top dead centre (TDC). Higher levels of cyclic variations are observed in the main (second) stage of HCCI combustion compared with that of the first stage for the PRF fuels studied. The sensitivity of SOC to different charge properties varies. Cyclic variation of SOC increases with an increase in the EGR rate, but it decreases with an increase in equivalence ratio, intake temperature, and coolant 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".