EFFECTS OF INTERNAL FUEL REFORMING AND INITIAL TEMPERATURE ON HCCI COMBUSTION OF LEAN ETHANOL/AIR MIXTURES-A COMPUTATIONAL STUDY
Bibliographic record
Abstract
Homoge11eous chCirRe compression ignition ( HCCI) engine has great potential to operate with high e_tficiency, ultm-low NOx emissions and low particulate matter. The major disadvantages of HCC/ engine are the lou· power output and inhere111 absence of combustion 011-set control. We investigated the expansion of the HCCI operating ronge and combustion control (Jy use of internal fuel reforming. The study is focused on multi sTep simulation of the engine cycle. comprised of ji1el reformation cycle and HCCI combustion cycle. In the .fite! refornwtion t·ycle the 1'(/lve timing was manipulated to create a negative valve overlap during which a fraction <J{ .fitel undergoes a reformatiou process. The rt:fornwte gas. composed mainly of hydrogen, carbon monoxide and other products of incomplete combustion. is then mixed with remainder of .fuel/ air mixture and enters the HCCI comhu.1·timt cYcle. The study is carried mu usi11g a .1·ingle-zone well-stirred reactor model and e.1·rahlished reaction mecfwni.Hns. The HCC/ engine cycle is fueled with lean mixtures of air and ethanol. This .I'Tudr denwnstrated that the .fiu!l internal n~fimning does extend the operational range of HCC/ engine into partial /o(ld region and is effectil·e in the co111lmstion on-set control. The model requires howe1·er, seveml enhancemellfs in order to moderate the crcle pressure rise and pressure magnitude, lower cycle temperatures and NO l'lllissitms.
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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 | 0.000 |
| 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".