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Record W4255936408 · doi:10.1115/icef2006-1562

An Experimental and Modeling Study of HCCI Combustion Using n-Heptane

2006· article· en· W4255936408 on OpenAlexaff
Hailin Li, Hongsheng Guo, W. Stuart Neill, Wally Chippior, Joshua D. Taylor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsHomogeneous charge compression ignitionCombustionNOxAutomotive engineeringIgnition systemMaterials scienceNuclear engineeringEnvironmental scienceThermodynamicsChemistryCombustion chamberEngineeringPhysics

Abstract

fetched live from OpenAlex

Homogeneous Charge Compression Ignition (HCCI) is an advanced combustion technology being considered for internal combustion engines due to the potential for high fuel conversion efficiency and extremely low PM and NOx emissions. In principle, HCCI involves the auto-ignition of a homogeneous mixture of fuel, air and diluents at low to moderate temperatures and high pressure. Previous research has indicated that fuel chemistry has a strong impact on HCCI combustion. This paper reports the preliminary results of an experimental and modeling study of HCCI engine operation using n-heptane, which has a well known fuel chemistry. The experiments were designed to explore the effects of intake temperature, compression ratio, air/fuel ratio, engine speed and turbo-charging on HCCI combustion. A numerical model with detailed fuel chemistry was developed to simulate the combustion process in HCCI engines and predict engine performance. The model captured the main combustion stage and its variation in phasing with critical engine parameters.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.291
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2006
Admission routes1
Has abstractyes

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