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Record W2331230693 · doi:10.1115/ices2012-81236

Dilution Effects on Partially-Premixed Combustion of an Ultra-Low Sulphur Diesel Fuel Under Low-Load Operation

2012· article· en· W2331230693 on OpenAlexaff
Cosmin E. Dumitrescu, W. Stuart Neill, Hongsheng Guo, Wallace L. Chippior

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDilutionBrake specific fuel consumptionExhaust gas recirculationCombustionNOxDiesel fuelDiesel engineMaterials scienceExhaust gasSootLimiting oxygen concentrationParticulatesEnvironmental scienceWaste managementChemistryAutomotive engineeringOxygenThermodynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Dilution of partially-premixed combustion (PPC) using different combinations of excess air (λ>1) and exhaust gas recirculation (EGR) was investigated in a single-cylinder, heavy-duty diesel engine equipped with common-rail fuel injection. The experiments were limited to a single fuel injection event using ultra-low sulphur diesel fuel at a low engine load (∼3 bar BMEP) and engine speeds of 900 and 1350 rpm. The start of injection was varied to optimize the combustion performance and emissions. The experimental results show that increasing air dilution at constant EGR reduced BSFC slightly. CO and HC emissions decreased significantly due to the increased oxygen concentration, but NOx and soot emissions increased. For a given level of charge dilution, there was an optimal EGR rate to minimize BSFC. NOx emissions decreased significantly as the proportion of dilution by EGR was increased, but CO and HC emissions increased due to the reduced in-cylinder temperature and oxygen concentration, which increased the combustion duration.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.944

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 communication0.0000.001
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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

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