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Record W1993874649 · doi:10.1115/1.2939003

An Improved Phenomenological Soot Formation Submodel for Three-Dimensional Diesel Engine Simulations: Extension to Agglomeration of Particles into Clusters

2008· article· en· W1993874649 on OpenAlexafffund
Joan Boulanger, W. Stuart Neill, Fengshan Liu, Gregory J. Smallwood

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2008
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsNational Research Council Canada
FundersGovernment of Canada
KeywordsSootEconomies of agglomerationCombustionDiesel engineMechanicsVolume (thermodynamics)CylinderMaterials scienceDiesel fuelDiesel exhaustCombustion chamberParticulatesEnvironmental scienceThermodynamicsMechanical engineeringChemical engineeringChemistryPhysicsAutomotive engineeringEngineeringPhysical chemistry

Abstract

fetched live from OpenAlex

An extension to a phenomenological submodel for soot formation to include soot agglomeration effects is developed. The improved submodel was incorporated into a commercial computational fluid dynamics code and was used to investigate soot formation in a heavy-duty diesel engine. The results of the numerical simulation show that the soot oxidation process is reduced close to the combustion chamber walls, due to heat loss, such that larger soot particles and clusters are predicted in an annular volume at the end of the combustion cycle. These results are consistent with available in-cylinder experimental data and suggest that the cylinder of a diesel engine must be split into several volumes, each of them with a different role regarding soot formation.

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: none
Teacher disagreement score0.359
Threshold uncertainty score0.571

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 head0.020
GPT teacher head0.256
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 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
Published2008
Admission routes2
Has abstractyes

Explore more

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