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Record W2273434230 · doi:10.4271/2006-01-0446

Evaluation of Scavenging Performance in a Novel Two-Stroke GDI Engine

2006· article· en· W2273434230 on OpenAlexaff
David E. Rival, G. Ciccarelli

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2006
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsScavengingTwo-stroke engineComputer scienceAutomotive engineeringChemistryEngineeringInternal combustion engine

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">CFD simulations of the transient, three-dimensional scavenging process in a novel two-stroke gasoline direct-injection (GDI) engine were performed for a variety of engine speeds and intake pressures. The simulations entail the modeling of fresh intake air flow through a set of intake ports distributed over the cylinder head, which in turn mixes with and displaces the combustion products out through exhaust ports located at the bottom of the cylinder. Global engine performance characteristics such as scavenging efficiency as a function of crank angle and delivery ratio are quantified. Furthermore, sources of short-circuiting of the fresh air charge as well as pockets of exhaust gas recirculation are identified within the engine cylinder during the course of the scavenging process.</div>

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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.

Study designObservational
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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