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Record W2802489128 · doi:10.1139/tcsme-2017-1038

PROPOSING A VALVE TRAIN SYSTEM FOR CYLINDER DEACTIVATION IN SI ENGINES

2017· article· en· W2802489128 on OpenAlexvenueno aff
Ly Vinh Dat, Yaojung Shiao

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCylinderAutomotive engineeringFuel efficiencyIgnition systemCylinder headSPARK (programming language)Materials scienceIgnition timingThrust specific fuel consumptionValve timingMechanical engineeringEnvironmental scienceComputer scienceInternal combustion engineEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Cylinder deactivation method can provide many advantages in improving emissions and fuel consumption at various load ranges in spark ignition (SI) engines. The study proposes a design valve train that can control the deactivation of cylinder in an inline SI engine with four cylinders. The proposed design, which is an improvement on the conventional valve train in the engine, can deactivate one- or two-cylinder mode depending on part or medium load in a vehicle. The results show that cylinder deactivation can reduce about 13–15% of fuel consumption compared with the conventional engine. The concentration of CO reduces by 15%, whereas HC decreases to about 8% when SI engine operates with different cylinder deactivation modes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.238
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicAdvanced Combustion Engine TechnologiesFrench-language works237,207