MétaCan
Menu
Back to cohort
Record W4238288645 · doi:10.1115/1.3043814

Extending the Lean Limit of Natural-Gas Engines

2009· article· en· W4238288645 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLean burnCombustionSpark plugNatural gasAutomotive engineeringCombustion chamberNOxIgnition systemJet (fluid)Flammability limitEnvironmental scienceEngineeringMechanical engineeringWaste managementChemistryAerospace engineering

Abstract

fetched live from OpenAlex

Two different methods to improve the thermal efficiency and reduce the emissions from lean-burn natural-gas fueled engines have been developed and are described in this paper. One method used a “squish-jet” combustion chamber designed specifically to enhance turbulence generation, while the second method provided a partially stratified-charge mixture near the spark plug in order to enhance the ignition of lean mixtures of natural gas and air. The squish-jet combustion chamber was found to reduce brake specific fuel consumption by up to 4.8% in a Ricardo Hydra engine, while the NOx efficiency trade-off was greatly improved in a Cummins L-10 engine. The partially stratified-charge combustion system extended the lean limit of operation in the Ricardo Hydra by some 10%, resulting in a 64% reduction in NOx emissions at the lean limit of operation. Both techniques were also shown to be effective in increasing the stability of combustion, thereby reducing cyclic variations in cylinder pressure.

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.

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)0.001
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 score0.161
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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