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Record W2238568102 · doi:10.4271/2005-01-3765

An Experimental Investigation of S.I. Engine Operation on Gaseous Fuels Lean Mixtures

2005· article· en· W2238568102 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

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of CalgaryNational Research Council Canada
Fundersnot available
KeywordsAutomotive engineeringEnvironmental scienceProcess engineeringWaste managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">The operation of S.I. engines on lean or diluents containing gaseous fuel-air mixtures is attractive in principle since it can provide improved fuel economy, reduced tendency to knock and low NO<sub>x</sub> emissions combined with a possible improvement to the operational life of the engine. However, the overall flame propagation rates then tend to drop sharply as the operational mixture is excessively leaned or diluted with CO<sub>2</sub> or N<sub>2</sub>.</div> <div class="htmlview paragraph">The paper presents experimental data obtained in a single cylinder, variable compression ratio, S.I., CFR engine when operated on a number of gaseous fuels and some of their mixtures. A gradual leaning of the operating mixture can affect adversely in turn, emissions of CO and unburned fuel and cyclic variation. The extent of deterioration in these operating parameters is shown to correlate well with the corresponding values of the combustion period, a key combustion indicator. Similar effects were observed when adding diluents to stoichiometric CH<sub>4</sub>-air mixtures.</div> <div class="htmlview paragraph">The addition of H<sub>2</sub> to CH<sub>4</sub> tends to accelerate the flame propagation and improve combustion stability but enhances the formation of NO<sub>x</sub>, especially for lean mixtures operation. A discussion of the possible reasons for the trends observed is presented together with outlining some possible measures to obtain low NO<sub>x</sub> emissions while keeping satisfactory rates of flame propagation.</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.

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 categoriesMeta-epidemiology (narrow)
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 score0.198
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.257
Teacher spread0.245 · 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