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Record W2049877004 · doi:10.4271/2015-01-0851

Combustion Simulation of Dual Fuel CNG Engine Using Direct Injection of Natural Gas and Diesel

2015· article· en· W2049877004 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 International Journal of Engines · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCompressed natural gasAutomotive engineeringDual (grammatical number)Natural gasCombustionDiesel fuelInternal combustion engineEnvironmental scienceHomogeneous charge compression ignitionDiesel engineFuel injectionWaste managementEngineeringCombustion chamberChemistryMechanical engineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The increased availability of natural gas (NG) in the U.S. has renewed interest in the application to heavy-duty (HD) diesel engines in order to realize fuel cost savings and reduce pollutant emissions, while increasing fuel economy.</div><div class="htmlview paragraph">Reactivity controlled compression ignition (RCCI) combustion employs two fuels with a large difference in auto-ignition properties to generate a spatial gradient of fuel-air mixtures and reactivity. Typically, a high octane fuel is premixed by means of port-injection, followed by direct injection of a high cetane fuel late in the compression stroke. Previous work by the authors has shown that NG and diesel RCCI offers improved fuel efficiency and lower oxides of nitrogen (NOx) and soot emissions when compared to conventional diesel diffusion combustion. The work concluded that NG and diesel RCCI engines are load limited by high rates of pressure rise (RoPR) (>15 bar/deg) and high peak cylinder pressure (PCP) (>200 bar). A high degree of premixing has been found by several researchers to cause excessively high rates of pressure rise thus limiting load.</div><div class="htmlview paragraph">The dual fuel engine proposed in this work employed direct injection of natural gas (DI-NG) (modeled as methane), as the main fuel, during the compression stroke in addition to early and late injections of small quantities of diesel fuel (modeled as n-heptane) to provide the ignition source. The DI-NG concept creates enhanced stratification of the NG fuel portion and avoids excessive premixing, which tempers the RoPR, thus enabling higher load operation.</div><div class="htmlview paragraph">A computational study was performed to examine the trade-offs of fuel consumption, PCP, and peak RoPR, with engine emissions. Several parameters were studied including: relative azimuthal angle between NG and diesel fuel nozzles, diesel pilot injection timing and quantity splits as well as injection timing sweeps. The results from the study indicated that DI-NG was successful in controlling the RoPR to below 10 bar/deg and PCP to less than 180 bar, while improving the NOx, HC and soot emissions to meet engine out targets for engines equipped with modern aftertreatment systems.</div></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 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 score0.112
Threshold uncertainty score0.490

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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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