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Record W3173357294 · doi:10.4271/2021-01-1176

Chemical Reactivity Control of DME/Ethanol Dual Fuel Combustion

2021· article· en· W3173357294 on OpenAlexaff
Simon Leblanc, Navjot Singh Sandhu, Xiao Yu, Ming Zheng, Jimi Tjong

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCombustionDual (grammatical number)Reactivity (psychology)EthanolAutomotive engineeringChemistryComputer scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The use of renewable fuels in place of conventional hydrocarbon fuels can minimize the carbon footprint of internal combustion engines. DME has been treated as a suitable surrogate to diesel fuel because of its high reactivity and soot-less combustion characteristics. The lower energy density of DME fuel demands a higher fuel supply rate to match the engine loads compared to diesel, which was achieved through prolonged injection duration and larger nozzle holes. When used as a pilot fuel to control the combustion behavior in a dual-fuel application, the fuel energy delivery rate becomes less critical allowing the use of a standard diesel common-rail injector for DME direct injection. In this work, the combustion of DME-Ethanol dual-fuel reactivity-controlled compression ignition was experimentally investigated. Compare with diesel, the high volatility of neat DME fuel can enhance its mixing with port injected fuel even under very early fuel injection timing, which is critical for reactivity-controlled compression ignition. On the other hand, the high chemical reactivity can enhance the combustion efficiency under high ethanol ratio conditions by enhancing ignition. Both factors make DME suitable as the direct injected fuel for the dual-fuel combustion process. The impact of DME pilot injection timing and DME/ethanol ratio on combustion characteristics was investigated under various engine load conditions. The results are then compared with diesel/ethanol dual fuel combustion, to discuss the impact of chemical reactivity of direct injected fuel on dual fuel combustion process.</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.

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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0020.003
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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

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