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Measurement of Laminar Flame Speed and Flammability Limits of a Biodiesel Surrogate

2016· article· en· W2507332081 on OpenAlexafffund
Carlos A. Gomez Casanova, Edwin Othen, John L. Sorensen, David B. Levin, Madjid Birouk

Bibliographic record

VenueEnergy & Fuels · 2016
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Manitoba
FundersBioFuelNet Canada
KeywordsLaminar flowLaminar flame speedBiodieselCombustionFlammability limitSchlierenDiesel fuelPremixed flameFlame speedDiffusion flameCombustion chamberGasolineAtmospheric pressureAdiabatic flame temperatureMaterials scienceMechanicsNuclear engineeringEnvironmental scienceChemistryMeteorologyCombustorOrganic chemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

Laminar flame speed of a newly developed biodiesel surrogate, 1,3-dimethoxyoctane, has been experimentally determined at standard atmospheric pressure and 433 K using a spherical combustion chamber. The 29 L combustion chamber has two pairs of fused silica windows for optical access and is also equipped with 4 pairs of axial fans for generating isotropic turbulence, which is used here to prepare homogeneous combustible mixtures of fuel and air. Schlieren technique was used to visualize and document the temporal evolution of the outwardly propagated spherical 1,3-dimethoxyoctane/air flame. An in-house developed Matlab code was employed for postprocessing of the flame front images and determining the time histories of its radius. Validation of the experimental setup and methodology was achieved by measuring the laminar flame speed of n -heptane/air mixtures at atmospheric pressure and 353 K, and compared with published reports. The results revealed that the proposed biodiesel surrogate, 1,3-dimethoxyoctane, has an overall flame speed comparable to that of published biodiesel surrogates. Furthermore, the flammability limits of the newly developed biodiesel surrogate were similar to those of gaseous hydrocarbons (e.g., methane, ethane) and higher than those of liquid fuels (e.g., gasoline, diesel).

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.426

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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 teacher head, 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
Published2016
Admission routes2
Has abstractyes

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