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Record W2312587868 · doi:10.1021/ef300049g

Three-Dimensional Fluorescence Spectra of Thermally Stressed Commercial Jet A-1 Aviation Fuel in the Autoxidative Regime

2012· article· en· W2312587868 on OpenAlexafffund
Mario Commodo, Ivo Fabris, Owen Wong, C. P. T. Groth, Ömer L. Gülder

Bibliographic record

VenueEnergy & Fuels · 2012
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsUniversity of Toronto
FundersConsiglio Nazionale delle RicercheShell CanadaPratt and Whitney Canada
KeywordsJet fuelJet (fluid)AviationSpectral lineFluorescenceEmission spectrumAviation fuelEnvironmental scienceMaterials scienceNuclear engineeringChemistryPhysicsAerospace engineeringEngineeringOpticsMechanicsAstronomy

Abstract

fetched live from OpenAlex

In this study, the thermal oxidative stability of a kerosene-type Jet A-1 commercial aviation fuel has been investigated using a three-dimensional (3D) excitation/emission matrix fluorescence (EEMF) method. The fuel was thermally stressed in flow test conditions over a range of temperatures in the autoxidative regime. To determine the effect of dissolved oxygen on aviation fuel thermal stability, the measurements were conducted for both air-saturated and fully deoxygenated fuel samples. The increase in the fuel temperature results in a large red shift of the fluorescence signals for the air-saturated fuel; however, fully deoxygenated fuel showed no difference in the fluorescence spectra with respect to neat fuel. The observed increase in the emission wavelengths of the collected spectra may be attributed to the formation of high-molecular-mass compounds within the liquid fuel. These species are formed as a consequence of the chemical reactions activated during the thermal stressing process. The use of 3D fluorescence spectra for aviation fuel analysis is shown to be a fast, suitable, and easily implementable tool for establishing and verifying fuel quality. Also, the level of fuel thermal degradation may be ascertained using this method, which should be of great interest for a better thermal management control of turbine engines.

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)0.000
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 score0.436
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.228
Teacher spread0.212 · 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

Citations18
Published2012
Admission routes2
Has abstractyes

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