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Record W4362513255 · doi:10.22215/etd/2023-15367

Design and Characterization of a Flame Spray Pyrolysis Apparatus to Compare Soot Emissions from Liquid Fuels

2023· dissertation· en· W4362513255 on OpenAlexaff
Jason Scott

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsCarleton University
Fundersnot available
KeywordsSootAgglomerateMaterials sciencePyrolysisCombustionCombustorScanning mobility particle sizerParticle numberParticle sizeAnalytical Chemistry (journal)GasolineEquivalence ratioJet (fluid)DilutionChemistryParticle-size distributionChemical engineeringComposite materialOrganic chemistryMechanicsThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

This study investigates flame spray pyrolysis (FSP) as a simple bench-top tool for comparison of soot emissions from different liquid jet fuels. A sampling assembly is designed for soot collection and particle property analysis. Soot agglomerate size distributions and elemental to total carbon ratios (EC/TC) are measured for three liquid fuels and flame conditions with Reynold's numbers and burner equivalence ratios ranging from 6000 to 9100 and 6.7 to 13.1. Day-to-day variations in the dilution ratio resulted in up to 20% variability in the measured total agglomerate number density and mobility diameters. Geometric mean primary particle and mobility diameter values are below 21 and 113 nm, in excellent agreement with those emitted from jet engines and earlier works using FSP. EC/TC is higher than 0.8 for all flames burning Jet A1, but values as low as 0.55 are measured for soot emitted from SAF burning flames.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.903

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 head0.019
GPT teacher head0.264
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

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

Citations0
Published2023
Admission routes1
Has abstractyes

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