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Record W3035442184 · doi:10.22215/etd/2015-10616

Methodology and Experiments to Determine Soot and NOx Yields from a Vertical Lab-Scale Flare Burning Alkane-Mixtures and Ethylene

2015· dissertation· en· W3035442184 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

Venuenot available
Typedissertation
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsCarleton University
Fundersnot available
KeywordsSootNOxCombustionMethaneFlareChemistryAnalytical Chemistry (journal)Environmental scienceNuclear engineeringEnvironmental chemistryOrganic chemistryAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

Species yields and combustion efficiency of lab-scale flares, turbulent non-premixed buoyant flames, were measured. A new facility was constructed allowing gas mixtures to be burned on 38.1 to 76.2 mm diameter flares at flow rates up to 410 standard litres per minute. A methodology was developed to quantify species yields and combustion efficiency within calculated uncertainties. Results showed combustion efficiencies greater than 97.8% in all cases, with up to 90% of the non-CO2 carbon emitted as soot. Soot yields were heavily dependent on flare gas chemistry, ranging from an average of 7.34∙10-5 kg-soot/kg-flare-gas for methane tests to 1.20∙10-2 kg-soot/kg-flare-gas for ethylene tests. NOX data suggest that average mass yield per energy content of the flare gas is 3.76∙10-2 kg-NOX/GJ and is independent of exit conditions and fuel chemistry for the range of fuels considered. Results are compared with published soot and NOX emission factors and potential scaling methods are discussed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.058
GPT teacher head0.332
Teacher spread0.274 · 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

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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