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Petroleum Coke Gasification Temperatures and Flame Spectra in the Visible Region at High Pressure

2016· article· en· W2526625057 on OpenAlexafffund
T. Parameswaran, Marc Duchesne, Scott Champagne, Robin W. Hughes

Bibliographic record

VenueEnergy & Fuels · 2016
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsNatural Resources Canada
FundersNatural Resources CanadaGovernment of Canada
KeywordsWood gas generatorPetroleum cokeCombustionSyngasCokeThermocoupleAnalytical Chemistry (journal)Materials scienceWaste managementChemistryCoalMetallurgyEnvironmental chemistryOrganic chemistryHydrogen

Abstract

fetched live from OpenAlex

In recent years, the mandate for CO 2 reduction and clean power generation has led to the advancement of research in high-pressure combustion and gasification. Traditionally, thermocouples monitor the wall temperature of a gasifier, and gas analyzers record the composition of the syngas produced. This paper describes flame emission spectroscopic measurements performed in a pilot-scale entrained-flow gasifier operating at a maximum pressure of 15 bar (g) with petroleum coke as fuel. Low cost and availability make petroleum coke attractive for use in energy production. In the current work, flame spectra observed in the visible region (500–800 nm) during petroleum coke gasification, in the pilot-scale gasifier at CanmetENERGY, are presented. These spectra were acquired with a cooled and purged fiber optic probe coupled to a spectrometer. Gasification flame spectra and information on reaction chamber temperature and the emission peaks of alkali metals and other spectral features observed in these measurements are discussed. The results show that flame emission spectroscopy is useful for gasifier performance monitoring.

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 score0.029
Threshold uncertainty score0.279

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 head0.006
GPT teacher head0.181
Teacher spread0.175 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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