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Record W2024723667 · doi:10.1002/cjce.5450810112

Analysis of Steady‐State Temperature Profiles from a Laboratory Reactor by Means of a Process Simulator

2003· article· en· W2024723667 on OpenAlexafffundvenue
R. R. Hudgins, Duško Pošarac, Attasak Jaree

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of British ColumbiaUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSteady state (chemistry)Ignition systemHeat transferHysteresisMaterials scienceThermodynamicsMechanicsCarbon monoxideNuclear engineeringChemistrySimulationCatalysisEngineeringPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract A process simulator was used for the analysis of steady‐state results from a laboratory‐scale tubular reactor for the oxidation of carbon monoxide over a platinum catalyst. From a set of 14 steady‐state experiments, temperature profiles were simulated with two adjustable parameters recovered by optimizing the fit: k°, the pre‐exponential portion of the rate constant, and hout, the outer wall heat transfer coefficient for the reactor tube. Simulation showed that despite elaborate insulation the reactor did not behave adiabatically. Simulation also predicted fairly well the magnitude of phenomena such as ignition, extinction, and rate hysteresis (caused by changes in feed temperatures or concentrations) but at temperatures below the experimental values.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2003
Admission routes3
Has abstractyes

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