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Record W3120691394 · doi:10.1002/cjce.24021

The influence of catalyst flow rate and superficial gas velocity on the modified two‐phase model for propylene polymerization in a gas‐phase fluidized bed reactor

2021· article· en· W3120691394 on OpenAlexvenueno aff
Mohd Farid Atan, M.A. Hussain, Ahmad Shamiri

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsnot available
Fundersnot available
KeywordsFluidized bedVolumetric flow rateSuperficial velocityMaterials sciencePolymerizationFlow (mathematics)ThermodynamicsMechanicsCatalysisChemical engineeringChemistryComposite materialOrganic chemistryEngineeringPolymerPhysics

Abstract

fetched live from OpenAlex

Abstract Olefin polymerization, especially of propylene in gas‐phase fluidized bed reactors, is increasingly prevalent because of its ability to handle the continuous process, among other advantages. The challenge for modelling this process is solving the high nonlinearity phenomena in such a system. This research studies the influence of catalyst flow rate and superficial gas velocity on the modified two‐phase model. The catalyst flow rates were set at 1 × 10 −4 , 2 × 10 −4 , and 3 × 10 −4 kg/s, while the superficial flow rates were set at 0.35, 0.5, and 0.65 m/s. Production rate, reactor temperature, and heat‐loss flow rate were found to be proportional to catalyst flow rate and inversely proportional to superficial gas velocity. Heat loss through the fluidized bed wall had an influence only on the reactor temperature. Finally, predicted reactor temperatures corresponded closely to the pilot plant data, with deviations smaller than 0.5%.

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)0.001
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 score0.390
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.215
Teacher spread0.203 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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