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Record W2134175281 · doi:10.1002/pen.21433

Numerical investigation and experimental validation of the performance of a tubular packed bed reactor for hydrogenation of diene‐based polymers

2009· article· en· W2134175281 on OpenAlexafffund
Chandra Mouli R. Madhuranthakam, Qinmin Pan, Garry L. Rempel

Bibliographic record

VenuePolymer Engineering and Science · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePacked bedPlug flow reactor modelPlug flowContinuous stirred-tank reactorIsothermal processNatural rubberPolymerMass transferIsobaric processChemical engineeringThermodynamicsComposite material

Abstract

fetched live from OpenAlex

Abstract A process which comprised a tubular reactor (that can be packed with different internal structures) has been modeled and theoretically analyzed for conducting the hydrogenation of nitrile butadiene rubber (NBR). The dynamics of the tubular reactor and the intrinsic hydrogenation kinetics are coupled, and detailed numerical simulations are performed under isothermal and isobaric conditions. The proposed model thus obtained involves coupled, nonlinear, partial differential equations (distributed parameter system). The effect of different reactor design parameters such as Peclet number, carbon–carbon double bond loading, mass transfer to reaction resistance, and solubility of hydrogen with respect to hydrogenation of the NBR has been investigated numerically. The conversions predicted using the proposed model for tubular packed bed reactor are compared with those possible in conventional plug flow reactor and continuous stirred tank reactor models. The optimal parameters and operating conditions for efficient production of hydrogenated NBR are suggested. Finally, the validity of the proposed model is confirmed by comparing the predicted and the experimental degree of hydrogenation obtained in a tubular reactor packed with Intalox saddles. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers

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 score0.434
Threshold uncertainty score0.213

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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

Citations1
Published2009
Admission routes2
Has abstractyes

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