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Record W1974386702 · doi:10.1002/cjce.5450820507

Strategies for Starting Up Azeotropic Distillation Columns with Multiple Steady States

2004· article· en· W1974386702 on OpenAlexvenueno aff
S.J. Benz, Javier A. Francesconi, Nicolás J. Scenna

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsnot available
FundersUniversidad Tecnológica Nacional
KeywordsOperabilityAzeotropic distillationPartition (number theory)DistillationProcess (computing)Computer scienceThermodynamicsControl theory (sociology)MechanicsMathematicsProcess engineeringChemistryEngineeringPhysicsChromatographyControl (management)

Abstract

fetched live from OpenAlex

Abstract The operability of azeotropic distillation columns with multiplicity is analysed during start‐up by dynamic simulation. Different steady states can be reached by applying different start‐up configurations and/or policies. The well‐known benzene‐heptane‐acetone (BHA) system is studied. The process by which the column reaches these steady states can be seen through the examination of profile evolutions corresponding to the given start‐up policies. Indeed, a clear partition of the start‐up policies space yielding different solutions is achieved. Some properties of this space are explained and start‐up critical values can be identified. Finally, some guidelines for start‐up supervision are outlined for the study case.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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