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Record W2342941251 · doi:10.1021/acs.iecr.5b03219

Semicontinuous Distillation of Quintenary and N-ary Mixtures

2015· article· en· W2342941251 on OpenAlexaff
Kushlani Wijesekera, Thomas A. Adams

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDistillationSeparation processContinuous distillationComponent (thermodynamics)Process (computing)Fractionating columnSeparation (statistics)Process engineeringExtractive distillationFractional distillationWork (physics)MathematicsComputer scienceChromatographyChemistryThermodynamicsEngineeringStatisticsPhysics

Abstract

fetched live from OpenAlex

This work examines the feasibility of the separation of a five-component mixture using a semicontinuous distillation process. The results are used to generalize semicontinuous separation to N-component mixtures. The proposed five-component separation system, called quintenary semicontinuous separation, requires just a single distillation column with three middle vessels. In contrast, a conventional continuous distillation process would require four columns to achieve the same separation objectives. This process is an extension of three- and four-component semicontinuous separation. These processes are more economical at intermediate throughputs when compared to traditional continuous separations processes as has been demonstrated in previous literature. The feasibility of the process and profitability compared to a conventional continuous process was demonstrated using a mixture of n -alkanes from C6–C10. Dynamic simulation results show that this system is able to remain within safe operating limits. An economic comparison between the continuous and semicontinuous processes shows that the semicontinuous separation process is economically favorable at intermediate flow rates.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.303
Teacher spread0.211 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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