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Record W1827776579 · doi:10.1002/cjce.22338

CFD simulation and experimental study on vapour splitter in packed Divided Wall Column

2015· article· en· W1827776579 on OpenAlexvenueno aff
Jiao Sun, Ge Huaqiang, Wenyi Chen, Nan Chen, Xiangwu Chen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSplitterComputational fluid dynamicsColumn (typography)MechanicsComputer simulationMaterials scienceSimulationComputer scienceMechanical engineeringOpticsEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract A Divided Wall Column (DWC) with an optimal vapour split offers much greater potential for energy savings compared to conventional column sequences. To realize the adjustment of the vapour split as well as uniform vapour distribution, a vapour splitter which had been applied for an invention patent was put forward. The effects on performance of adjusting the vapour split and gas nonuniformities under different factors were investigated using numerical simulation and experimental research. The simulation study was carried out using the Computational Fluid Dynamics (CFD) software STAR‐CCM+. The simulation results were compared with experimental data, and they showed close agreement with each other. All the results revealed that the device can flexibly adjust the vapour split and achieve a uniform vapour distribution.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.023
GPT teacher head0.238
Teacher spread0.216 · 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
Published2015
Admission routes1
Has abstractyes

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