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Record W2041185995 · doi:10.1002/cjce.5450780603

Hydrodynamics and mass transfer in a pulsed packed column

2000· article· en· W2041185995 on OpenAlexvenueno aff
Jie Yu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersState Key Laboratory of Chemical Engineering
KeywordsRaschig ringMass transferPacked bedMaterials sciencePhase (matter)Analytical Chemistry (journal)ChromatographyKeroseneMass fractionChemistryThermodynamicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract The hydrodynamics and mass transfer characteristics of a pulsed packed column (PPC) filled with a stainless steel super mini ring (SMR), ceramic and stainless steel Raschig rings have been studied using a 30% tributyl phosphate‐kerosene (dispersed phase)/acetic acid/water (continuous phase) system. Experiments were performed in a 100 mm internal diameter column with 1.0 m height of packing. The mass transfer and axial mixing parameters were estimated simultaneously from the measured concentration profiles of two‐phase based on the backflow model. It was found that pulsation has great influence on hydrodynamics and mass transfer characteristics of PPC with the SMR. H oxp and H ox decrease significantly with pulsation, whereas flooding velocity decreases only slightly. Comparison among the three types of packing showed that the SMR has superior characteristics both in terms of capacity and mass transfer efficiency. The influence of mass transfer on characteristics of PPC was also studied. New empirical equations of characteristic velocity, H ox and H oxd were proposed and good agreement between calculated and experimental data was obtained.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.392

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 head0.003
GPT teacher head0.141
Teacher spread0.139 · 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 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

Citations25
Published2000
Admission routes1
Has abstractyes

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