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Record W1978716904 · doi:10.1002/cjce.5450780304

Hydrodynamic behaviour of a magneto airlift column in a transverse magnetic field

2000· article· en· W1978716904 on OpenAlexvenueno aff
Zakaria Al‐Qodah

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetic fieldFluidizationIntensity (physics)Fluidized bedSolenoidMechanicsAirliftMagnetic pressureMaterials scienceHysteresisNuclear magnetic resonanceCondensed matter physicsMagnetizationChemistryOpticsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract The hydrodynamics of a three‐phase airlift reactor of magnetic particles has been investigated in the presence of a transverse magnetic field. Experiments were carried out in two modes: applying the magnetic field to a static bed then increasing the field flow, and applying the magnetic field to a fluidized bed then increasing the magnetic field intensity. In magnetizing the first mode and parallel to the increasing gas superficial velocity, several bed regimes were observed, including: initial packed, stabilized, and fluidized beds. On the other hand, in magnetizing last mode and while increasing the magnetic field intensity, the fluidized bed changes from a fluidized to a stabilized to frozen bed. Bed expansion before the onset of fluidization increases as the magnetic field intensity increases. Minimum fluidization velocity was found to be strongly dependent on the magnetic field intensity and the minimum stabilization intensity was also strongly dependent on the gas velocity. The magnetic field intensity also affects the bed expansion hysteresis and the liquid circulation velocity. A photocell was used to measure the water circulation rate in the downcomer of the reactor.

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 score0.109
Threshold uncertainty score0.451

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 head0.002
GPT teacher head0.148
Teacher spread0.145 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

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