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Record W3132561464 · doi:10.1002/cjce.24070

Modelling and validation of a gas‐solid fluidized bed using advanced measurement techniques

2021· article· en· W3132561464 on OpenAlexvenueno aff
Sebastián Uribe, Haidar Taofeeq, Muthanna H. Al‐Dahhan

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsnot available
Fundersnot available
KeywordsPressure dropFluidized bedDimensionless quantityMechanicsComputational fluid dynamicsFluidizationSolid mechanicsMaterials scienceMultiphase flowRangingInletCFD-DEMThermodynamicsMechanical engineeringEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract With a Euler‐two‐phase (E2P) approach, through computational fluid dynamics (CFD) techniques, a mathematical model for the prediction of the local hydrodynamic behaviour of a gas‐solid fluidized bed was implemented. Simulations are conducted for a fluidized bed of 0.14 m internal diameter packed with Gerdart B glass beads particles, with an average diameter of 365 μm, at dimensionless inlet velocities ranging from . The implemented model considers the multiphase and multiscale interactions through the inclusion of three sub‐models, which allows the model to have a broad range of applicability. Predictions were compared against experimental measurements reported on previous contributions for validation purposes. The experimental study was conducted by implementing advanced measurement techniques, such as a differential pressure transducer, and an optical fibre probe for simultaneous measurement of solids holdup and velocity, developed at the Multiphase Flow and Reactors Engineering and Applications Laboratory (mFReal). Local radial solids holdup, solids velocity, and pressure drop profiles were experimentally determined. Results show that the implemented model possesses a high predictive quality, predicting pressure drops with an average absolute relative error (AARE) between 8.6%–11.3%; solids holdup with a root mean squared deviation (RMSD) under 5%; and solids velocity with a RMSD under 22%.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.417

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 head0.019
GPT teacher head0.203
Teacher spread0.184 · 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 designBench or experimental
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

Citations7
Published2021
Admission routes1
Has abstractyes

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