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Record W2883383462 · doi:10.1002/cjce.23299

Effect of vertical internals on the pressure drop in a gas‐solid fluidized bed

2018· article· en· W2883383462 on OpenAlexvenueno aff
Haidar Taofeeq, Muthanna H. Al‐Dahhan

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsnot available
Fundersnot available
KeywordsPressure dropFluidized bedDrop (telecommunication)Materials scienceMechanicsDifferential pressureDimensionless quantityFluidizationComposite materialPressure sensorChemistryMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract In this work, the pressure drop at the wall and the radial profiles of pressure drop along the bed height have been measured using a differential pressure transducer and pressure probe‐differential pressure transducer in a gas‐solid fluidized bed with a 0.14 m inside diameter. Two types of circular arrangements of intense vertical internals (0.0254 and 0.0127 m diameter), two kinds of solid particles of Geldart B type (glass beads and aluminum oxide), and four selected superficial gas velocities in terms of u/u mf have been used to study the impact of these different designs, as well as the physical and operating variables on the pressure drop measured at the wall of the bed and the radial pressure drop inside the fluidized bed. It has been experimentally demonstrated that the 0.0254 m internals can reduce the pressure drop at the wall and the radial pressure drop inside the bed by about 10 % when compared to without internals, and this result holds true for both kinds of solids used. However, the implementation of 0.0127 m internals inside the gas‐solid fluidized bed leads to a decrease in the pressure drop and radial pressure drop in the case of glass bead solid particles and an increase in the pressure drop in the case of aluminum oxide solid particles. The experimental results in the form of relevant dimensionless groups have been correlated using the statistical analysis software of JMP 12, due to the big difference between the experimental results of this work and the predicted values from the available correlations in the literature. The new correlation has been developed with a mean relative deviation value of 1.08 % between the experimental and predicted values.

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)0.001
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 score0.032
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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