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Record W1981233807 · doi:10.5539/mas.v4n9p110

Prediction of Gas Holdup in a Three-Phase Internal Loop Airlift Fluidized Bed Reactor Using Newtonian and non-Newtonian Liquids

2010· article· en· W1981233807 on OpenAlexvenueno aff
Akilamudhan Palaniappan, Kannan Kandasamy

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsNon-Newtonian fluidAirliftNewtonian fluidMaterials scienceDraft tubeChromatographyFluidized bedThermodynamicsSpargingMechanicsAnalytical Chemistry (journal)ChemistryPhysicsBioreactor

Abstract

fetched live from OpenAlex

The effect of superficial gas and liquid velocities, particle diameter and sphericity, physical and rheological properties of liquids on gas holdup were studied in a three phase internal loop airlift fluidized bed reactor. Air was used as a gas phase. Water, n-butanol, various concentrations of glycerol (60% and 80%) were used as Newtonian liquids and different concentrations (0.25%, 0.6% and 1.0%) of carboxy methyl cellulose (CMC) solutions were used as non-Newtonian liquids. Spheres, Bearl saddle and Rasich ring with different diameters were used as solid phases. Superficial gas velocity varied from 0.000142 m/s to 0.005662 m/s and superficial liquid velocity varied from 0.001 to 0.12 m/s. The experimental result shows that increase in particle size and superficial gas velocity increases gas holdup and decreases with increase in concentration of Newtonian and non-Newtonian systems. Based on the experimental results a separate correlation was developed to predict gas holdup for both Newtonian and non-Newtonian liquids for wide range of operating conditions.

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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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