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Record W2000163563 · doi:10.5539/mas.v4n8p75

Prediction of Riser Gas Holdup in Three- Phase External Loop Air Lift Fluidized Bed Reactor

2010· article· en· W2000163563 on OpenAlexvenueno aff
Kannan Kandasamy, Akilamudhan Palaniappan

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsDraft tubeAirliftMechanicsMaterials scienceFluidized bedNewtonian fluidNon-Newtonian fluidFluidizationFlow (mathematics)ThermodynamicsChemistryPhysicsBioreactor

Abstract

fetched live from OpenAlex

Hydrodynamics is an important issue for design and development of three phase external-loop airlift fluidized bed. This paper deals on the experimental investigations on the effect of superficial gas and liquid velocities and properties of solids on the riser gas holdup of a three phase external-loop airlift fluidized bed reactor and it was characterized using Newtonian and non Newtonian systems. Water, 65% and 85% of glycerol and n-butanol were used as Newtonian liquids and different concentration of Carboxyl Methyl Cellulose (CMC) i.e., 0.2%, 0.5% and 1% were used as non Newtonian liquids. Spherical glass beads, bearl saddles and rasching rings of different sizes were used as solid phase. The phase flow rates and properties of solid particle had significant effect on the hydrodynamic characteristics of the external-loop airlift fluidized bed reactor such as riser gas holdup. Unified correlations have been developed to estimate the riser gas holdup as a function of superficial phase velocities, properties of solid particle and physical properties of both Newtonian and Non-Newtonian liquid systems. The predicting ability of the correlations were tested with the experimental data and found to be good fit with an absolute average relative error (AARD) of ± 9.7 % for riser gas holdup.

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)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.221
Teacher spread0.208 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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