MétaCan
Menu
Back to cohort
Record W2147765428 · doi:10.1002/cjce.20333

Gas holdup in a two‐phase reversed flow jet loop reactor

2010· article· en· W2147765428 on OpenAlexvenueno aff
Sameer M. Wagh, Kishore V. Koranne, R. B. Mankar, R.L. Sonolikar

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleVolumetric flow rateDraft tubeMechanicsAnnulus (botany)Flow (mathematics)Loop (graph theory)Jet (fluid)ChemistryThermodynamicsMaterials sciencePhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract Experimental investigations have been carried out in Reversed Flow Jet Loop Reactor (RFJLR) to study the influence of liquid flow rate, gas flow rate, immersion height of two‐fluid nozzle in reactor and nozzle diameter on gas holdup without circulation, that is, gas–liquid mixture in draft tube only ( E gd ) and gas holdup with circulation loop ( E g ). Also critical liquid flow rate required for transition from draft tube to circulation loop has been determined. Gas holdup was measured by isolation valve technique. Gas holdup in draft tube and circulation loop increased with increase in liquid flow rate and gas flow rate. It is observed that the increased flow rate is required for achieving a particular value of gas holdup with larger nozzle diameter. Nozzle at the top edge of draft tube have higher gas holdup as compared to other positions. It has been noted that, no significant recirculation of gas bubbles into the top of draft tube from annulus section has been observed till a particular liquid flow rate is reached. A plot of gas holdup with no circulation and with circulation mode determines minimum liquid flow rate required to achieve complete circulation loop. Critical liquid flow rate required to achieve complete circulation loop increases with increase in gas flow rate and is minimum at lowest immersion height of two‐fluid nozzle.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.508

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 integrity0.0000.001
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 head0.193
Teacher spread0.188 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicFluid Dynamics and MixingFrench-language works237,207