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Record W2526653943 · doi:10.1002/cjce.22696

CFD analysis of flow regimes in airlift reactor using Eulerian‐Lagrangian approach

2016· article· en· W2526653943 on OpenAlexvenueno aff
Sanjay B. Pawar

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersNational Environmental Engineering Research InstituteDepartment of Science and Technology, Government of KeralaDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsMechanicsSpargingTurbulenceBubbleComputational fluid dynamicsAirliftLagrangian particle trackingSauter mean diameterFlow (mathematics)BuoyancyParticle (ecology)Materials sciencePhysicsThermodynamicsChemistryNozzleGeologyBioreactor

Abstract

fetched live from OpenAlex

Abstract The hydrodynamic aspects of the concentric tube airlift reactor have been studied using two‐phase CFD simulations with a Eulerian ‐ Lagrangian approach. The three‐dimensional CFD simulations are carried out with the experimental geometry of airlift reactor (H/D = 12) reported in the published literature. The standard k ‐ ϵ turbulence model is used with additional consideration of production and dissipation of buoyancy‐induced turbulence. Two different bubble size distributions (BSDs) and their Sauter mean diameters have been considered to represent the gas distribution at sparger in the reactor. This study shows that the BSD1 (1 – 5 – 10 mm) containing a high fraction of small bubbles (≤ 5 mm) represents the hydrodynamics of flows appropriately as compared to the BSD2 (5 – 10 – 15 mm) containing a high fraction of large bubbles (≥ 10 mm) or the single size bubble diameters (5.25 mm and 10 mm). Further, three regimes of operation such as no gas bubbles in the downcomer (regime I), stationary gas bubbles in the downcomer (regime II), and gas bubble recirculation from the downcomer section to the riser section (regime III), are verified using CFD simulations with Lagrangian particle tracking. Satisfactory agreement (within 15 % deviation) with the experimental data was observed for parameters such as the gas holdups in the riser and downcomer and the liquid circulation velocity in the flow regimes I and II for BSD1.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.172
Teacher spread0.165 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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