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Record W2737067463 · doi:10.1002/cjce.22943

Effect of aeration mode on the performance of center‐ and annulus‐rising internal‐loop airlift bioreactors

2017· article· en· W2737067463 on OpenAlexvenueno aff
Mei Han, Арто Лаари, Tuomas Koiranen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersTekes
KeywordsAirliftAerationBioreactorDraft tubeAnnulus (botany)MechanicsMaterials scienceShear (geology)Mass transferChemistryPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract Extensive experimental studies on internal‐loop airlift reactors, including center‐rising (CR‐ALR) and annulus‐rising airlift reactors (AR‐ALR), have been reported in the literature. However, to the best of the authors’ knowledge, the effects of the aeration mode on the local hydrodynamics remain an under‐investigated area, especially for complex culture media. At present, it is difficult to select the best aeration mode for ALRs due to limited understanding of the pros and cons of the different modes. This study presents a detailed quantitative investigation of the overall gas holdup, local liquid velocity, liquid circulation time, shear rate distribution, and volumetric mass transfer coefficient in center‐ and annulus‐rising airlift bioreactors to better understand the effect of aeration mode on airlift bioreactor performance. Particle image velocimetry is employed to conduct local measurements. The results show that the overall gas holdup, liquid circulation time, and volumetric mass transfer coefficient are larger in the AR‐ALR than in the CR‐ALR. The local liquid velocity circulating into the downcomer of the AR‐ALR, which contributes to bubble entrainment and therefore to overall gas holdup, is higher than in the CR‐ALR. It was observed that a large circulation loop formed in the CR‐ALR, whereas two counter‐looping circulation cells appeared in the AR‐ALR. It was also found that the shear rate field was more uniform in the AR‐ALR than the CR‐ALR although the shear rates were similar in magnitude.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.252

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 integrity0.0000.000
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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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