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Record W2141652170 · doi:10.1002/cjce.20338

Intensified operation of slurry bubble columns using structured gas injection

2010· article· en· W2141652170 on OpenAlexvenueno aff
Nasim Hooshyar, P.J. Hamersma, R.F. Mudde, J. Ruud van Ommen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsSpargingBubbleSlurryFraction (chemistry)MechanicsMaterials scienceHomogeneousSecondary air injectionChromatographyChemistryAnalytical Chemistry (journal)ThermodynamicsComposite materialPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract We investigate uniform gas injection using a needle sparger as a structuring methodology to reduce backmixing in slurry bubble columns. Using optical probes, we determined the gas fraction and the bubble behaviour in 2D and 3D slurry bubble columns with a uniform gas injection. Experimental results for air–water–glass beads ( d s = 108 µm, U sg = 0–0.10 m/s) indicate that a strong reduction in the vortical structures has been achieved and the homogeneous flow regime can be extended beyond 30% gas fraction. Increasing the solids concentration decreases the gas fraction and widens the bubble velocity distribution. Furthermore, we show by modelling that the reduced backmixing leads to a major improvement of the conversion in case of Fischer–Tropsch synthesis.

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 score0.446
Threshold uncertainty score0.335

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 head0.005
GPT teacher head0.172
Teacher spread0.166 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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