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Record W4294142494 · doi:10.1002/cjce.24629

Effect of resistance internal on hydrodynamic behaviours and bubble characteristics in a laboratory‐scale bubble column

2022· article· en· W4294142494 on OpenAlexvenueno aff
Jiashu Qian, Youqing Wu, Sheng Huang, Shiyong Wu, Haiqi Wang, Jinsheng Gao

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsBubbleSauter mean diameterMaterials scienceMechanicsBreakupWork (physics)Environmental scienceThermodynamicsPhysicsNozzle

Abstract

fetched live from OpenAlex

Abstract A novel resistance internal is proposed to optimize the flow field and improve the gas–liquid contact in a co‐hydrogenation reactor of coal and vacuum residuum. Local gas holdup, local liquid velocity, and characteristics of the bubble were investigated in a scaled‐down laboratory model. The quantitative results showed that the resistance internals could reduce the thickness of the liquid reflux layer by a percentage up to 32% and reduce the difference in the local gas holdup at cross‐sections of up to 44%. The Sauter mean diameter of the bubble decreased from 20.30 to 16.00 mm, which aroused the increase in bubble surface area by a percentage of up to 71.9%. The resistance internal promoted the breakup of the bubble with multiple mechanisms and provided diversion to fluid. In this work, improvement at multiple scales was realized, and the technical support for industrial application was provided.

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 score0.390
Threshold uncertainty score0.452

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 head0.002
GPT teacher head0.159
Teacher spread0.158 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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