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Record W2165706359 · doi:10.1002/cjce.20240

Hydrodynamic characteristics of gas–solid fluidization at high temperature

2010· article· en· W2165706359 on OpenAlexaffvenue
Shabnam Sanaei, Navid Mostoufi, Ramin Radmanesh, Rahmat Sotudeh‐Gharebagh, Christophe Guy, Jamal Chaouki

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsPolytechnique MontréalDuPont (Canada)
Fundersnot available
KeywordsBubbleThermal diffusivityEmulsionMixing (physics)FluidizationMaterials scienceParticle (ecology)Temperature jumpSurface tensionThermodynamicsFluidized bedMechanicsWork (physics)ChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Effect of temperature on the hydrodynamics of bubbling gas–solid fluidized beds was investigated in this work. Experiments were carried out at different temperatures ranged of 25–600°C and different superficial gas velocities in the range of 0.17–0.78 m/s with sand particles. The time‐position trajectory of particles was obtained by the radioactive particle tracking technique at elevated temperature. These data were used for determination of some hydrodynamic parameters (mean velocity of upward and downward‐moving particles, jump frequency, cycle frequency, and axial/radial diffusivities) which are representative to solids mixing through the bed. It was shown that solids mixing and diffusivity of particles increases by increasing temperature up to around 300°C. However, these parameters decrease by further increasing the temperature to higher than 300°C. This could be attributed to the properties of bubble and emulsion phases. Results of this study indicated that the bubbles grow up to a maximum diameter by increasing the temperature up to 300°C, after which the bubbles become smaller. The results showed that due to the wall effect, there is no significant change in the mean velocity of downward‐moving clusters. In order to explain these trends, surface tension of emulsion between the rising bubble and the emulsion phase was introduced and evaluated in the bubbling fluidized bed. The results showed that surface tension between bubble and emulsion is increased by increasing temperature up to 300°C, however, after that it acts in oppositely.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.460

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 head0.153
Teacher spread0.151 · 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

Citations20
Published2010
Admission routes2
Has abstractyes

Explore more

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