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Record W2093664428 · doi:10.1002/masy.200651104

Hydrodynamics in a Gas‐Solids Fluidized Bed Using X‐Ray Fluoroscopy and Pressure Fluctuation Measurements

2006· article· en· W2093664428 on OpenAlexaff
Bangyou Wu, Zhengxing He, Apostolos Kantzas, C. T. Bellehumeur, Sergey Kryuchkov

Bibliographic record

VenueMacromolecular Symposia · 2006
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBubbleMaterials scienceFluidized bedParticle (ecology)Flow (mathematics)MechanicsFluoroscopyFluidizationTurbulenceThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract In this work, non‐intrusive techniques were used to characterize the hydrodynamics in a gas‐solids bubbling fluidized bed using polyethylene powder and glass beads of comparable mean diameter ( d p = 360 µm) but different density. X‐ray fluoroscopy measurements and pressure fluctuations were performed on a pseudo 2‐dimensional gas‐solids fluidized bed. Bubble properties were captured from X‐ray fluoroscopy measurements. Similarities and differences of flow behavior of the two particle systems were revealed from comparison of bubble properties. Bubble properities normally varied similary with operating conditions for the two particle systems, while bubble sizes for the glass beads system are larger than those for the polyethylene system. Wavelet analysis of pressure fluctuations was applied to investigate the gas and solids phase flow behavior. Multi‐scale flow behavior was extracted from the standard deviation of the decomposed coefficient series. Flow behavior due to particles and bubbles of different sizes were captured at different decomposition levels of pressure fluctuations, which is difficult to know from analysis of the original signal. Results extracted from X‐ray fluoroscopy and pressure fluctuation measurements were consistent, suggesting that conventional pressure fluctuation measurements can be effectively used for investigation of the bubbling behavior.

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 categoriesMeta-epidemiology (narrow)
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 score0.447
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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.

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

Citations2
Published2006
Admission routes1
Has abstractyes

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