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Record W4393321364 · doi:10.1016/j.ces.2024.120048

Identifying dominant flow structures in a bubbling gas-particle fluidized bed using the spectral proper orthogonal decomposition

2024· article· en· W4393321364 on OpenAlexafffund
Mohsen Zarepour, Donald J. Bergstrom, Raymond J. Spiteri

Bibliographic record

VenueChemical Engineering Science · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlow (mathematics)MechanicsFluidizationParticle (ecology)Volume fractionVolume (thermodynamics)MathematicsFluidized bedPhysicsThermodynamicsGeology

Abstract

fetched live from OpenAlex

This study applies the spectral proper orthogonal decomposition (SPOD) to analyze the spatio-temporal characteristics associated with the flow fields of a bubbling fluidized bed. The results suggest there is no singular dominant frequency linked to the highest energy levels; rather, there is a spectrum of frequencies. These frequencies are consistent with the natural frequency from published correlations. SPOD analysis allows for the capture of quasi-periodicity associated with the flow that arises from the semi-periodic evolution of bubbles in the bed and reveals the presence of multiple co-existing spatio-temporal patterns in the particle volume fraction and velocity fields. The dominant SPOD modes can be used for prediction, control, design, optimization, and reduced-order system representation. The capability of a few dominant modes to yield a low-rank reconstruction of the flow fields is demonstrated. The intermittent behavior of the bed is examined through frequency-time analysis of the gas pressure field.

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 score0.259
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.244
Teacher spread0.234 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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