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Record W4406940262 · doi:10.1016/j.powtec.2025.120714

Propagation and attenuation of surface waves and pressure waves in a fluidized bed with a vibrating plate

2025· article· en· W4406940262 on OpenAlexafffund
Eric Jia, Li Niu, Xiaotao Bi

Bibliographic record

VenuePowder Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsCanadian Nuclear LaboratoriesUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAttenuationMechanicsSurface waveWave propagationAcousticsGeologyMaterials sciencePhysicsOptics

Abstract

fetched live from OpenAlex

A fluidized bed with a surface wave generator was utilized to investigate pressure wave sources, propagation, and attenuation. The results indicated at least three distinct waves within the fluidized bed, i.e., surface waves originating from the movement of the bed surface, reflected surface waves from the wall, and the elastic waves resulting from the compression of the particulate phase in the vicinity of the plate. The attenuation rate is related to the intricate interplay of these pressure waves within the bed. Pressure waves propagate both horizontally and vertically within the bed. In the horizontal direction, surface waves are the dominant pressure waves at low frequencies, and the surface waves are no longer the dominant components of the pressure waves at high frequencies. The surface waves are not dominant in vertically propagating pressure waves. The vibrating plate impedes the transmission of the reflected wave in the vertical direction. • Origin, propagation and attenuation of pressure waves were studied. • Surface waves, reflected surface waves, and elastic waves were identified. • Surface waves are not always dominant pressure waves in fluidized beds. • Pressure waves propagate and get attenuated in all directions.

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 score0.053
Threshold uncertainty score0.352

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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