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Record W2082185341 · doi:10.1002/aic.14337

Distribution of large biomass particles in a sand‐biomass fluidized bed: Experiments and modeling

2013· article· en· W2082185341 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIChE Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcGill UniversityPolytechnique Montréal
Fundersnot available
KeywordsFluidizationBiomass (ecology)TRACERFluidized bedPressure dropParticle (ecology)Volume (thermodynamics)Mixing (physics)Fraction (chemistry)Environmental scienceMechanicsChemistryGeologyChromatographyThermodynamicsNuclear physicsPhysics

Abstract

fetched live from OpenAlex

The axial distribution of large biomass particles in bubbling fluidized beds comprised of sand and biomass is investigated in this study. The global and local pressure drop profiles are analyzed in mixtures fluidized at superficial gas velocities ranging from 0.2 to 1 m/s. In addition, the radioactive particle tracking technique is used to track the trajectory of a tracer mimicking the behavior of biomass particles in systems consisting of 2, 8, and 16% of biomass mass ratio. The effects of superficial gas velocity and the mixture composition on the mixing/segregation of the bed components are explored by analyzing the circulatory motion of the active tracer. Contrary to low fluidization velocity (U = 0.36 m/s), biomass circulation and distribution are enhanced at U = 0.64 m/s with increasing the load of biomass particles. The axial profile of volume fraction of biomass along the bed is modeled on the basis of the experimental findings. © 2014 American Institute of Chemical Engineers AIChE J , 60: 869–880, 2014

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.

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 score0.232
Threshold uncertainty score0.418

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 head0.016
GPT teacher head0.247
Teacher spread0.230 · 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