MétaCan
Menu
Back to cohort
Record W2378550605

NONLINEAR ANALYSIS OF GAS-SOLID FLOW BEHAVIOR IN FAST FLUIDIZED BED RISER

2004· article· en· W2378550605 on OpenAlexaff
Weixing Huang, Jesse Zhu

Bibliographic record

VenueJournal of Chemical Industry and Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsWestern University
Fundersnot available
KeywordsTurbulenceMechanicsNonlinear systemAnnulus (botany)Volumetric flow rateEntropy (arrow of time)Fluidized bed combustionThermodynamicsMaterials sciencePhysicsChemistryFluidized bed
DOInot available

Abstract

fetched live from OpenAlex

A fast fluidized bed riser with 16m height and 0.10m ID was operated with FCC particles and in a wide range of operating conditions.The superficial gas velocity U g ranged from 3.5m·s -1 to 8.1m·s -1, and the solids circulating rate G s was from 50kg·m -2·s -1 to 201kg·m -2·s -1.Time series signals of solids holdup fluctuation were measured at a frequency of 900Hz using an optical fiber located at 8 axial and 11 radial positions.The nonlinear method was used to analyze the time series and consequently Kolmogorov entropy was calculated to describe the dynamic characteristics of the gas-solid flow behavior in the annular-core section. The results showed that Kolmogorov entropy could describe the annular-core flow structure. According to three marked characteristics of Kolmogorov entropy in the radial direction, three flow regions were identified:random-particles-controlled core region, chaotic-particles-controlled transitional region, wall-controlled annulus region.The change of Kolmogorov entropy in the radial direction was also interpreted based on the influence of solids on gas turbulence structures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.224
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Chemical Industry and EngineeringSame topicGranular flow and fluidized bedsFrench-language works237,207