MétaCan
Menu
Back to cohort
Record W1987036449 · doi:10.1002/cjce.20618

A hydrodynamic model of a circulating fluidised bed with low‐density particles

2011· article· en· W1987036449 on OpenAlexaffvenueabout
Qi Miao, Jesse Zhu, Shahzad Barghi, Chuangzhi Wu, Xiuli Yin, Zhaoqiu Zhou

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsWestern University
Fundersnot available
KeywordsSawdustMechanicsMaterials scienceMeasure (data warehouse)Wood gas generatorEnvironmental scienceChemistryEngineeringPhysicsWaste managementCoal

Abstract

fetched live from OpenAlex

Abstract In this study, a two‐dimensional mathematical model was developed considering the hydrodynamic behaviour of a circulating fluidised bed biomass gasifier (CFBBG), which is also applicable for other low‐density particles. In the modelling, the CFB riser was divided into two regions: a dense region at the bottom and a dilute region at the top of the riser. Kunii and Levenspiel's [Kunii and Levenspiel, Powder Technol. 61, 193‐206 (1990)] model was adopted to express the vertical solids distribution with some other assumptions. Radial distributions of bed voidage were taken into account in the upper zone by using Zhang et al.'s [Zhang et al., Chem. Eng. Sci. 46(12), 3045‐3052 (1991)] correlation. For model validation purposes, a cold model CFB was employed, in which sawdust was transported with air as the fluidising agent. The column is 10 m in height and 280 mm in diameter, and is equipped with pressure transducers to measure axial pressure profile and with a reflective optical fibre probe to measure local solids holdup. A satisfactory agreement between the model predictions and experimental data was found. © 2011 Canadian Society for Chemical Engineering

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.152
Teacher spread0.142 · 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

Citations8
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicGranular flow and fluidized bedsFrench-language works237,207