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Record W2062012811 · doi:10.2202/1542-6580.1108

Analysis of the Microscopic Flow Structure of a CFB Downer Reactor Using Solids Concentration Signals

2003· article· en· W2062012811 on OpenAlexfundno aff
Samwel Victor Manyele, Jesse Zhu, Hui Zhang

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2003
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Dar es Salaam
KeywordsVolumetric flow rateSauter mean diameterFlux (metallurgy)Analytical Chemistry (journal)Materials scienceMechanicsChemistryChromatographyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

The microflow structure in a downer reactor was studied by measuring the solids concentration fluctuations at various elevations and radial positions, using an optical fiber probe, at a sampling rate of 970 Hz. The downer reactor (0.1 m i.d. and 10 m high) was operated at gas velocities ranging from 3.5 to 10.0 m/s and solids flux from 50 to 200 kg/m2s, with spent FCC catalyst of Sauter mean diameter of 67 mm and density of 1500 kg/m3. The analysis of solids concentration time series was performed using statistical, spectral and chaos techniques. Results from these analyses were compared and related to the operating conditions (gas velocity and solids circulation rate) as well as to the spatial locations (radial and axial positions) in the downer reactor. Different techniques of time series analysis gave similar results but with different sensitivity to changes in the dynamics. A combination of the three signal analysis techniques proved to be more useful in providing more insight understanding of the microflow structure.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.264
Teacher spread0.255 · 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 designObservational
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

Citations18
Published2003
Admission routes1
Has abstractyes

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