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Record W2163863799 · doi:10.1002/ceat.201300163

Catalytic Ozone Decomposition in a Gas‐Solids Circulating Fluidized‐Bed Riser

2014· article· en· W2163863799 on OpenAlex
Lei Kong, Jesse Zhu, Chao Zhang

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

VenueChemical Engineering & Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsWestern University
Fundersnot available
KeywordsFluid catalytic crackingComputational fluid dynamicsCatalysisFluidized bed combustionReaction rateFluidized bedDecompositionParticle (ecology)ThermodynamicsChemistryMechanicsMaterials scienceChemical engineeringEngineeringPhysicsOrganic chemistryGeology

Abstract

fetched live from OpenAlex

Abstract Computational fluid dynamics (CFD) modeling of the catalytic ozone decomposition reaction in a circulating fluidized‐bed (CFB) riser, using iron‐impregnated fluid catalytic cracking particles as catalyst, is carried out. The catalytic reaction is defined as a one‐step reaction, and the reaction equation is modified by with respect to the particle surface area, A p , and an empirical coefficient. The Eularian‐Eularian method with the kinetic theory of granular flow is used to solve the gas‐solids two‐phase flow in the CFB riser. The simulation results are compared with experimental data, and the reaction rate is modified by using an empirical coefficient, to provide better simulation results than the original reaction rate. Moreover, the particle size has great effects on the reaction rate. The generality of the CFD model is further validated under different operating conditions of the riser.

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 categoriesMeta-epidemiology (narrow)
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 score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.190
Teacher spread0.187 · 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