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Record W2329632241 · doi:10.1021/ie3010176

Modeling Coke Distribution above the Freeboard of a FLUID COKING Reactor

2012· article· en· W2329632241 on OpenAlexaff
Christopher B. Solnordal, Kevin Reid, Larry P. Hackman, Ray Cocco, John G. Findlay

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2012
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsSyncrude (Canada)
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsFreeboardCokeComputational fluid dynamicsParticle (ecology)MechanicsMaterials scienceCoker unitWork (physics)Environmental scienceNuclear engineeringWaste managementThermodynamicsFluidized bedEngineeringPhysicsMetallurgy

Abstract

fetched live from OpenAlex

In a FLUID COKING unit, reactor cyclone fouling by coke deposits can set the run length of the unit. Over time the coke deposits can grow and obstruct the cyclone which will limit throughput and lead to a shutdown. For this reason, producing a more uniform coke distribution pattern within the reactor horn chamber may lead to an increased interval between turnarounds. An existing pilot-scale experimental model of the coker reactor freeboard, horn chamber, and exit cyclones allows determination of coke distribution to the cyclones, but provides limited understanding of the underlying fluid dynamics within the system. In this work a two-phase computational fluid dynamics (CFD) model of this experimental rig was developed. Coke was modeled as an Eulerian stream of solid particles with monodisperse particle diameter. It was found that predicted coke distributions were sensitive to the choice of coke diameter, but a suitable choice gave good agreement with experimental observations. In the current work this value was 167 μm which was substantially higher than the value of the Sauter mean diameter of 139 μm. It was found that the CFD model could quantitatively predict coke distributions in the freeboard region of a FLUID COKING reactor experimental rig, while providing insight into the flow dynamics. When modeling the particle size distribution with a monodisperse particle diameter, comparison with experimental results is necessary to identify the coke particle diameter that leads to optimal model performance.

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 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)0.002
metaresearch head score (Gemma)0.001
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 score0.206
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.079
GPT teacher head0.291
Teacher spread0.212 · 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 teacher head, not a consensus.

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

Citations6
Published2012
Admission routes1
Has abstractyes

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