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Record W2071172641 · doi:10.1002/cjce.21837

Numerical evaluation of a one‐dimensional two‐fluid model applied to gas–solid cold‐flows in fluidised beds

2013· article· en· W2071172641 on OpenAlexvenueno aff
Jannike Solsvik, Zhongxi Chao, Hugo A. Jakobsen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsnot available
Fundersnot available
KeywordsDragClosure (psychology)MechanicsComputational fluid dynamicsFlow (mathematics)Computer simulationCombustionProcess (computing)MethaneTwo-fluid modelComputer scienceProcess engineeringEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Computational demanding two‐ and three‐dimensional two‐fluid models are frequently adopted simulating gas–solid flows in fluidised beds. Reduced computational cost is favourable for efficient numerical studies of technologies such as the novel chemical looping combustion (CLC), chemical looping reforming (CLR), and sorption‐enhanced steam methane reforming (SE‐SMR) processes. In this study, we elucidate the potential of a one‐dimensional two‐fluid model to describe gas–solid cold‐flows in fluidised beds. The validity of the numerical simulation results of the bubbling beds and risers have been compared to experimental data in the literature. Moreover, sensitivity analyses on drag closure laws and operation condition have been performed and a number of model solution techniques and algorithms are studied. In addition, simulation results of the one‐dimensional model are compared to results of a two‐dimensional model. For particular sets of operating conditions and flow characteristics, the one‐dimensional model compares fairly well to the simulation results of the two‐dimensional model and to experimental data. Under other operating conditions, large quantitative deviations can be observed. However, the one‐dimensional model is assumed to be sufficently accurate for particular reactor process optimisation and design evaluations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.049
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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 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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicChemical Looping and Thermochemical ProcessesFrench-language works237,207