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Record W2304989410 · doi:10.1115/1.4032732

A New Subgrid Model for the Heat and Mass Transfer Between a Hot Gas and Char Particles in Dense-Bed Reactors

2016· article· en· W2304989410 on OpenAlexaff
S. Schulze, Petr A. Nikrityuk

Bibliographic record

VenueJournal of Energy Resources Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Alberta
FundersEuropean Regional Development FundFederalno Ministarstvo Obrazovanja i Nauke
KeywordsCharMass transferParticle (ecology)Heat transferMechanicsWork (physics)PorosityVolume (thermodynamics)Flue gasFluidized bedComputational fluid dynamicsMaterials scienceControl volumeThermodynamicsReynolds numberChemistryCombustionPhysicsTurbulenceGeologyComposite material

Abstract

fetched live from OpenAlex

This work is devoted to the development and verification of a new intrinsic-based subgrid model for moving char particles gasifying in a hot flue gas or syngas environments consisting of CO2/H2O/CO species. The distinguishing feature of our model relative to the submodels published in the literature is that it takes into account the thermal and chemical nonequilibrium between the particle's surface and its center. Thus, our model is able to predict temperature and species gradients inside the particles. The main focus of the new submodel is to demonstrate the crucial role of intrinsic-based heterogeneous reactions in the adequate prediction of carbon conversion rates for char particles gasification in fixed-bed and fluidized-bed gasifiers. The new model is verified against steady-state, particle-resolved computational fluid dynamics (CFD)-based, three-dimensional simulations carried out for different volume fractions of solid phase in a control volume (CV). Acceptable agreement has been demonstrated. Finally, to demonstrate our new model's predictions, we carried out several unsteady simulations for different ambient temperatures and Reynolds numbers. The importance of simultaneous change of char porosity and particles size during gasification has been demonstrated for different regimes indicated by the Damköhler numbers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.294

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 head0.011
GPT teacher head0.198
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

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
Published2016
Admission routes1
Has abstractyes

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