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Record W2320252079 · doi:10.1017/s0956792515000145

A Stefan model for mass transfer in a rotating disk reaction vessel

2015· article· en· W2320252079 on OpenAlexafffund
C. Sean Bohun

Bibliographic record

VenueEuropean Journal of Applied Mathematics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaKing Abdullah University of Science and Technology
KeywordsMass transferChemical reactionDecoupling (probability)Boundary layerStefan problemMechanicsThermodynamicsReaction–diffusion systemChemical equilibriumDiffusionAlgebraic numberPhysicsStatistical physicsBoundary (topology)ChemistryMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

In this paper, we focus on the process of mass transfer in the rotating disk apparatus formulated as a Stefan problem with consideration given to both the hydrodynamics of the process and the specific chemical reactions occurring in the bulk. The wide range in the reaction rates of the underlying chemistry allows for a natural decoupling of the problem into a simplified set of weakly coupled convective–reaction–diffusion equations for the slowly reacting chemical species and a set of algebraic relations for the species that react rapidly. An analysis of the chemical equilibrium conditions identifies an expansion parameter and a reduced model that remains valid for arbitrarily large times. Numerical solutions of the model are compared to an asymptotic analysis revealing three distinct time scales and chemical diffusion boundary layer that lies completely inside the hydrodynamic layer. Formulated as a Stefan problem, the model generalizes the work of Levich (Levich and Spalding (1962) Physicochemical hydrodynamics, vol. 689, Prentice-Hall Englewood Cliffs, NJ) and will help better understand the natural limitations of the rotating disk reaction vessel when consideration is made for the reacting chemical species.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.058
GPT teacher head0.251
Teacher spread0.192 · 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 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

Citations0
Published2015
Admission routes2
Has abstractyes

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Same venueEuropean Journal of Applied MathematicsSame topicnanoparticles nucleation surface interactionsFrench-language works237,207