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Record W2148108143 · doi:10.1002/nme.1101

Modelling heat transfer in two‐fluid interfacial flows

2004· article· en· W2148108143 on OpenAlexaff
Vala Mehdi-Nejad, J. Mostaghimi, S. Chandra

Bibliographic record

VenueInternational Journal for Numerical Methods in Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVolume of fluid methodMechanicsAdvectionHeat transferThermal diffusivityThermal conductivityFluid dynamicsThermodynamicsVortexDiffusionMomentum (technical analysis)Materials scienceChemistryPhysicsFlow (mathematics)

Abstract

fetched live from OpenAlex

Abstract This paper presents a method to calculate heat transfer across an interface separating immiscible fluids. A volume tracking method was used to model the simultaneous movement of mass, momentum and energy across cell boundaries. Both first‐ and second‐order methods were used to approximate temperature fields with sharp gradients that exist near the fluid–fluid interface. Temperature distributions around hot droplets surrounded by a colder fluid with uniform velocity were calculated and the magnitude of false diffusion identified. The effect of changing the thermal diffusivity of the surrounding fluid was studied. It was found that in most cases a second‐order approximation, such as the van Leer scheme, is sufficient for estimating advection temperatures. To demonstrate the capabilities of the model we modelled molten tin droplets falling in an oil bath. The development of vortices behind droplets was modelled and the effect of fluid re‐circulation and oil thermal conductivity on heat dissipation studied. Copyright © 2004 John Wiley & Sons, Ltd.

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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.368
Teacher spread0.341 · 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
GenreMethods

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

Citations12
Published2004
Admission routes1
Has abstractyes

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