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Record W4387087853 · doi:10.1115/ht2023-106961

Transient Thermal Spreading From a Circular Heat Source in Polygonal Flux Channels

2023· article· en· W4387087853 on OpenAlexaff
Sahar Goudarzi, Lisa Steigerwalt Lam, Yuri S. Muzychka, G.F. Naterer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Prince Edward IslandMemorial University of Newfoundland
Fundersnot available
KeywordsHeat fluxMechanicsThermal conductionThermal resistanceTransient (computer programming)Materials scienceIsothermal processWork (physics)Context (archaeology)Heat transferGeometryThermodynamicsMathematicsPhysicsGeologyComposite materialComputer science

Abstract

fetched live from OpenAlex

Abstract Thermal spreading or constriction resistance plays an important role in thermal engineering problems. A numerical simulation is developed for transient constriction resistance considering various semi-infinite flux channel geometries, including circle on circle, circle on triangle, circle on square, circle on pentagon, and circle on hexagon. In this work, an isothermal circular heat source supplies heat in these polygonal flux channels. In this context, a finite volume method is considered to study the transient constriction resistance in mentioned geometries. After validating the steady-state mode for constant heat flux condition, the work is extended to study the transient heat conduction with constant temperature boundary condition. Observations of these various geometries clarify that similar results are produced for the non-dimensionalized constriction resistance and time. The appropriate characteristic length for this non-dimensionalization is the square root of the source area. Simple models are developed for predicting the transient spreading resistance for isothermal heat sources.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.453

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 head0.012
GPT teacher head0.201
Teacher spread0.188 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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