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Record W4393207380 · doi:10.11159/jffhmt.2024.006

Heat-Kernel Parametric Model of Heat Transfer Through Layered Materials Coupled to Heat Sinks

2024· article· en· W4393207380 on OpenAlexvenueno aff
Edward Michaelchuck, Jesse Duncan, Scott Ramsey, Troy Mayo, Samuel G. Lambrakos

Bibliographic record

VenueJournal of Fluid Flow Heat and Mass Transfer · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsnot available
Fundersnot available
KeywordsHeat transferHeat sinkParametric statisticsMaterials scienceHeat kernelHeat spreaderMechanicsThermodynamicsPhysicsMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

A parametric model of heat transfer through layered materials is presented.This model is formally based on the heatkernel solution to the advection-diffusion equation, which is extended to include effects of multiple layers with varying thermal diffusivities, interface effects (e.g., large changes in thermal properties), contact resistance, and the effects of singular heat-sinks, represented by negative heat sources.This model provides parametric representations of temperature distributions within layered-material systems, which can be utilized for their design and optimization for layerconfiguration, including heat-sink control of thermal transport.Results of prototype modelling of controlled heat transfer in layered-material systems are presented and validated, demonstrating general aspects of the parametric model for thermal analysis and simulation of heat-transfer control using layer configurations and embedded heat sinks.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.342
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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