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Thermal Resistance of a Two Dimensional Flux Channel with Eccentric Heat Source and Asymmteric Edge Cooling

2024· article· en· W4394596689 on OpenAlexafffund
M. Razavi, Yuri S. Muzychka, Serpil Kocabiyik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsMemorial University of NewfoundlandNew York Institute of Technology
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeat fluxThermal resistanceEnhanced Data Rates for GSM EvolutionMaterials scienceThermalFlux (metallurgy)MechanicsChannel (broadcasting)Heat transferThermodynamicsPhysicsElectrical engineeringComputer scienceEngineeringMetallurgyTelecommunications

Abstract

fetched live from OpenAlex

In this paper, an analytical solution is presented for the temperature profile and thermal resistance of a non-symmetrical flux channel with convective cooling along the sink plane and edges. The heat transfer coefficients along the right and left edges of the channel are defined separately and both are independent from the heat transfer coefficient applied over the sink plane. The system is solved using the method of separation of variables. Due to the edge cooling and non-symmetry, the eigenvalues should be calculated using the heat transfer coefficient on both edges. For satisfying the orthogonality condition, a normalized function is defined. The temperature distribution over the channel is presented in the form of a Fourier series expansion and some expressions are presented to calculate the thermal resistance and dimensionless thermal resistance. Some case studies are considered and the results are compared with other literature and the Finite Element Method (FEM) using COMSOL commercial software package [1]. The proposed model is useful for thermal engineers who wish to model micro-electronic devices with different conductance and heat sink configurations.

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: none
Teacher disagreement score0.524
Threshold uncertainty score0.268

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 head0.006
GPT teacher head0.196
Teacher spread0.189 · 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
Published2024
Admission routes2
Has abstractyes

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