MétaCan
Menu
Back to cohort
Record W2142415302 · doi:10.2514/1.t4328

Dynamic Heat Transfer Inside Multilayered Packages with Arbitrary Heat Generations

2014· article· en· W2142415302 on OpenAlexaff
M. Fakoor-Pakdaman, Mehran Ahmadi, Farshid Bagheri, Majid Bahrami

Bibliographic record

VenueJournal of Thermophysics and Heat Transfer · 2014
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHeat fluxMaterials scienceHeat transferThermal conductionMechanicsCoolantDimensionless quantityTransient (computer programming)CylinderThermodynamicsPhysicsMechanical engineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

In most engineering applications, e.g., hybrid electric vehicles, the multilayered electronic packages generate arbitrary heat over a transient thermal duty cycle. In addition, the outer surface of such media endures time-dependent temperature as a result of variable coolant temperature during driving/duty cycles. As such, a new analytical model is developed to predict transient heat conduction inside multilayered composite media with arbitrary heat generation inside the layers. It is assumed that the temperature of the outer surface varies periodically over time. New compact closed-form relationships are developed for calculating 1) the temperature distribution inside multilayered media, 2) the average temperature of each layer, and 3) the interfacial heat flux. As an example, the methodology is applied to a two-concentric-cylinder composite. A detailed parametric study is conducted, and the critical values for the dimensionless parameters are evaluated; beyond these values, the temperature field inside the media is not affected considerably for any combination of other variables. It is shown that there is an optimum angular frequency that maximizes the amplitude of the interfacial heat flux. An independent numerical simulation is also performed using commercially available software ANSYS; the maximum relative difference between the obtained numerical data and the analytical model is less than 2%.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.961

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Thermophysics and Heat TransferSame topicHeat Transfer and OptimizationFrench-language works237,207