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Record W4237122997 · doi:10.5383/ijtee.13.02.009

Revamped Cooling of a Rectangular Shaped Chip Inserting a Highly Conductive Solid: Coupled vs. Uncoupled Conceptions

2017· article· en· W4237122997 on OpenAlexvenueno aff
M Hajmohamdami, Antonio Campo

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsHeat sinkChipMaterials scienceHeat fluxElectrical conductorInsert (composites)Thermal conductionThermal conductivityVolume fractionThermalComposite materialMechanicsThermodynamicsHeat transferElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

The performance of highly conductive inserts embedded into a heated chip has been investigated in recent years. The role of the insert was to gather the heat current within the chip and remove it to a low temperature heat sink. The central goal of this study is to invoke several reconsiderations, which results in the plausible reduction of the peak temperature in a heated rectangular chip in comparison with the lowest peak temperature achieved in previous works. It is proved that for the configuration under study with its bottom surface receiving a constant uniform heat flux, the branching patterns of the insert must be avoided, instead the appropriate revisions in the architecture (width, location and cross section area) of the insert are accounted for the simple patterns. An uncoupled analytical solution for predicting the peak temperatures in the rectangular chip containing the cooling insert is also addressed. It is also proved that under the same volume fraction and thermal conductivity of the insert, the peak temperature can be reduced to 2.9 °C, which is 94% below the lowest temperature reported in the archival literature, which was around 50.5 °C.

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 score0.595
Threshold uncertainty score0.502

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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
Published2017
Admission routes1
Has abstractyes

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