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Record W4401046840 · doi:10.1134/s0040601524700149

Multiphase Natural Convection Heat Sink for Information and Communications Technology Applications

2024· article· en· W4401046840 on OpenAlexaff
Frédéric J. Lesage, M. Aladji, R. Eugenie

Bibliographic record

VenueThermal Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsHeat sinkNatural convectionSink (geography)ConvectionEnvironmental scienceEngineeringMechanicsMechanical engineeringPetroleum engineeringPhysicsGeography

Abstract

fetched live from OpenAlex

Abstract The requirement for heat sinks to better reject excess thermal energy is ever increasing due to the recent improvements in output power capacity in the Information and Communications Technology (ICT) industry. Current ICT thermal management strategies rely on single phase heat transfer techniques which have attained their upper limit. The present work aims to demonstrate that two-phase thermal system strategies can decrease heat sink size. A comparison of the heat dissipation capacity of a natural convection heat sink with and without the thermal transport mechanism of vaporization are measured and discussed. A discussion relating to the mathematical analysis of the heat transfer mechanisms leads to quantified results showing the efficiency gains of a two phase micro-porous heat sink. It is shown that the presence of evaporation from the holes on the front surface of the radiator makes it possible to reduce its size by 37.6% compared to a radiator in which heat removal is carried out only by natural convection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.005
GPT teacher head0.213
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 source (direct Gemma or distilled Codex), 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

Citations2
Published2024
Admission routes1
Has abstractyes

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