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Record W2069472731 · doi:10.1115/icnmm2011-58002

Numerical Simulation of a Novel Jet-Impingement Micro Heat Sink With Cross Flow Under Non Uniform Heating Condition

2011· article· en· W2069472731 on OpenAlexaff
Yanfeng Fan, Ibrahim Hassan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceHeat sinkNusselt numberHeat fluxMechanicsHeat transfer coefficientPressure dropHeat transferMicrochannelThermal resistanceThermodynamicsReynolds numberPhysicsTurbulence

Abstract

fetched live from OpenAlex

A novel micro heat sink applying the jet-impingement and cross flow is proposed to dissipate the heat from the electrical devices. Six hotspots of 2 mm × 2 mm are positioned on a flat plate of 25.4 mm × 25.4 mm. The area of flat plate except the hotspots is provided a constant heat flux of 20 W/cm2 as background heating source among cases. Four heat fluxes from 40 to 100 W/cm2 on the hotspots are tested to simulate the different operation conditions. The cross flow is used to remove the background heat flux and jet flow is supplied into the swirl microchannel, located at the right top of hotspot, to dissipate the large heat flux from hotspots. The channel depth is 0.5 mm and the width of swirl microchannel is 0.38 mm. The cross flow and jet flow velocity vary from 0.1 m/s to 0.5 m/s and from 0.5 m/s to 2 m/s, respectively. The effects of cross flow and jet flow on the cooling performance are investigated by numerical simulation. The local heat transfer coefficient and Nusselt number are calculated to evaluate the cooling performance of proposed micro heat sink for the targets of low maximum temperature, temperature gradient and pressure drop. The results show that the maximum temperature of the proposed design occurred at the outlet is approximately 65 °C among tested cases. The corresponding pressure drop is 5.5 kPa. The overall thermal resistance reaches as small as 0.23 K/W.

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 score0.600
Threshold uncertainty score0.611

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 head0.030
GPT teacher head0.255
Teacher spread0.225 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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