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Experimental demonstration of a tailored-width microchannel heat exchanger configuration for uniform wall temperature

2013· article· en· W2012365489 on OpenAlexaff
Sara Riera, Jérôme Barrau, Jordi Rosell, Mohamed Omri, Luc G. Fréchette

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMicrochannelHeat sinkMaterials scienceHeat fluxHeat exchangerMechanicsThermal resistanceMicro heat exchangerThermodynamicsVolumetric flow rateWork (physics)Heat spreaderThermalHeat transferPlate heat exchangerPhysicsNanotechnology

Abstract

fetched live from OpenAlex

In this work, an experimental study of a novel microfabricated heat sink configuration that tends to uniform the wall temperature, even with increasing flow temperature, is presented. The design consists of a series of microchannel sections with stepwise varying width. This scheme counteracts the flow temperature increase by reducing the local thermal resistance along the flow path. A test apparatus with uniform heat flux and distributed wall temperature measurements was developed for microchannel heat exchanger characterisation. The energy balance is checked and the temperature distribution is analysed for each test. The results show that the wall temperature decreases slightly along the flow path while the fluid temperature increases, highlighting the strong impact of this approach. For a flow rate of 16 ml/s, the mean thermal resistance of the heat sink is 2,35·10 −5 m 2 ·K/W which enhances the results compared to the millimeter scale channels nearly three-fold. For the same flow rate and a heat flux of 50 W/cm 2 , the temperature uniformity, expressed as the standard deviation of the wall temperature, is around 6 °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 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: Bench or experimental · Consensus signal: Bench or experimental
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 science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.219
Teacher spread0.204 · 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 designBench or experimental
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

Citations15
Published2013
Admission routes1
Has abstractyes

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