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Record W1984517618 · doi:10.1115/fedsm-icnmm2010-30770

Cooling in Constant Wall Temperature Microchannels With Thermal Creep Effects

2010· article· en· W1984517618 on OpenAlexafffund
Ali Amiri-Jaghargh, Hamid Niazmand, Metin Renksizbulut

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaFerdowsi University of Mashhad
KeywordsTemperature jumpMechanicsMaterials scienceMicrochannelInletHeat transferSlip (aerodynamics)ThermodynamicsKnudsen numberCreepThermal conductionAdiabatic wallAdiabatic processReynolds numberComposite materialPhysicsMechanical engineeringTurbulence

Abstract

fetched live from OpenAlex

Fluid flow and heat transfer in the entrance region of rectangular microchannels of various aspect ratios, 0.2 ≤ α* ≤ 1, are numerically investigated in the slip flow regime, 10−3 ≤ Kn ≤ 10−1, with particular attention to the thermal creep effects. Uniform inlet velocity and temperature profiles are prescribed in a microchannel with constant wall temperature. The gas inlet temperature is prescribed higher than the wall temperature in order to study the thermal creep effects in a fluid cooling process. To avoid unrealistically large axial temperature gradients due to the prescribed uniform inlet temperature and upstream conduction associated with low Reynolds number flows encountered in microchannels, an adiabatic section is added to the inlet of the channel, which resembles an adiabatic reservoir. A control volume technique is employed to solve the Navier-Stokes and energy equations which are accompanied with appropriate velocity-slip and temperature-jump boundary conditions at walls. Despite the constant wall temperature, axial and peripheral temperature gradients form in the gas layer adjacent to the wall due to temperature-jump. The simultaneous effects of velocity-slip, temperature-jump and thermal creep on the flow and thermal patterns along with the key flow parameters are examined in detail for a wide range of cross sectional aspect ratios, and Knudsen and Reynolds numbers (0.1 ≤ Re ≤ 5). Present results indicate that thermal creep effects influence the flow field and the temperature distribution significantly in the early section of the channel.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.295

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 head0.002
GPT teacher head0.171
Teacher spread0.169 · 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 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

Citations1
Published2010
Admission routes2
Has abstractyes

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