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Record W2112826244 · doi:10.1115/ht2007-32191

Models for Gaseous Slip Flow in Non-Circular Microchannels

2007· article· en· W2112826244 on OpenAlexaff
Zhipeng Duan, Yuri S. Muzychka

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMicrochannelSlip (aerodynamics)MechanicsPressure dropReynolds numberLaminar flowMaterials scienceSlip ratioSlip factorMechanical engineeringEngineeringPhysicsAerospace engineeringShear stress

Abstract

fetched live from OpenAlex

Micro-scale fluid dynamics has received intensive interest due to the emergence of Micro-Electro-Mechanical Systems (MEMS) technology. Non-circular cross sections are common channel shapes that can be produced through a variety of micro-fabrication techniques. Non-circular microchannels have extensive practical applications in MEMS. Slip flow in noncircular microchannels has been examined by the authors and a review of several new models obtained by the authors is presented. These models are general and robust, and can be used by the research community for practical engineering design of microchannel flow systems. The reviewed models address: (i) fully developed slip flow in non-circular microchannels, (ii) hydrodynamically developing slip flow in non-circular microchannels, (iii) compressibility effects, and (iv) roughness effects. A model is proposed to predict the friction factor and Reynolds product fRe for fully developed and developing slip flow in most non-circular micro-channels. Compressibility effects on slip flow in non-circular microchannels have been examined and simple models are proposed to predict the pressure distribution and mass flow rate for slip flow in most non-circular microchannels. Finally, the effect of corrugated surface roughness on fully developed laminar flow in microtubes is examined. Simple analytical models are developed to predict friction factor and pressure drop in corrugated rough microtubes for continuum flow and slip flow.

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 score0.947
Threshold uncertainty score0.331

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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