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Record W1970245417 · doi:10.1088/0960-1317/16/10/033

Slip-flow irreversibility of dissipative kinetic and internal energy exchange in microchannels

2006· article· en· W1970245417 on OpenAlexaff
Emmanuel O. Ogedengbe, G.F. Naterer, Marc A. Rosen

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2006
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsOntario Tech UniversityUniversity of Manitoba
Fundersnot available
KeywordsDissipative systemMechanicsKinetic energySlip (aerodynamics)Materials scienceFlow (mathematics)Energy exchangeClassical mechanicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The mechanisms of near-wall velocity slip and their effects on energy conversion of fluid motion in microchannels are investigated. Unlike large-scale channels with no-slip boundary conditions, this paper predicts how streamwise temperature gradients and transverse velocity gradients contribute to velocity slip during intermolecular interactions near a microchannel wall. A numerical formulation is developed with a mass-weighted convection scheme (called NISUS; non-inverted skew upwind scheme) in a SIMPLEC finite volume method. The new convection scheme provides accurate upstream interpolation of convection variables, including robust pressure/velocity coupling near the slip-flow boundary. Numerical predictions of entropy production characterize the near-wall dissipation of kinetic energy. Effects of varying pressure ratios, accommodation coefficients, flow rates and channel aspect ratios are presented for nitrogen gas flows between Re = 0.001 and 0.003. This paper gives new insight regarding dissipative kinetic and internal energy exchange in microchannels, due to slip-flow behavior.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.166
Teacher spread0.163 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

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